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Where is Bitcoin Going and When?

Where is Bitcoin Going and When?

The Federal Reserve and the United States government are pumping extreme amounts of money into the economy, already totaling over $484 billion. They are doing so because it already had a goal to inflate the United States Dollar (USD) so that the market can continue to all-time highs. It has always had this goal. They do not care how much inflation goes up by now as we are going into a depression with the potential to totally crash the US economy forever. They believe the only way to save the market from going to zero or negative values is to inflate it so much that it cannot possibly crash that low. Even if the market does not dip that low, inflation serves the interest of powerful people.
The impending crash of the stock market has ramifications for Bitcoin, as, though there is no direct ongoing-correlation between the two, major movements in traditional markets will necessarily affect Bitcoin. According to the Blockchain Center’s Cryptocurrency Correlation Tool, Bitcoin is not correlated with the stock market. However, when major market movements occur, they send ripples throughout the financial ecosystem which necessary affect even ordinarily uncorrelated assets.
Therefore, Bitcoin will reach X price on X date after crashing to a price of X by X date.

Stock Market Crash

The Federal Reserve has caused some serious consternation with their release of ridiculous amounts of money in an attempt to buoy the economy. At face value, it does not seem to have any rationale or logic behind it other than keeping the economy afloat long enough for individuals to profit financially and politically. However, there is an underlying basis to what is going on which is important to understand in order to profit financially.
All markets are functionally price probing systems. They constantly undergo a price-discovery process. In a fiat system, money is an illusory and a fundamentally synthetic instrument with no intrinsic value – similar to Bitcoin. The primary difference between Bitcoin is the underlying technology which provides a slew of benefits that fiat does not. Fiat, however, has an advantage in being able to have the support of powerful nation-states which can use their might to insure the currency’s prosperity.
Traditional stock markets are composed of indices (pl. of index). Indices are non-trading market instruments which are essentially summaries of business values which comprise them. They are continuously recalculated throughout a trading day, and sometimes reflected through tradable instruments such as Exchange Traded Funds or Futures. Indices are weighted by market capitalizations of various businesses.
Price theory essentially states that when a market fails to take out a new low in a given range, it will have an objective to take out the high. When a market fails to take out a new high, it has an objective to make a new low. This is why price-time charts go up and down, as it does this on a second-by-second, minute-by-minute, day-by-day, and even century-by-century basis. Therefore, market indices will always return to some type of bull market as, once a true low is formed, the market will have a price objective to take out a new high outside of its’ given range – which is an all-time high. Instruments can only functionally fall to zero, whereas they can grow infinitely.
So, why inflate the economy so much?
Deflation is disastrous for central banks and markets as it raises the possibility of producing an overall price objective of zero or negative values. Therefore, under a fractional reserve system with a fiat currency managed by a central bank – the goal of the central bank is to depreciate the currency. The dollar is manipulated constantly with the intention of depreciating its’ value.
Central banks have a goal of continued inflated fiat values. They tend to ordinarily contain it at less than ten percent (10%) per annum in order for the psyche of the general populace to slowly adjust price increases. As such, the markets are divorced from any other logic. Economic policy is the maintenance of human egos, not catering to fundamental analysis. Gross Domestic Product (GDP) growth is well-known not to be a measure of actual growth or output. It is a measure of increase in dollars processed. Banks seek to produce raising numbers which make society feel like it is growing economically, making people optimistic. To do so, the currency is inflated, though inflation itself does not actually increase growth. When society is optimistic, it spends and engages in business – resulting in actual growth. It also encourages people to take on credit and debts, creating more fictional fiat.
Inflation is necessary for markets to continue to reach new heights, generating positive emotional responses from the populace, encouraging spending, encouraging debt intake, further inflating the currency, and increasing the sale of government bonds. The fiat system only survives by generating more imaginary money on a regular basis.
Bitcoin investors may profit from this by realizing that stock investors as a whole always stand to profit from the market so long as it is managed by a central bank and does not collapse entirely. If those elements are filled, it has an unending price objective to raise to new heights. It also allows us to realize that this response indicates that the higher-ups believe that the economy could crash in entirety, and it may be wise for investors to have multiple well-thought-out exit strategies.

Economic Analysis of Bitcoin

The reason why the Fed is so aggressively inflating the economy is due to fears that it will collapse forever or never rebound. As such, coupled with a global depression, a huge demand will appear for a reserve currency which is fundamentally different than the previous system. Bitcoin, though a currency or asset, is also a market. It also undergoes a constant price-probing process. Unlike traditional markets, Bitcoin has the exact opposite goal. Bitcoin seeks to appreciate in value and not depreciate. This has a quite different affect in that Bitcoin could potentially become worthless and have a price objective of zero.
Bitcoin was created in 2008 by a now famous mysterious figure known as Satoshi Nakamoto and its’ open source code was released in 2009. It was the first decentralized cryptocurrency to utilize a novel protocol known as the blockchain. Up to one megabyte of data may be sent with each transaction. It is decentralized, anonymous, transparent, easy to set-up, and provides myriad other benefits. Bitcoin is not backed up by anything other than its’ own technology.
Bitcoin is can never be expected to collapse as a framework, even were it to become worthless. The stock market has the potential to collapse in entirety, whereas, as long as the internet exists, Bitcoin will be a functional system with a self-authenticating framework. That capacity to persist regardless of the actual price of Bitcoin and the deflationary nature of Bitcoin means that it has something which fiat does not – inherent value.
Bitcoin is based on a distributed database known as the “blockchain.” Blockchains are essentially decentralized virtual ledger books, replete with pages known as “blocks.” Each page in a ledger is composed of paragraph entries, which are the actual transactions in the block.
Blockchains store information in the form of numerical transactions, which are just numbers. We can consider these numbers digital assets, such as Bitcoin. The data in a blockchain is immutable and recorded only by consensus-based algorithms. Bitcoin is cryptographic and all transactions are direct, without intermediary, peer-to-peer.
Bitcoin does not require trust in a central bank. It requires trust on the technology behind it, which is open-source and may be evaluated by anyone at any time. Furthermore, it is impossible to manipulate as doing so would require all of the nodes in the network to be hacked at once – unlike the stock market which is manipulated by the government and “Market Makers”. Bitcoin is also private in that, though the ledge is openly distributed, it is encrypted. Bitcoin’s blockchain has one of the greatest redundancy and information disaster recovery systems ever developed.
Bitcoin has a distributed governance model in that it is controlled by its’ users. There is no need to trust a payment processor or bank, or even to pay fees to such entities. There are also no third-party fees for transaction processing. As the ledge is immutable and transparent it is never possible to change it – the data on the blockchain is permanent. The system is not easily susceptible to attacks as it is widely distributed. Furthermore, as users of Bitcoin have their private keys assigned to their transactions, they are virtually impossible to fake. No lengthy verification, reconciliation, nor clearing process exists with Bitcoin.
Bitcoin is based on a proof-of-work algorithm. Every transaction on the network has an associated mathetical “puzzle”. Computers known as miners compete to solve the complex cryptographic hash algorithm that comprises that puzzle. The solution is proof that the miner engaged in sufficient work. The puzzle is known as a nonce, a number used only once. There is only one major nonce at a time and it issues 12.5 Bitcoin. Once it is solved, the fact that the nonce has been solved is made public.
A block is mined on average of once every ten minutes. However, the blockchain checks every 2,016,000 minutes (approximately four years) if 201,600 blocks were mined. If it was faster, it increases difficulty by half, thereby deflating Bitcoin. If it was slower, it decreases, thereby inflating Bitcoin. It will continue to do this until zero Bitcoin are issued, projected at the year 2140. On the twelfth of May, 2020, the blockchain will halve the amount of Bitcoin issued when each nonce is guessed. When Bitcoin was first created, fifty were issued per block as a reward to miners. 6.25 BTC will be issued from that point on once each nonce is solved.
Unlike fiat, Bitcoin is a deflationary currency. As BTC becomes scarcer, demand for it will increase, also raising the price. In this, BTC is similar to gold. It is predictable in its’ output, unlike the USD, as it is based on a programmed supply. We can predict BTC’s deflation and inflation almost exactly, if not exactly. Only 21 million BTC will ever be produced, unless the entire network concedes to change the protocol – which is highly unlikely.
Some of the drawbacks to BTC include congestion. At peak congestion, it may take an entire day to process a Bitcoin transaction as only three to five transactions may be processed per second. Receiving priority on a payment may cost up to the equivalent of twenty dollars ($20). Bitcoin mining consumes enough energy in one day to power a single-family home for an entire week.

Trading or Investing?

The fundamental divide in trading revolves around the question of market structure. Many feel that the market operates totally randomly and its’ behavior cannot be predicted. For the purposes of this article, we will assume that the market has a structure, but that that structure is not perfect. That market structure naturally generates chart patterns as the market records prices in time. In order to determine when the stock market will crash, causing a major decline in BTC price, we will analyze an instrument, an exchange traded fund, which represents an index, as opposed to a particular stock. The price patterns of the various stocks in an index are effectively smoothed out. In doing so, a more technical picture arises. Perhaps the most popular of these is the SPDR S&P Standard and Poor 500 Exchange Traded Fund ($SPY).
In trading, little to no concern is given about value of underlying asset. We are concerned primarily about liquidity and trading ranges, which are the amount of value fluctuating on a short-term basis, as measured by volatility-implied trading ranges. Fundamental analysis plays a role, however markets often do not react to real-world factors in a logical fashion. Therefore, fundamental analysis is more appropriate for long-term investing.
The fundamental derivatives of a chart are time (x-axis) and price (y-axis). The primary technical indicator is price, as everything else is lagging in the past. Price represents current asking price and incorrectly implementing positions based on price is one of the biggest trading errors.
Markets and currencies ordinarily have noise, their tendency to back-and-fill, which must be filtered out for true pattern recognition. That noise does have a utility, however, in allowing traders second chances to enter favorable positions at slightly less favorable entry points. When you have any market with enough liquidity for historical data to record a pattern, then a structure can be divined. The market probes prices as part of an ongoing price-discovery process. Market technicians must sometimes look outside of the technical realm and use visual inspection to ascertain the relevance of certain patterns, using a qualitative eye that recognizes the underlying quantitative nature
Markets and instruments rise slower than they correct, however they rise much more than they fall. In the same vein, instruments can only fall to having no worth, whereas they could theoretically grow infinitely and have continued to grow over time. Money in a fiat system is illusory. It is a fundamentally synthetic instrument which has no intrinsic value. Hence, the recent seemingly illogical fluctuations in the market.
According to trade theory, the unending purpose of a market or instrument is to create and break price ranges according to the laws of supply and demand. We must determine when to trade based on each market inflection point as defined in price and in time as opposed to abandoning the trend (as the contrarian trading in this sub often does). Time and Price symmetry must be used to be in accordance with the trend. When coupled with a favorable risk to reward ratio, the ability to stay in the market for most of the defined time period, and adherence to risk management rules; the trader has a solid methodology for achieving considerable gains.
We will engage in a longer term market-oriented analysis to avoid any time-focused pressure. The Bitcoin market is open twenty-four-hours a day, so trading may be done when the individual is ready, without any pressing need to be constantly alert. Let alone, we can safely project months in advance with relatively high accuracy. Bitcoin is an asset which an individual can both trade and invest, however this article will be focused on trading due to the wide volatility in BTC prices over the short-term.

Technical Indicator Analysis of Bitcoin

Technical indicators are often considered self-fulfilling prophecies due to mass-market psychology gravitating towards certain common numbers yielded from them. They are also often discounted when it comes to BTC. That means a trader must be especially aware of these numbers as they can prognosticate market movements. Often, they are meaningless in the larger picture of things.
  • Volume – derived from the market itself, it is mostly irrelevant. The major problem with volume for stocks is that the US market open causes tremendous volume surges eradicating any intrinsic volume analysis. This does not occur with BTC, as it is open twenty-four-seven. At major highs and lows, the market is typically anemic. Most traders are not active at terminal discretes (peaks and troughs) because of levels of fear. Volume allows us confidence in time and price symmetry market inflection points, if we observe low volume at a foretold range of values. We can rationalize that an absolute discrete is usually only discovered and anticipated by very few traders. As the general market realizes it, a herd mentality will push the market in the direction favorable to defending it. Volume is also useful for swing trading, as chances for swing’s validity increases if an increase in volume is seen on and after the swing’s activation. Volume is steadily decreasing. Lows and highs are reached when volume is lower.
Therefore, due to the relatively high volume on the 12th of March, we can safely determine that a low for BTC was not reached.
  • VIX – Volatility Index, this technical indicator indicates level of fear by the amount of options-based “insurance” in portfolios. A low VIX environment, less than 20 for the S&P index, indicates a stable market with a possible uptrend. A high VIX, over 20, indicates a possible downtrend. VIX is essentially useless for BTC as BTC-based options do not exist. It allows us to predict the market low for $SPY, which will have an indirect impact on BTC in the short term, likely leading to the yearly low. However, it is equally important to see how VIX is changing over time, if it is decreasing or increasing, as that indicates increasing or decreasing fear. Low volatility allows high leverage without risk or rest. Occasionally, markets do rise with high VIX.
As VIX is unusually high, in the forties, we can be confident that a downtrend for the S&P 500 is imminent.
  • RSI (Relative Strength Index): The most important technical indicator, useful for determining highs and lows when time symmetry is not availing itself. Sometimes analysis of RSI can conflict in different time frames, easiest way to use it is when it is at extremes – either under 30 or over 70. Extremes can be used for filtering highs or lows based on time-and-price window calculations. Highly instructive as to major corrective clues and indicative of continued directional movement. Must determine if longer-term RSI values find support at same values as before. It is currently at 73.56.
  • Secondly, RSI may be used as a high or low filter, to observe the level that short-term RSI reaches in counter-trend corrections. Repetitions based on market movements based on RSI determine how long a trade should be held onto. Once a short term RSI reaches an extreme and stay there, the other RSI’s should gradually reach the same extremes. Once all RSI’s are at extreme highs, a trend confirmation should occur and RSI’s should drop to their midpoint.

Trend Definition Analysis of Bitcoin

Trend definition is highly powerful, cannot be understated. Knowledge of trend logic is enough to be a profitable trader, yet defining a trend is an arduous process. Multiple trends coexist across multiple time frames and across multiple market sectors. Like time structure, it makes the underlying price of the instrument irrelevant. Trend definitions cannot determine the validity of newly formed discretes. Trend becomes apparent when trades based in counter-trend inflection points continue to fail.
Downtrends are defined as an instrument making lower lows and lower highs that are recurrent, additive, qualified swing setups. Downtrends for all instruments are similar, except forex. They are fast and complete much quicker than uptrends. An average downtrend is 18 months, something which we will return to. An uptrend inception occurs when an instrument reaches a point where it fails to make a new low, then that low will be tested. After that, the instrument will either have a deep range retracement or it may take out the low slightly, resulting in a double-bottom. A swing must eventually form.
A simple way to roughly determine trend is to attempt to draw a line from three tops going upwards (uptrend) or a line from three bottoms going downwards (downtrend). It is not possible to correctly draw a downtrend line on the BTC chart, but it is possible to correctly draw an uptrend – indicating that the overall trend is downwards. The only mitigating factor is the impending stock market crash.

Time Symmetry Analysis of Bitcoin

Time is the movement from the past through the present into the future. It is a measurement in quantified intervals. In many ways, our perception of it is a human construct. It is more powerful than price as time may be utilized for a trade regardless of the market inflection point’s price. Were it possible to perfectly understand time, price would be totally irrelevant due to the predictive certainty time affords. Time structure is easier to learn than price, but much more difficult to apply with any accuracy. It is the hardest aspect of trading to learn, but also the most rewarding.
Humans do not have the ability to recognize every time window, however the ability to define market inflection points in terms of time is the single most powerful trading edge. Regardless, price should not be abandoned for time alone. Time structure analysis It is inherently flawed, as such the markets have a fail-safe, which is Price Structure. Even though Time is much more powerful, Price Structure should never be completely ignored. Time is the qualifier for Price and vice versa. Time can fail by tricking traders into counter-trend trading.
Time is a predestined trade quantifier, a filter to slow trades down, as it allows a trader to specifically focus on specific time windows and rest at others. It allows for quantitative measurements to reach deterministic values and is the primary qualifier for trends. Time structure should be utilized before price structure, and it is the primary trade criterion which requires support from price. We can see price structure on a chart, as areas of mathematical support or resistance, but we cannot see time structure.
Time may be used to tell us an exact point in the future where the market will inflect, after Price Theory has been fulfilled. In the present, price objectives based on price theory added to possible future times for market inflection points give us the exact time of market inflection points and price.
Time Structure is repetitions of time or inherent cycles of time, occurring in a methodical way to provide time windows which may be utilized for inflection points. They are not easily recognized and not easily defined by a price chart as measuring and observing time is very exact. Time structure is not a science, yet it does require precise measurements. Nothing is certain or definite. The critical question must be if a particular approach to time structure is currently lucrative or not.
We will measure it in intervals of 180 bars. Our goal is to determine time windows, when the market will react and when we should pay the most attention. By using time repetitions, the fact that market inflection points occurred at some point in the past and should, therefore, reoccur at some point in the future, we should obtain confidence as to when SPY will reach a market inflection point. Time repetitions are essentially the market’s memory. However, simply measuring the time between two points then trying to extrapolate into the future does not work. Measuring time is not the same as defining time repetitions. We will evaluate past sessions for market inflection points, whether discretes, qualified swings, or intra-range. Then records the times that the market has made highs or lows in a comparable time period to the future one seeks to trade in.
What follows is a time Histogram – A grouping of times which appear close together, then segregated based on that closeness. Time is aligned into combined histogram of repetitions and cycles, however cycles are irrelevant on a daily basis. If trading on an hourly basis, do not use hours.
  • Yearly Lows (last seven years): 1/1/13, 4/10/14, 1/15/15, 1/17/16, 1/1/17, 12/15/18, 2/6/19
  • Monthly Mode: 1, 1, 1, 1, 2, 4, 12
  • Daily Mode: 1, 1, 6, 10, 15, 15, 17
  • Monthly Lows (for the last year): 3/12/20 (10:00pm), 2/28/20 (7:09am), 1/2/20 (8:09pm), 12/18/19 (8:00am), 11/25/19 (1:00am), 10/24/19 (2:59am), 9/30/19 (2:59am), 8/29,19 (4:00am), 7/17/19 (7:59am), 6/4/19 (5:59pm), 5/1/19 (12:00am), 4/1/19 (12:00am)
  • Daily Lows Mode for those Months: 1, 1, 2, 4, 12, 17, 18, 24, 25, 28, 29, 30
  • Hourly Lows Mode for those Months (Military time): 0100, 0200, 0200, 0400, 0700, 0700, 0800, 1200, 1200, 1700, 2000, 2200
  • Minute Lows Mode for those Months: 00, 00, 00, 00, 00, 00, 09, 09, 59, 59, 59, 59
  • Day of the Week Lows (last twenty-six weeks):
Weighted Times are repetitions which appears multiple times within the same list, observed and accentuated once divided into relevant sections of the histogram. They are important in the presently defined trading time period and are similar to a mathematical mode with respect to a series. Phased times are essentially periodical patterns in histograms, though they do not guarantee inflection points
Evaluating the yearly lows, we see that BTC tends to have its lows primarily at the beginning of every year, with a possibility of it being at the end of the year. Following the same methodology, we get the middle of the month as the likeliest day. However, evaluating the monthly lows for the past year, the beginning and end of the month are more likely for lows.
Therefore, we have two primary dates from our histogram.
1/1/21, 1/15/21, and 1/29/21
2:00am, 8:00am, 12:00pm, or 10:00pm
In fact, the high for this year was February the 14th, only thirty days off from our histogram calculations.
The 8.6-Year Armstrong-Princeton Global Economic Confidence model states that 2.15 year intervals occur between corrections, relevant highs and lows. 2.15 years from the all-time peak discrete is February 9, 2020 – a reasonably accurate depiction of the low for this year (which was on 3/12/20). (Taking only the Armstrong model into account, the next high should be Saturday, April 23, 2022). Therefore, the Armstrong model indicates that we have actually bottomed out for the year!
Bear markets cannot exist in perpetuity whereas bull markets can. Bear markets will eventually have price objectives of zero, whereas bull markets can increase to infinity. It can occur for individual market instruments, but not markets as a whole. Since bull markets are defined by low volatility, they also last longer. Once a bull market is indicated, the trader can remain in a long position until a new high is reached, then switch to shorts. The average bear market is eighteen months long, giving us a date of August 19th, 2021 for the end of this bear market – roughly speaking. They cannot be shorter than fifteen months for a central-bank controlled market, which does not apply to Bitcoin. (Otherwise, it would continue until Sunday, September 12, 2021.) However, we should expect Bitcoin to experience its’ exponential growth after the stock market re-enters a bull market.
Terry Laundy’s T-Theory implemented by measuring the time of an indicator from peak to trough, then using that to define a future time window. It is similar to an head-and-shoulders pattern in that it is the process of forming the right side from a synthetic technical indicator. If the indicator is making continued lows, then time is recalculated for defining the right side of the T. The date of the market inflection point may be a price or indicator inflection date, so it is not always exactly useful. It is better to make us aware of possible market inflection points, clustered with other data. It gives us an RSI low of May, 9th 2020.
The Bradley Cycle is coupled with volatility allows start dates for campaigns or put options as insurance in portfolios for stocks. However, it is also useful for predicting market moves instead of terminal dates for discretes. Using dates which correspond to discretes, we can see how those dates correspond with changes in VIX.
Therefore, our timeline looks like:
  • 2/14/20 – yearly high ($10372 USD)
  • 3/12/20 – yearly low thus far ($3858 USD)
  • 5/9/20 – T-Theory true yearly low (BTC between 4863 and 3569)
  • 5/26/20 – hashrate difficulty halvening
  • 11/14/20 – stock market low
  • 1/15/21 – yearly low for BTC, around $8528
  • 8/19/21 – end of stock bear market
  • 11/26/21 – eighteen months from halvening, average peak from halvenings (BTC begins rising from $3000 area to above $23,312)
  • 4/23/22 – all-time high
Taken from my blog: http://aliamin.info/2020/
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Libra + eUSD = Bitcoin Bull

(Oddly I posted this in /bitcoins and it was no idea why as it meets all rules...)
Here’s my theory around the last 24 hours and why the next year is going to be one hell of a good ride for Bitcoin...
Take a minute and consider how price responded the week Facebook announced Libra... the addition of 2 billion digital wallets, regardless that the focus was not on Bitcoin was a huge positive for us. As the Senate, the Fed.. mainstream media... all poo-poo’d the idea we then saw correlated pullback in price. Recently big names have been jumping ship... further eroding the hope for those +2 billion wallets. Enter the digital dollar discussion....
https://techcrunch.com/2019/10/20/in-a-big-reversal-libra-reportedly-could-peg-its-cryptocurrencies-to-national-currencies/
(Similar article is on Bloomberg behind a paywall if someone can grab it.. )
The timing of this discussion couldn’t be better. Last week the former chairman of the Commodity Futures Trading Commission took out a full page ad pushing the eUSD along with this opinion piece.
https://www.wsj.com/articles/we-sent-a-man-to-the-moon-we-can-send-the-dollar-to-cyberspace-11571179923
And then we had both the European Central Bank and some at our own Fed begin openly considering or endorsing the idea..
Germany’s finance minister in July stated they could not allow Libra, now he’s pushing for a national German cryptocurrency... https://www.theblockcrypto.com/linked/42244/german-finance-minister-olaf-scholz-wants-to-introduce-digital-euro
Members of Congress have formally asked the Fed to get on board..
https://www.coindesk.com/us-congressmen-ask-fed-to-consider-developing-national-digital-currency
And now even the Fed admits it is ‘actively debating’ the idea when just two months ago they stated there was no need or interest to do so
https://www.coindesk.com/top-fed-official-says-us-central-bank-actively-debating-digital-dollar
Even mainstream financial conversation are starting to see the benefits of the eUSD especially as we get closer to the next recession
https://www.marketwatch.com/story/why-the-coming-recession-could-force-the-federal-reserve-to-swap-greenbacks-for-digital-dollars-2019-09-06
The people behind LIbra project are now shifting their position and considering not using a ‘synthetic basket’ of currencies but instead peg the Libra directly to national digital currencies. Even better, Zuckerberg is scheduled to testify in form of Congress Oct 23 (Wednesday) and I will place a strong bet that his response to attackers on the Libra project will be what his team just ‘floated’... “Fine, if you launch a digital currency (eUSD) then we will build on top of that and all (most) of your concerns will disappear.....but if you don’t we are moving forward regardless”.
We will then spend the next 3-4 months watching the debate in Washington to launch eUSD accelerate 10x... with a lot of movement but in general half commitments and vague statements... until eYuan. China has already stated they are working on their own digital currency and while they backpedaled a bit last month, that was likely due to difficulties on the development side (cause, you know...coding is hard) and not a real change in intention or goals. They want a digital currency that allows them to shift the commerce they control to something other then the USD. They do trillions of business with countries other then the US and so the move has real implications (note the US is actually China’s third largest trading partner exporting $1.6 trillion. In 2018). It not only reduces the power the dollar has over them, it helps blunts the impacts US tariffs have on their economy.
Immediately after China’s official announcements, the US will likely act like they’ve been ‘onboard’ to launch the eUSD from the beginning, and are working quickly to get there. These two world leaders, China and US will create far more then Facebooks 2 billion digital wallets... and the new space race to launch a digital currency will have been started for EVERY country in the world. I’d expect the eEuro will announce sometime after China and the US, they tend to need to talk and debate for 2x longer then other countries on major EU policies (which is understandable given their diverse political make-up).
Here’s the timeline I see as realistic:

And to be clear, Bitcoin doesn’t need to be ‘the’ currency... but it will almost certainly be available in 99% of all digital wallets people use. It might not be in the official Chinese or US wallet but no one will use ‘just those’... and it’s digital so it really doesn’t matter. The eUSD and eYuan will trade on the same exchanges you trade bitcoin today, even better the lines between traditional forex trading and crypto trading will almost immediately blur. The confidence in Bitcoin, and blockchain as a whole will SKYROCKET... Imagine 2billion+ crypto onramps... that don't require fiat deposits because your national currency is already digital.
The second greatest thing to happen with Bitcoin price will be an the launch of an ETF.. but I’ll explain why that will happen in the next 12 months as well, in my next post.
Btw, this is obviously all just my opinion and I am posting so that others (possibly smarter then myself) can punch holes and refine the theory. So you don’t need to be a dick, just explain where or why my hypothesis breaks down and let’s figure this shit out.
-peace out.
submitted by bitradr to BitcoinMarkets [link] [comments]

The crypto market’s correlation with traditional markets (by Robert Aron Zawiasa)

https://medium.com/@Zawiasa/the-crypto-markets-correlation-with-traditional-markets-79e8209a6d8
At the time of Corona virus and the — not so related — economic meltdown, many questions the correlation between the virtual economy of cryptocurrencies and the “trad” one.
Why is it such an important question? For many years crypto evangelists predicted Bitcoin as a new safe-haven, the “digital gold”. — Oh boy, they were wrong.
The correlation is not imaginary, trad market players now have significant capital in cryptocurrency and when they need to pull liquidity to cover fiat liabilities, they just do it. The reason for the steep drop in % terms is because the BTC market is not liquid enough at this point in time.
Is it a problem? A heresy of the crypto evangelion?
A heresy for sure, but not a problem at all. Let’s be honest and admit it: The crypto community found nothing unusual in the recent price-drops. I, myself even shorted the market, because crypto is still full of promises but lacking adoption.
Okay, so they are correlating and crypto is full of shit and scammy and basically the same, right?
Not so! Do you remember the times when we had to wait days for a transaction? Paying with wire transfer for something in China was insanely expensive? When merchants preferred cash over credit cards, because of high fees? When you had to hire a broker for investing?
Those times are gone and yes, not because of crypto solved these problems, but crypto definitely accelerated this transformation, urged the financial world to change rules or die. Now what if I say, this is only the beginning and these are only entry-level benefits of what really crypo promises?

Crypto promises us the “digital America”

Uh, I said it. Crypto is the new land and all the resourceful wants their own pieces of it. The reason behind why so many are thinking about Bitcoin as the digital gold is because the digital America’s gold rush is happening now. We all know deep in our consciousness that the world is heavily changing, the youth is changing, society is being digitalized even if brain-computer interfaces are not a thing yet..
Damn son you are weird and I stopped reading here.
The reason you feel weird about our descendants living online is because you know it will happen, but stay in the present now and I will tell you what crypto is doing to our traditional economy!

What is the “crypto dream”?

Many of the early adopters joined not because they wanted to make money, but because they think the current money system is unfair. Common citizens are paying the highest on almost everything and most of the time they don’t know about it. The financial sector’s practices are so hidden, almost like an occult knowledge. There are a few people who understand it and then there are everyone else, the vulnerable. This makes the first statement of the dream:
One of my biggest frustration as a teenager was I did not see real good opportunities in the world. I read about them, I saw them in historical movies, but in reality workplaces were boring and abusive, investments were only for the rich. Neither the booming housing market or fake forex trading seemed like a good fit for me. I had very little money, but a big passion to forge my fortune.
The wolves of Wall Street created our current system in the ideology of “I own what I could acquire” and backfired each other just like everyone did. They have done this, because there is no trust in the traditional world, but trust is heavily needed. But if things are transparent and open, we only need one more thing to wake up from this nightmare:
You read it right, a trustless environment provide uncheatable cooperation. There is no single entity that has authority over the system, and consensus is achieved without participants having to know or trust anything but the system itself.
I don’t eat your utopian bullshit! Your software is written by people I still need to trust.
People tend to be happier to direct trust towards organizations than systems. However, while organizations are made up of people who are easily corruptible, trustless systems can be governed entirely by computer code. All of the source code in crypto should be accessible to everyone. If it is not, then it is not a part of our ecosystem.

The technology behind crypto

Many being confused about the blockchain, thinking it is not a big deal. We had many software far older than Bitcoin, implementing the very same ideas. What Bitcoin had — which made the blockchain a very unique thing — is philosophy. It was intended to use a special way and confronted a very big thing, nobody thought it could be possible to confront.
The blockchain is a way to store information. A decentralized, fully transparent one, which is accessible for everyone 7/24. It never stops, It cannot be stopped and people make it doing different things.
The first use case its inventor made it doing is persisting transactions, money transfers. He told all of us it is just an experiment, which he didn’t tell is the capabilities of this technology. So fast people realized it is possible to do extraordinary things with it, like running a whole computer on the blockchain, making it behave like a virtual computer instance.
No one did things like this before: A global computer which cannot be stopped, which is capable to run all kinds of software on it.

What was the impact?

People go mad about it, especially greedy people who don’t know a bum about the technology but have money to pour in. At one point, the fundraising softwares running on the Ethereum global computer had more impact and volume than the whole VC industry in America. This was only the early rising of crypto, 2017 spring. Later that year, everyone hopped on the train who were brave or stupid enough.
Did crypto had a real economy at that point? Was it an industry? Real-world adoption? NOPE
It was a bitter funny hype train, challenging everyone inside or outside the community, but it showed us one thing: We have the gold.
Not so much people are capable to find and extract gold, to be honest: Most of us are just lurkers, fortune hunters and times could be rough when a mass hype destructs all the mines, but people had keep going, continuing the work.

How the crypto economy relates to the traditional economy now?

It is expanding much faster than any other economy in the world. Our frontiers in adoption are companies like Crypto.com paying hundred millions of dollars ($50 bonus for every new customer) to onboard millions of users, others like Coinbase paying $166 anyone to motivate in learning about cryptocurrencies. Handshake is airdropping hundreds of dollars (on current rates) to open-source developers and these are just a few examples of how generous and prosperous our thriving world is. In comparison: Revolut, a fintech company which is very similar to Crypto.com only paid 10 USD for new card holders and no one would ever pay you to educate yourself about financials. Developers? They historically get a fraction of a fraction of the pie in Silicon Valley. (Sorry Y Combinator, you are a delightful exception)
These companies I mentioned are very traditional ones and they are not innovating in software, but keeping our gates open to the new world. I don’t want to credit here any of the thousands of developer teams, all working on the “real deal”. I only leave here a link to the list of all variants of the Bitcoin source code alone. Understanding what blockchain companies are working on is a whole new profession now.
The idea of a crypto company is the DAO (Decentralized Autonomous Organization). Which covers trustless, often anonymous and fully transparent organizations with profit sharing and they are aimed to become better alternatives to traditional companies. Most of us in the community have different understanding, proposals and hopes about what a DAO should be, but common sense tell us it is the next big thing to emerge.

Wild West is Happening

We are building railway systems across the land, making connections and interoperations between blockchains. We are attracting a lot of immigrants day-to-day, because we have better paying workplaces, better interest rates and in overall a flourish economy. We are growing a strong identity to support our nation as the blockchain developers, economists, philosophers and investors. Our money is under our control as we own our future and all of us knows: We will soon show the world, what we are capable to achieve.
This is my view of the crypto world. This is the manifesto of “digital America”.
RAZ
contact me at zawiasa.hu
submitted by ZGenKibernetika to u/ZGenKibernetika [link] [comments]

Using Python and Pandas to explore trader sentiment data

FXCM’s Speculative Sentiment Index (SSI) focuses on buyers and sellers, comparing how many are active in the market and producing a ratio to indicate how traders are behaving in relation to a particular currency pair. A positive SSI ratio indicates more buyers are in the market than sellers, while a negative SSI ratio indicates that more sellers are in the market. FXCM’s sentiment data was designed around this index, providing 12 sentiment measurements per minute (click here for an overview of each measurement.)
The sample data is stored in a GNU compressed zip file on FXCM’s GitHub as https://sampledata.fxcorporate.com/sentiment/{instrument}.csv.gz. To download the file, we’ll use this URL, but change {instrument} to the instrument of our choice. For this example we’ll use EUUSD price.
import datetime import pandas as pd url = 'https://sampledata.fxcorporate.com/sentiment/EURUSD.csv.gz' data = pd.read_csv(url, compression='gzip', index_col='DateTime', parse_dates=True) """Convert data into GMT to match the price data we will download later""" import pytz data = data.tz_localize(pytz.timezone('US/Eastern')) data = data.tz_convert(pytz.timezone('GMT')) """Use pivot method to pivot Name rows into columns""" sentiment_pvt = data.tz_localize(None).pivot(columns='Name', values='Value') 
Now that we have downloaded sentiment data, it would be helpful to have the price data for the same instrument over the same period for analysis. Note the sentiment data is in 1-minute increments, so I will need to pull 1-minute EURUSD candles. We could pull this data into a DataFrame quickly and easily using fxcmpy, however the limit of the number of candles we can pull using fxcmpy is 10,000, which is fewer than the number of 1-minute candles in January 2018. Instead, we can download the candles in 1-week packages from FXCM’s GitHub and create a loop to compile them into a DataFrame. This sounds like a lot of work, but really it’s only a few lines of code. Similarly to the sentiment data, historical candle data is stored in GNU zip files which can be called by their URL.
url = 'https://candledata.fxcorporate.com/' periodicity='m1' ##periodicity, can be m1, H1, D1 url_suffix = '.csv.gz' symbol = 'EURUSD' start_dt = datetime.date(2018,1,2)##select start date end_dt = datetime.date(2018,2,1)##select end date start_wk = start_dt.isocalendar()[1] end_wk = end_dt.isocalendar()[1] year = str(start_dt.isocalendar()[0]) data=pd.DataFrame() for i in range(start_wk, end_wk+1): url_data = url + periodicity + '/' + symbol + '/' + year + '/' + str(i) + url_suffix print(url_data) tempdata = pd.read_csv(url_data, compression='gzip', index_col='DateTime', parse_dates=True) data=pd.concat([data, tempdata]) """Combine price and sentiment data""" frames = data['AskClose'], sentiment_pvt.tz_localize(None) combineddf = pd.concat(frames, axis=1, join_axes=[sentiment_pvt.tz_localize(None).index], ignore_index=False).dropna() combineddf 
At this point you can begin your exploratory data analysis. We started by viewing the descriptive statistics of the data, creating a heatmap of the correlation matrix, and plotting a histogram of the data to view its distribution. View this articleto see our sample code and the results.
submitted by JasonRogers to AlgoTradingFXCM [link] [comments]

ROFX.Group

ROFX.Group
https://preview.redd.it/6q30gbl8ikn11.jpg?width=1200&format=pjpg&auto=webp&s=5522d29a7b2159e73f5612f871f86e9ae43c38aa
Presuming that you have gone through all the basic requirements of what is needed to be a successful forex trader and found that you do not meet any, does that means it’s the end of your investment chances? Of course not because there is a service that lets even the novice and unrefined forex traders invest in the market without the slightest background in it. The ROFX.group for forex trading service will let you invest in this rewarding market with so much simplicity and flexibility that you do not need to do much other than wait for your profits. Beginners finally do not need to invest much mental work into choosing the right broker, installing the right software and trade. You finally do not need to begin the demo trading journey and learn all the details of money management, pair selection and correlation that beginner traders have to go through. This service just lets you invest a certain amount of money and have your profits remitted to you after a team of forex experts working with an AI system have done all the work. You know what that means? Your money grows in a stable and rewarding arrangement and still offers you a guarantee that your money will not shrink. The service offers profits of about 0.5% on average daily.
Artificial Intelligence in a different way
Artificial Intelligence aids with a lot of processes that would take a lot of time to do manually. Lately, these robots can even figure out some patterns that a human eye may have ignored or was just not aware of its existence and meaning. The ROFX.group robot is run by proven forex traders and other scientists who keep on updating its code with the newest trade-sensitive information to ensure that all clients only get the best of the market. You can go on with your business having the confidence that the team will work together to pick the optimal trades and leave out the potential bad eggs that have a high chance of ending up as losing trades.
AI is supervised by an experienced group of in-house forex traders
The AI system has been in operation for almost 10 years and it simply builds on the store of experience that the current team has had through the years. Having an operation style that combines both human input and the AI input irons out all the possibilities of having a computerized system that runs wild and places trades that are mathematically justified but do not fit the current market fundamentals and news.
The RoFx platform is simple to use and does not require setup
One thing you will be glad about after reading this ROFX.group review is that you are closer to a “hands free” investment channel that also has a sleek and simple platform. You can check up your account balance, see your profit history and contact the team of experts only with a few clicks. The platform does not need any downloading and as such, there is no difficult installation process involved. It may sound obvious but a lot of people do not find it easy to install and operate the platforms involved in traditional forex trading. Older systems had icons that needed a person to hoover the mouse over them for them to understand what they mean. The RoFx platform just needs someone to log onto the platform and click anything they want done quick.
No hidden costs and there is coverage
Believe it or not, traditional forex trading still has some costs involved whether you are making profits or not. People need to consider spreads and commissions meant for brokers. The kind of broker chosen also affects how much you pay in spreads and other hidden costs. Requotes have also been a sneaky method through which some brokers ensure that you do not profit out of quick scalp trades. With this service, investors do not get charged for depositing or withdrawing over the contract period and get very good prices for their bitcoin deposits.
You get the very best of protection for money you have deposited and enjoy loss coverage in case you are wondering what happens when the system makes a loss on that day. The service has a vast store of funds to cover for that negative profit for that day in case it occurs at all. Most of all, the money wallet in the service allows for easy transaction making with different deposit options such as bitcoin, bank transfer, VISA and Mastercard. You can make transactions from anywhere using any internet ready device.
submitted by ROFX_user to Daytrading [link] [comments]

I want to talk about Bitcoin scams

EDIT: I edited the name out of a screencap. sorry about that.
pardon the wall of text but this is super important to me.
i am a hardcore bitcoin evangelist and my entire facebook friend list probabaly associates me with bitcoin because i spend a great deal of time educating people and discussing it on social media. my background is computer network engineering and web developing; i've studied bitcoin for a few years now.
first i wanna talk about USI Tech.
not long ago i was asked to invest some bitcoin via a company called USI Tech. at the time, USI Tech's only relation to bitcoin was that they sold cryptic "bitcoin packages" that would return 140% over 140 days. that means if i gave them 1 BTC today, they would give me 1% of a bitcoin for 140 days, meaning that after 100 days, my initial investment would be recovered, and then all i get to do is wait for those 40 days to see my profit.
when i was first recruited, it was before they rebranded themselves. this was just a few weeks ago. prior to this rebranding, there was no indication from the company regarding exactly how they were able to provide that kind of return on investment. at the time their only product other than these "bitcoin packages" was a license that provided access to a very special very secretive robot that harnessed artificial intelligence to yield apparently handsome returns via speculative arbitrage in the foreign exchange market. there are zero trades attributed to this "robot" and in fact there is zero evidence of a robot at all. they do have software for their customers that apparently track gains however there is zero correlation between these numbers and their apparent source.
since their rebranding, they are now marketing these "bitcoin packages" as having generated income via cloud mining. keep in mind that USI Tech does not sell hashrate, nor even techinically access to remote hardware; USI Tech sells "bitcoin packages" however how these packages specifically relate to hashrates accessed on remote hardware, or cloud mining, is not at all explained. in fact, here on their website they say that details will be released and then reference a date that has already passed..
to be blunt, cloud mining is a meme. mining cryptocurrency for a profit is generally difficult even for the big boys in China. that bitcoin could be worth more in the future than it is now is the reason why miners mine; the energy spent mining bitcoin costs more than the value of those mined bitcoins.
how does USI Tech not only mine so successfully that they themselves can be profitable, but so that customers who purchase this mining remotely can be successful to the tune of 140% over 140 days?
also they are in pre-sale for their own ICO,
also they have zero registration documents filed with the SEC,
also the names that used to be on their masthead, Ralf Gold and Joao Severino, were involved in past scams,
also their business is registered in Dubai, just like almost every single forex ponzi,
also like i said there is zero proof that they trade anything at all, anywhere.
i really thought i knew my shit. is there a more experienced bitcoin user that can point to any situation where that sort of profitibility can be achieved by cloud mining?
if the question seems rhetorical for the high bitcoin minds on this sub, then maybe i've done my duty by exposing USI Tech's dubious claims and raising suspicion which brings me to my next point:
secondly i wanna talk about the tactics used by this company to fool people.
primarily i should say that USI Tech operates a multilevel marketing structure that rewards recruitment through commission. it is not a coincidense that ponzi schemes use MLM structures to grow; ponzis require a continuous flow of new investment in order to work. to be blunt, MLM is a predatory business approach that exploits people's hope and greed. all MLM use the same tactic of targeting people's desperation to earn passive income.
USI Tech takes advantage of a population of people who are desperate to invest in a technology they do not comprehend. this is how they can get away with selling something that there is no evidence of. people now have a very dire desire to be involved in bitcoin because they have seen the news. people that do not know enough about investments, let alone cryptography, are aching to enter the space before all the potential is claimed.
there is much fertile potential to scam people who don't know that hyperbole like "smart contracts made off-chain that return high yield arbitration via intelligent algorithms backed by authenticated crypto-asset bonds.." is all bullshit. in most cases, even if they could, there is no code to review, no whitepaper to digest, and in the case of USI Tech, not even satisfacory rhetoric to substantiate anything being sold by these scammers.
earlier today, i went into a facebook group called USI TECH BITCOIN TEAM SUCCESS, and i asked a question. i said "i'm interested in joining USI Tech, and as a programmer and bitcoin nerd, i want to know the details of their mining operation." immediately the reaction was two-fold. promptly some were chiming in with agreeable sentiments like 'i've also wondered' and 'yes there is a lack of transparency', and others were already indignant with stuff like 'they said they are working on transparency give them a break' and 'troll detected, usi tech is not a scam because look i made money'.
okay fair enough the conversation was started and i was pretty quickly banned from the group. i had a dozen or so people in my ear at this point asking me what happened, people that have invested real money in this company. i spent hours discussing this with some of them. i had a conversation with the group's admin, here it is. he basically says that he doesn't want to upset people that have found a way to make money, and that my questions should be directed somewhere else.
i've sent exhaustive emails pondering specifics to USI Tech to no avail.
in conclusion, bitcoin has provided rich new opportunities for scamming people.
let me be clear: yes money can be made in a ponzi scheme. the operative to earning money in a ponzi is to know when to discontinue reinvestment. by all means, partake in the ponzi even, so long as you know what you are contribtuing to. the number one argument that people will make in favor of the ponzi they're in is
"but i made money".
it is our duty as crypto-enthusiasts to spread responsible education regarding bitcoin. i say to people "if you are interested in bitcoin, invest in bitcoin, because that is where the actual innovation is".
TL;DR: fuck bitcoins ponzis like USI Tech, stay alert, stay safe.
submitted by beartowitness to Bitcoin [link] [comments]

Looking for programmers to start a team

First, who I am. I work in the financial industry as a level 2 PC support. I have a computer science and mathematics degree and have worked as a programmer for over 3 years, and PC support for over 6. I’ve been working for the last 3 months on “breaking” a platform that we used in the past to auto-trade forex so that it could trade cryptocurrencies. I currently have a system running that has been making roughly .5-1% per day since mid-January but are looking to accelerate and improve this. I also have a system that is projected to make much more but implementing a way to execute those trades on the market will require a bit of work.
The Plan. I’d like to build a team of skilled individuals but divide them into teams that won’t share work with the exception of meetings to talk about progress and if one team seriously needs help understanding something another team is doing. This will slowly go away as everyone gets vetted and works together more frequently. Each of these teams will get their part of the project that I’ve developed over the last 3 months so that they can understand and improve upon it. The only time they will have access to another part of it is when they’re working with a member of that team either through discord or some RDC (Discord, VNC, RDP, TeamViewer, Skype etc.). The reasoning for this is so that one individual can’t run off with all of our work and build their own team to do this with, as has happened to me prior.
At some point I’d like to have everyone I add to the team get well-vetted enough to do away with the segregation and have one team working together, but until I get to know everyone I bring in I need to do this for all our benefit. As of right now I have assembled a team of 5 and look to add a few more.
Stage 2 of the plan -once we have proven ourselves through a strong portfolio- is to eventually build this into a fully-fledged trading fund. I already have someone who’s passed the series 7 and series 65 exams willing to join the team.
Team Structure. Team 1 will need to be strong in coding both python and C#, strong at making things that are not intended to work together run like a clock and will be the core to our back end. All data that comes from Brokers, Google Trends, Google Analytics, Twitter, etc. will come from the back end that is built by this team. As of right now it’s run in python because 2 of the API’s I use don’t have open-API’s but have libraries already built for python. Eventually I’d like to “break” our platform even further and integrate the entire backend into it using C# so everything becomes more streamlined. (2 open spots)
Team 2 will be somewhat split into two subteams, both of which will be working solely on the platform itself. The first subteam will need to be strong and experienced traders, understanding both fundamental and technical trading. A base understanding of programming to better articulate your thoughts to your teammates is also a huge asset. (1 open spot)
The second subteam will be made up of programmers who are able to code C# and are able to understand what the non-programming oriented first half of this team are trying to tell a computer to do. This will consist of writing and testing certain correlations that they may view impactful and creating new indicators as well as re-writing parts of the platform in our favor. (1 open spot)
Team 3 will work on the machine learning. It’s important they have a strong understanding of C# and data science theory. I’d like to integrate this directly into the platform for the sake of consistency and speed. Python is also a useful language to know but is not required. They will work with team 2 short term. And will have a more self-contained project long term. (1 open spot)
What we have:
submitted by OneFinding to algotrading [link] [comments]

ROFX - Review

ROFX - Review
https://preview.redd.it/gq5kmrjkfdn11.jpg?width=1200&format=pjpg&auto=webp&s=19978f0a54d31140735d7ee27e906381d98d2c6a
Presuming that you have gone through all the basic requirements of what is needed to be a successful forex trader and found that you do not meet any, does that means it’s the end of your investment chances? Of course not because there is a service that lets even the novice and unrefined forex traders invest in the market without the slightest background in it. The ROFX.group for forex trading service will let you invest in this rewarding market with so much simplicity and flexibility that you do not need to do much other than wait for your profits. Beginners finally do not need to invest much mental work into choosing the right broker, installing the right software and trade. You finally do not need to begin the demo trading journey and learn all the details of money management, pair selection and correlation that beginner traders have to go through. This service just lets you invest a certain amount of money and have your profits remitted to you after a team of forex experts working with an AI system have done all the work. You know what that means? Your money grows in a stable and rewarding arrangement and still offers you a guarantee that your money will not shrink. The service offers profits of about 0.5% on average daily.
Artificial Intelligence in a different way
Artificial Intelligence aids with a lot of processes that would take a lot of time to do manually. Lately, these robots can even figure out some patterns that a human eye may have ignored or was just not aware of its existence and meaning. The ROFX.group robot is run by proven forex traders and other scientists who keep on updating its code with the newest trade-sensitive information to ensure that all clients only get the best of the market. You can go on with your business having the confidence that the team will work together to pick the optimal trades and leave out the potential bad eggs that have a high chance of ending up as losing trades.
AI is supervised by an experienced group of in-house forex traders
The AI system has been in operation for almost 10 years and it simply builds on the store of experience that the current team has had through the years. Having an operation style that combines both human input and the AI input irons out all the possibilities of having a computerized system that runs wild and places trades that are mathematically justified but do not fit the current market fundamentals and news.
The RoFx platform is simple to use and does not require setup
One thing you will be glad about after reading this ROFX.group review is that you are closer to a “hands free” investment channel that also has a sleek and simple platform. You can check up your account balance, see your profit history and contact the team of experts only with a few clicks. The platform does not need any downloading and as such, there is no difficult installation process involved. It may sound obvious but a lot of people do not find it easy to install and operate the platforms involved in traditional forex trading. Older systems had icons that needed a person to hoover the mouse over them for them to understand what they mean. The RoFx platform just needs someone to log onto the platform and click anything they want done quick.
No hidden costs and there is coverage
Believe it or not, traditional forex trading still has some costs involved whether you are making profits or not. People need to consider spreads and commissions meant for brokers. The kind of broker chosen also affects how much you pay in spreads and other hidden costs. Requotes have also been a sneaky method through which some brokers ensure that you do not profit out of quick scalp trades. With this service, investors do not get charged for depositing or withdrawing over the contract period and get very good prices for their bitcoin deposits.
You get the very best of protection for money you have deposited and enjoy loss coverage in case you are wondering what happens when the system makes a loss on that day. The service has a vast store of funds to cover for that negative profit for that day in case it occurs at all. Most of all, the money wallet in the service allows for easy transaction making with different deposit options such as bitcoin, bank transfer, VISA and Mastercard. You can make transactions from anywhere using any internet ready device.
submitted by ROFX_user to u/ROFX_user [link] [comments]

Ivybot - Not Your Usual Forex Trading Robot!

This article is to help the buyers to get know how about the potential of this product without wasting their time on searching for Mega droid reviews on internet. Lot of time has been invested by us for asking about it from its users whether it is useful or useless to spend money in Mega droid. In the following we have just tried to solve his simple question that whether the Forex MegaDroid actually works or it is only one more manic.

This wonderful invention was created by Albert Perrier and John Grace the two gurus of forex trading. Their work experience in the trading world is about four decades. The ideology behind its making was to invent a machine which really predicts the market condition in the coming 2 to 4 hours. Due to this In this technique brokers will definitely be able to judge the correct time for investing in the international market. They had put their 40 years of forex trading experience for developing this profitable product.

The Forex MegaDroid is based on artificial intelligence system that has the ability to forecast the current and past market trends of trading industry in contrast the rest of the robots in the market place only handle the previous market information to guess the right time of trading. Though, its makers declare that this is the only robot which is not only dealing with the past as well as current market situation. The above mentioned technology is the central part of its artificial intelligence system called as Correlated Time and Price Analysis (RCTPA). Due to this factor the Forex MegaDroid gained great publicity because it is the first mechanism which is utilizing the RCTPA technology.

The other reason behind its popularity is that, its makers claims that this robot predicts the market trends upto 95% accurately even when market conditions are fluctuating unexpectedly. To sum up, some traders had profitable achievement through Mega droid so they admitted that it really works while there are also some other traders who says this is a scam.

https://criptomonde.com/the-ripple-code-review/
https://criptomonde.com/high-performance-selling-review/
https://criptomonde.com/the-credit-people-credit-repair-review/
https://criptomonde.com/profit-genesis-2-0-review/
submitted by reginawilliam to u/reginawilliam [link] [comments]

[uncensored-r/Bitcoin] I want to talk about Bitcoin scams

The following post by beartowitness is being replicated because the post has been silently greylisted(for 2.5 hours).
(It was approved by the mods at: 2017-11-04T01:26:17.000Z)
The original post can be found(in censored form) at this link:
np.reddit.com/ Bitcoin/comments/7amu9s
The original post's content was as follows:
EDIT: I edited the name out of a screencap. sorry about that.
pardon the wall of text but this is super important to me.
i am a hardcore bitcoin evangelist and my entire facebook friend list probabaly associates me with bitcoin because i spend a great deal of time educating people and discussing it on social media. my background is computer network engineering and web developing; i've studied bitcoin for a few years now.
first i wanna talk about USI Tech.
not long ago i was asked to invest some bitcoin via a company called USI Tech. at the time, USI Tech's only relation to bitcoin was that they sold cryptic "bitcoin packages" that would return 140% over 140 days. that means if i gave them 1 BTC today, they would give me 1% of a bitcoin for 140 days, meaning that after 100 days, my initial investment would be recovered, and then all i get to do is wait for those 40 days to see my profit.
when i was first recruited, it was before they rebranded themselves. this was just a few weeks ago. prior to this rebranding, there was no indication from the company regarding exactly how they were able to provide that kind of return on investment. at the time their only product other than these "bitcoin packages" was a license that provided access to a very special very secretive robot that harnessed artificial intelligence to yield apparently handsome returns via speculative arbitrage in the foreign exchange market. there are zero trades attributed to this "robot" and in fact there is zero evidence of a robot at all. they do have software for their customers that apparently track gains however there is zero correlation between these numbers and their apparent source.
since their rebranding, they are now marketing these "bitcoin packages" as having generated income via cloud mining. keep in mind that USI Tech does not sell hashrate, nor even techinically access to remote hardware; USI Tech sells "bitcoin packages" however how these packages specifically relate to hashrates accessed on remote hardware, or cloud mining, is not at all explained. in fact, here on their website they say that details will be released and then reference a date that has already passed..
to be blunt, cloud mining is a meme. mining cryptocurrency for a profit is generally difficult even for the big boys in China. that bitcoin could be worth more in the future than it is now is the reason why miners mine; the energy spent mining bitcoin costs more than the value of those mined bitcoins.
how does USI Tech not only mine so successfully that they themselves can be profitable, but so that customers who purchase this mining remotely can be successful to the tune of 140% over 140 days?
also they are in pre-sale for their own ICO,
also they have zero registration documents filed with the SEC,
also the names that used to be on their masthead, Ralf Gold and Joao Severino, were involved in past scams,
also their business is registered in Dubai, just like almost every single forex ponzi,
also like i said there is zero proof that they trade anything at all, anywhere.
i really thought i knew my shit. is there a more experienced bitcoin user that can point to any situation where that sort of profitibility can be achieved by cloud mining?
if the question seems rhetorical for the high bitcoin minds on this sub, then maybe i've done my duty by exposing USI Tech's dubious claims and raising suspicion which brings me to my next point:
secondly i wanna talk about the tactics used by this company to fool people.
primarily i should say that USI Tech operates a multilevel marketing structure that rewards recruitment through commission. it is not a coincidense that ponzi schemes use MLM structures to grow; ponzis require a continuous flow of new investment in order to work. to be blunt, MLM is a predatory business approach that exploits people's hope and greed. all MLM use the same tactic of targeting people's desperation to earn passive income.
USI Tech takes advantage of a population of people who are desperate to invest in a technology they do not comprehend. this is how they can get away with selling something that there is no evidence of. people now have a very dire desire to be involved in bitcoin because they have seen the news. people that do not know enough about investments, let alone cryptography, are aching to enter the space before all the potential is claimed.
there is much fertile potential to scam people who don't know that hyperbole like "smart contracts made off-chain that return high yield arbitration via intelligent algorithms backed by authenticated crypto-asset bonds.." is all bullshit. in most cases, even if they could, there is no code to review, no whitepaper to digest, and in the case of USI Tech, not even satisfacory rhetoric to substantiate anything being sold by these scammers.
earlier today, i went into a facebook group called USI TECH BITCOIN TEAM SUCCESS, and i asked a question. i said "i'm interested in joining USI Tech, and as a programmer and bitcoin nerd, i want to know the details of their mining operation." immediately the reaction was two-fold. promptly some were chiming in with agreeable sentiments like 'i've also wondered' and 'yes there is a lack of transparency', and others were already indignant with stuff like 'they said they are working on transparency give them a break' and 'troll detected, usi tech is not a scam because look i made money'.
okay fair enough the conversation was started and i was pretty quickly banned from the group. i had a dozen or so people in my ear at this point asking me what happened, people that have invested real money in this company. i spent hours discussing this with some of them. i had a conversation with the group's admin, here it is. he basically says that he doesn't want to upset people that have found a way to make money, and that my questions should be directed somewhere else.
i've sent exhaustive emails pondering specifics to USI Tech to no avail.
in conclusion, bitcoin has provided rich new opportunities for scamming people.
let me be clear: yes money can be made in a ponzi scheme. the operative to earning money in a ponzi is to know when to discontinue reinvestment. by all means, partake in the ponzi even, so long as you know what you are contribtuing to. the number one argument that people will make in favor of the ponzi they're in is
"but i made money".
it is our duty as crypto-enthusiasts to spread responsible education regarding bitcoin. i say to people "if you are interested in bitcoin, invest in bitcoin, because that is where the actual innovation is".
TL;DR: fuck bitcoins ponzis like USI Tech, stay alert, stay safe.
submitted by censorship_notifier to noncensored_bitcoin [link] [comments]

Subreddit Stats: cs7646_fall2017 top posts from 2017-08-23 to 2017-12-10 22:43 PDT

Period: 108.98 days
Submissions Comments
Total 999 10425
Rate (per day) 9.17 95.73
Unique Redditors 361 695
Combined Score 4162 17424

Top Submitters' Top Submissions

  1. 296 points, 24 submissions: tuckerbalch
    1. Project 2 Megathread (optimize_something) (33 points, 475 comments)
    2. project 3 megathread (assess_learners) (27 points, 1130 comments)
    3. For online students: Participation check #2 (23 points, 47 comments)
    4. ML / Data Scientist internship and full time job opportunities (20 points, 36 comments)
    5. Advance information on Project 3 (19 points, 22 comments)
    6. participation check #3 (19 points, 29 comments)
    7. manual_strategy project megathread (17 points, 825 comments)
    8. project 4 megathread (defeat_learners) (15 points, 209 comments)
    9. project 5 megathread (marketsim) (15 points, 484 comments)
    10. QLearning Robot project megathread (12 points, 691 comments)
  2. 278 points, 17 submissions: davebyrd
    1. A little more on Pandas indexing/slicing ([] vs ix vs iloc vs loc) and numpy shapes (37 points, 10 comments)
    2. Project 1 Megathread (assess_portfolio) (34 points, 466 comments)
    3. marketsim grades are up (25 points, 28 comments)
    4. Midterm stats (24 points, 32 comments)
    5. Welcome to CS 7646 MLT! (23 points, 132 comments)
    6. How to interact with TAs, discuss grades, performance, request exceptions... (18 points, 31 comments)
    7. assess_portfolio grades have been released (18 points, 34 comments)
    8. Midterm grades posted to T-Square (15 points, 30 comments)
    9. Removed posts (15 points, 2 comments)
    10. assess_portfolio IMPORTANT README: about sample frequency (13 points, 26 comments)
  3. 118 points, 17 submissions: yokh_cs7646
    1. Exam 2 Information (39 points, 40 comments)
    2. Reformat Assignment Pages? (14 points, 2 comments)
    3. What did the real-life Michael Burry have to say? (13 points, 2 comments)
    4. PSA: Read the Rubric carefully and ahead-of-time (8 points, 15 comments)
    5. How do I know that I'm correct and not just lucky? (7 points, 31 comments)
    6. ML Papers and News (7 points, 5 comments)
    7. What are "question pools"? (6 points, 4 comments)
    8. Explanation of "Regression" (5 points, 5 comments)
    9. GT Github taking FOREVER to push to..? (4 points, 14 comments)
    10. Dead links on the course wiki (3 points, 2 comments)
  4. 67 points, 13 submissions: harshsikka123
    1. To all those struggling, some words of courage! (20 points, 18 comments)
    2. Just got locked out of my apartment, am submitting from a stairwell (19 points, 12 comments)
    3. Thoroughly enjoying the lectures, some of the best I've seen! (13 points, 13 comments)
    4. Just for reference, how long did Assignment 1 take you all to implement? (3 points, 31 comments)
    5. Grade_Learners Taking about 7 seconds on Buffet vs 5 on Local, is this acceptable if all tests are passing? (2 points, 2 comments)
    6. Is anyone running into the Runtime Error, Invalid DISPLAY variable when trying to save the figures as pdfs to the Buffet servers? (2 points, 9 comments)
    7. Still not seeing an ML4T onboarding test on ProctorTrack (2 points, 10 comments)
    8. Any news on when Optimize_Something grades will be released? (1 point, 1 comment)
    9. Baglearner RMSE and leaf size? (1 point, 2 comments)
    10. My results are oh so slightly off, any thoughts? (1 point, 11 comments)
  5. 63 points, 10 submissions: htrajan
    1. Sample test case: missing data (22 points, 36 comments)
    2. Optimize_something test cases (13 points, 22 comments)
    3. Met Burt Malkiel today (6 points, 1 comment)
    4. Heads up: Dataframe.std != np.std (5 points, 5 comments)
    5. optimize_something: graph (5 points, 29 comments)
    6. Schedule still reflecting shortened summer timeframe? (4 points, 3 comments)
    7. Quick clarification about InsaneLearner (3 points, 8 comments)
    8. Test cases using rfr? (3 points, 5 comments)
    9. Input format of rfr (2 points, 1 comment)
    10. [Shameless recruiting post] Wealthfront is hiring! (0 points, 9 comments)
  6. 62 points, 7 submissions: swamijay
    1. defeat_learner test case (34 points, 38 comments)
    2. Project 3 test cases (15 points, 27 comments)
    3. Defeat_Learner - related questions (6 points, 9 comments)
    4. Options risk/reward (2 points, 0 comments)
    5. manual strategy - you must remain in the position for 21 trading days. (2 points, 9 comments)
    6. standardizing values (2 points, 0 comments)
    7. technical indicators - period for moving averages, or anything that looks past n days (1 point, 3 comments)
  7. 61 points, 9 submissions: gatech-raleighite
    1. Protip: Better reddit search (22 points, 9 comments)
    2. Helpful numpy array cheat sheet (16 points, 10 comments)
    3. In your experience Professor, Mr. Byrd, which strategy is "best" for trading ? (12 points, 10 comments)
    4. Industrial strength or mature versions of the assignments ? (4 points, 2 comments)
    5. What is the correct (faster) way of doing this bit of pandas code (updating multiple slice values) (2 points, 10 comments)
    6. What is the correct (pythonesque?) way to select 60% of rows ? (2 points, 11 comments)
    7. How to get adjusted close price for funds not publicly traded (TSP) ? (1 point, 2 comments)
    8. Is there a way to only test one or 2 of the learners using grade_learners.py ? (1 point, 10 comments)
    9. OMS CS Digital Career Seminar Series - Scott Leitstein recording available online? (1 point, 4 comments)
  8. 60 points, 2 submissions: reyallan
    1. [Project Questions] Unit Tests for assess_portfolio assignment (58 points, 52 comments)
    2. Financial data, technical indicators and live trading (2 points, 8 comments)
  9. 59 points, 12 submissions: dyllll
    1. Please upvote helpful posts and other advice. (26 points, 1 comment)
    2. Books to further study in trading with machine learning? (14 points, 9 comments)
    3. Is Q-Learning the best reinforcement learning method for stock trading? (4 points, 4 comments)
    4. Any way to download the lessons? (3 points, 4 comments)
    5. Can a TA please contact me? (2 points, 7 comments)
    6. Is the vectorization code from the youtube video available to us? (2 points, 2 comments)
    7. Position of webcam (2 points, 15 comments)
    8. Question about assignment one (2 points, 5 comments)
    9. Are udacity quizzes recorded? (1 point, 2 comments)
    10. Does normalization of indicators matter in a Q-Learner? (1 point, 7 comments)
  10. 56 points, 2 submissions: jan-laszlo
    1. Proper git workflow (43 points, 19 comments)
    2. Adding you SSH key for password-less access to remote hosts (13 points, 7 comments)
  11. 53 points, 1 submission: agifft3_omscs
    1. [Project Questions] Unit Tests for optimize_something assignment (53 points, 94 comments)
  12. 50 points, 16 submissions: BNielson
    1. Regression Trees (7 points, 9 comments)
    2. Two Interpretations of RFR are leading to two different possible Sharpe Ratios -- Need Instructor clarification ASAP (5 points, 3 comments)
    3. PYTHONPATH=../:. python grade_analysis.py (4 points, 7 comments)
    4. Running on Windows and PyCharm (4 points, 4 comments)
    5. Studying for the midterm: python questions (4 points, 0 comments)
    6. Assess Learners Grader (3 points, 2 comments)
    7. Manual Strategy Grade (3 points, 2 comments)
    8. Rewards in Q Learning (3 points, 3 comments)
    9. SSH/Putty on Windows (3 points, 4 comments)
    10. Slight contradiction on ProctorTrack Exam (3 points, 4 comments)
  13. 49 points, 7 submissions: j0shj0nes
    1. QLearning Robot - Finalized and Released Soon? (18 points, 4 comments)
    2. Flash Boys, HFT, frontrunning... (10 points, 3 comments)
    3. Deprecations / errata (7 points, 5 comments)
    4. Udacity lectures via GT account, versus personal account (6 points, 2 comments)
    5. Python: console-driven development (5 points, 5 comments)
    6. Buffet pandas / numpy versions (2 points, 2 comments)
    7. Quant research on earnings calls (1 point, 0 comments)
  14. 45 points, 11 submissions: Zapurza
    1. Suggestion for Strategy learner mega thread. (14 points, 1 comment)
    2. Which lectures to watch for upcoming project q learning robot? (7 points, 5 comments)
    3. In schedule file, there is no link against 'voting ensemble strategy'? Scheduled for Nov 13-20 week (6 points, 3 comments)
    4. How to add questions to the question bank? I can see there is 2% credit for that. (4 points, 5 comments)
    5. Scratch paper use (3 points, 6 comments)
    6. The big short movie link on you tube says the video is not available in your country. (3 points, 9 comments)
    7. Distance between training data date and future forecast date (2 points, 2 comments)
    8. News affecting stock market and machine learning algorithms (2 points, 4 comments)
    9. pandas import in pydev (2 points, 0 comments)
    10. Assess learner server error (1 point, 2 comments)
  15. 43 points, 23 submissions: chvbs2000
    1. Is the Strategy Learner finalized? (10 points, 3 comments)
    2. Test extra 15 test cases for marketsim (3 points, 12 comments)
    3. Confusion between the term computing "back-in time" and "going forward" (2 points, 1 comment)
    4. How to define "each transaction"? (2 points, 4 comments)
    5. How to filling the assignment into Jupyter Notebook? (2 points, 4 comments)
    6. IOError: File ../data/SPY.csv does not exist (2 points, 4 comments)
    7. Issue in Access to machines at Georgia Tech via MacOS terminal (2 points, 5 comments)
    8. Reading data from Jupyter Notebook (2 points, 3 comments)
    9. benchmark vs manual strategy vs best possible strategy (2 points, 2 comments)
    10. global name 'pd' is not defined (2 points, 4 comments)
  16. 43 points, 15 submissions: shuang379
    1. How to test my code on buffet machine? (10 points, 15 comments)
    2. Can we get the ppt for "Decision Trees"? (8 points, 2 comments)
    3. python question pool question (5 points, 6 comments)
    4. set up problems (3 points, 4 comments)
    5. Do I need another camera for scanning? (2 points, 9 comments)
    6. Is chapter 9 covered by the midterm? (2 points, 2 comments)
    7. Why grade_analysis.py could run even if I rm analysis.py? (2 points, 5 comments)
    8. python question pool No.48 (2 points, 6 comments)
    9. where could we find old versions of the rest projects? (2 points, 2 comments)
    10. where to put ml4t-libraries to install those libraries? (2 points, 1 comment)
  17. 42 points, 14 submissions: larrva
    1. is there a mistake in How-to-learn-a-decision-tree.pdf (7 points, 7 comments)
    2. maximum recursion depth problem (6 points, 10 comments)
    3. [Urgent]Unable to use proctortrack in China (4 points, 21 comments)
    4. manual_strategynumber of indicators to use (3 points, 10 comments)
    5. Assignment 2: Got 63 points. (3 points, 3 comments)
    6. Software installation workshop (3 points, 7 comments)
    7. question regarding functools32 version (3 points, 3 comments)
    8. workshop on Aug 31 (3 points, 8 comments)
    9. Mount remote server to local machine (2 points, 2 comments)
    10. any suggestion on objective function (2 points, 3 comments)
  18. 41 points, 8 submissions: Ran__Ran
    1. Any resource will be available for final exam? (19 points, 6 comments)
    2. Need clarification on size of X, Y in defeat_learners (7 points, 10 comments)
    3. Get the same date format as in example chart (4 points, 3 comments)
    4. Cannot log in GitHub Desktop using GT account? (3 points, 3 comments)
    5. Do we have notes or ppt for Time Series Data? (3 points, 5 comments)
    6. Can we know the commission & market impact for short example? (2 points, 7 comments)
    7. Course schedule export issue (2 points, 15 comments)
    8. Buying/seeking beta v.s. buying/seeking alpha (1 point, 6 comments)
  19. 38 points, 4 submissions: ProudRamblinWreck
    1. Exam 2 Study topics (21 points, 5 comments)
    2. Reddit participation as part of grade? (13 points, 32 comments)
    3. Will birds chirping in the background flag me on Proctortrack? (3 points, 5 comments)
    4. Midterm Study Guide question pools (1 point, 2 comments)
  20. 37 points, 6 submissions: gatechben
    1. Submission page for strategy learner? (14 points, 10 comments)
    2. PSA: The grading script for strategy_learner changed on the 26th (10 points, 9 comments)
    3. Where is util.py supposed to be located? (8 points, 8 comments)
    4. PSA:. The default dates in the assignment 1 template are not the same as the examples on the assignment page. (2 points, 1 comment)
    5. Schedule: Discussion of upcoming trading projects? (2 points, 3 comments)
    6. [defeat_learners] More than one column for X? (1 point, 1 comment)
  21. 37 points, 3 submissions: jgeiger
    1. Please send/announce when changes are made to the project code (23 points, 7 comments)
    2. The Big Short on Netflix for OMSCS students (week of 10/16) (11 points, 6 comments)
    3. Typo(?) for Assess_portfolio wiki page (3 points, 2 comments)
  22. 35 points, 10 submissions: ltian35
    1. selecting row using .ix (8 points, 9 comments)
    2. Will the following 2 topics be included in the final exam(online student)? (7 points, 4 comments)
    3. udacity quiz (7 points, 4 comments)
    4. pdf of lecture (3 points, 4 comments)
    5. print friendly version of the course schedule (3 points, 9 comments)
    6. about learner regression vs classificaiton (2 points, 2 comments)
    7. is there a simple way to verify the correctness of our decision tree (2 points, 4 comments)
    8. about Building an ML-based forex strategy (1 point, 2 comments)
    9. about technical analysis (1 point, 6 comments)
    10. final exam online time period (1 point, 2 comments)
  23. 33 points, 2 submissions: bhrolenok
    1. Assess learners template and grading script is now available in the public repository (24 points, 0 comments)
    2. Tutorial for software setup on Windows (9 points, 35 comments)
  24. 31 points, 4 submissions: johannes_92
    1. Deadline extension? (26 points, 40 comments)
    2. Pandas date indexing issues (2 points, 5 comments)
    3. Why do we subtract 1 from SMA calculation? (2 points, 3 comments)
    4. Unexpected number of calls to query, sum=20 (should be 20), max=20 (should be 1), min=20 (should be 1) -bash: syntax error near unexpected token `(' (1 point, 3 comments)
  25. 30 points, 5 submissions: log_base_pi
    1. The Massive Hedge Fund Betting on AI [Article] (9 points, 1 comment)
    2. Useful Python tips and tricks (8 points, 10 comments)
    3. Video of overview of remaining projects with Tucker Balch (7 points, 1 comment)
    4. Will any material from the lecture by Goldman Sachs be covered on the exam? (5 points, 1 comment)
    5. What will the 2nd half of the course be like? (1 point, 8 comments)
  26. 30 points, 4 submissions: acschwabe
    1. Assignment and Exam Calendar (ICS File) (17 points, 6 comments)
    2. Please OMG give us any options for extra credit (8 points, 12 comments)
    3. Strategy learner question (3 points, 1 comment)
    4. Proctortrack: Do we need to schedule our test time? (2 points, 10 comments)
  27. 29 points, 9 submissions: _ant0n_
    1. Next assignment? (9 points, 6 comments)
    2. Proctortrack Onboarding test? (6 points, 11 comments)
    3. Manual strategy: Allowable positions (3 points, 7 comments)
    4. Anyone watched Black Scholes documentary? (2 points, 16 comments)
    5. Buffet machines hardware (2 points, 6 comments)
    6. Defeat learners: clarification (2 points, 4 comments)
    7. Is 'optimize_something' on the way to class GitHub repo? (2 points, 6 comments)
    8. assess_portfolio(... gen_plot=True) (2 points, 8 comments)
    9. remote job != remote + international? (1 point, 15 comments)
  28. 26 points, 10 submissions: umersaalis
    1. comments.txt (7 points, 6 comments)
    2. Assignment 2: report.pdf (6 points, 30 comments)
    3. Assignment 2: report.pdf sharing & plagiarism (3 points, 12 comments)
    4. Max Recursion Limit (3 points, 10 comments)
    5. Parametric vs Non-Parametric Model (3 points, 13 comments)
    6. Bag Learner Training (1 point, 2 comments)
    7. Decision Tree Issue: (1 point, 2 comments)
    8. Error in Running DTLearner and RTLearner (1 point, 12 comments)
    9. My Results for the four learners. Please check if you guys are getting values somewhat near to these. Exact match may not be there due to randomization. (1 point, 4 comments)
    10. Can we add the assignments and solutions to our public github profile? (0 points, 7 comments)
  29. 26 points, 6 submissions: abiele
    1. Recommended Reading? (13 points, 1 comment)
    2. Number of Indicators Used by Actual Trading Systems (7 points, 6 comments)
    3. Software Install Instructions From TA's Video Not Working (2 points, 2 comments)
    4. Suggest that TA/Instructor Contact Info Should be Added to the Syllabus (2 points, 2 comments)
    5. ML4T Software Setup (1 point, 3 comments)
    6. Where can I find the grading folder? (1 point, 4 comments)
  30. 26 points, 6 submissions: tomatonight
    1. Do we have all the information needed to finish the last project Strategy learner? (15 points, 3 comments)
    2. Does anyone interested in cryptocurrency trading/investing/others? (3 points, 6 comments)
    3. length of portfolio daily return (3 points, 2 comments)
    4. Did Michael Burry, Jamie&Charlie enter the short position too early? (2 points, 4 comments)
    5. where to check participation score (2 points, 1 comment)
    6. Where to collect the midterm exam? (forgot to take it last week) (1 point, 3 comments)
  31. 26 points, 3 submissions: hilo260
    1. Is there a template for optimize_something on GitHub? (14 points, 3 comments)
    2. Marketism project? (8 points, 6 comments)
    3. "Do not change the API" (4 points, 7 comments)
  32. 26 points, 3 submissions: niufen
    1. Windows Server Setup Guide (23 points, 16 comments)
    2. Strategy Learner Adding UserID as Comment (2 points, 2 comments)
    3. Connect to server via Python Error (1 point, 6 comments)
  33. 26 points, 3 submissions: whoyoung99
    1. How much time you spend on Assess Learner? (13 points, 47 comments)
    2. Git clone repository without fork (8 points, 2 comments)
    3. Just for fun (5 points, 1 comment)
  34. 25 points, 8 submissions: SharjeelHanif
    1. When can we discuss defeat learners methods? (10 points, 1 comment)
    2. Are the buffet servers really down? (3 points, 2 comments)
    3. Are the midterm results in proctortrack gone? (3 points, 3 comments)
    4. Will these finance topics be covered on the final? (3 points, 9 comments)
    5. Anyone get set up with Proctortrack? (2 points, 10 comments)
    6. Incentives Quiz Discussion (2-01, Lesson 11.8) (2 points, 3 comments)
    7. Anyone from Houston, TX (1 point, 1 comment)
    8. How can I trace my error back to a line of code? (assess learners) (1 point, 3 comments)
  35. 25 points, 5 submissions: jlamberts3
    1. Conda vs VirtualEnv (7 points, 8 comments)
    2. Cool Portfolio Backtesting Tool (6 points, 6 comments)
    3. Warren Buffett wins $1M bet made a decade ago that the S&P 500 stock index would outperform hedge funds (6 points, 12 comments)
    4. Windows Ubuntu Subsystem Putty Alternative (4 points, 0 comments)
    5. Algorithmic Trading Of Digital Assets (2 points, 0 comments)
  36. 25 points, 4 submissions: suman_paul
    1. Grade statistics (9 points, 3 comments)
    2. Machine Learning book by Mitchell (6 points, 11 comments)
    3. Thank You (6 points, 6 comments)
    4. Assignment1 ready to be cloned? (4 points, 4 comments)
  37. 25 points, 3 submissions: Spareo
    1. Submit Assignments Function (OS X/Linux) (15 points, 6 comments)
    2. Quantsoftware Site down? (8 points, 38 comments)
    3. ML4T_2017Spring folder on Buffet server?? (2 points, 5 comments)
  38. 24 points, 14 submissions: nelsongcg
    1. Is it realistic for us to try to build our own trading bot and profit? (6 points, 21 comments)
    2. Is the risk free rate zero for any country? (3 points, 7 comments)
    3. Models and black swans - discussion (3 points, 0 comments)
    4. Normal distribution assumption for options pricing (2 points, 3 comments)
    5. Technical analysis for cryptocurrency market? (2 points, 4 comments)
    6. A counter argument to models by Nassim Taleb (1 point, 0 comments)
    7. Are we demandas to use the sample for part 1? (1 point, 1 comment)
    8. Benchmark for "trusting" your trading algorithm (1 point, 5 comments)
    9. Don't these two statements on the project description contradict each other? (1 point, 2 comments)
    10. Forgot my TA (1 point, 6 comments)
  39. 24 points, 11 submissions: nurobezede
    1. Best way to obtain survivor bias free stock data (8 points, 1 comment)
    2. Please confirm Midterm is from October 13-16 online with proctortrack. (5 points, 2 comments)
    3. Are these DTlearner Corr values good? (2 points, 6 comments)
    4. Testing gen_data.py (2 points, 3 comments)
    5. BagLearner of Baglearners says 'Object is not callable' (1 point, 8 comments)
    6. DTlearner training RMSE none zero but almost there (1 point, 2 comments)
    7. How to submit analysis using git and confirm it? (1 point, 2 comments)
    8. Passing kwargs to learners in a BagLearner (1 point, 5 comments)
    9. Sampling for bagging tree (1 point, 8 comments)
    10. code failing the 18th test with grade_learners.py (1 point, 6 comments)
  40. 24 points, 4 submissions: AeroZach
    1. questions about how to build a machine learning system that's going to work well in a real market (12 points, 6 comments)
    2. Survivor Bias Free Data (7 points, 5 comments)
    3. Genetic Algorithms for Feature selection (3 points, 5 comments)
    4. How far back can you train? (2 points, 2 comments)
  41. 23 points, 9 submissions: vsrinath6
    1. Participation check #3 - Haven't seen it yet (5 points, 5 comments)
    2. What are the tasks for this week? (5 points, 12 comments)
    3. No projects until after the mid-term? (4 points, 5 comments)
    4. Format / Syllabus for the exams (2 points, 3 comments)
    5. Has there been a Participation check #4? (2 points, 8 comments)
    6. Project 3 not visible on T-Square (2 points, 3 comments)
    7. Assess learners - do we need to check is method implemented for BagLearner? (1 point, 4 comments)
    8. Correct number of days reported in the dataframe (should be the number of trading days between the start date and end date, inclusive). (1 point, 0 comments)
    9. RuntimeError: Invalid DISPLAY variable (1 point, 2 comments)
  42. 23 points, 8 submissions: nick_algorithm
    1. Help with getting Average Daily Return Right (6 points, 7 comments)
    2. Hint for args argument in scipy minimize (5 points, 2 comments)
    3. How do you make money off of highly volatile (high SDDR) stocks? (4 points, 5 comments)
    4. Can We Use Code Obtained from Class To Make Money without Fear of Being Sued (3 points, 6 comments)
    5. Is the Std for Bollinger Bands calculated over the same timespan of the Moving Average? (2 points, 2 comments)
    6. Can't run grade_learners.py but I'm not doing anything different from the last assignment (?) (1 point, 5 comments)
    7. How to determine value at terminal node of tree? (1 point, 1 comment)
    8. Is there a way to get Reddit announcements piped to email (or have a subsequent T-Square announcement published simultaneously) (1 point, 2 comments)
  43. 23 points, 1 submission: gong6
    1. Is manual strategy ready? (23 points, 6 comments)
  44. 21 points, 6 submissions: amchang87
    1. Reason for public reddit? (6 points, 4 comments)
    2. Manual Strategy - 21 day holding Period (4 points, 12 comments)
    3. Sharpe Ratio (4 points, 6 comments)
    4. Manual Strategy - No Position? (3 points, 3 comments)
    5. ML / Manual Trader Performance (2 points, 0 comments)
    6. T-Square Submission Missing? (2 points, 3 comments)
  45. 21 points, 6 submissions: fall2017_ml4t_cs_god
    1. PSA: When typing in code, please use 'formatting help' to see how to make the code read cleaner. (8 points, 2 comments)
    2. Why do Bollinger Bands use 2 standard deviations? (5 points, 20 comments)
    3. How do I log into the [email protected]? (3 points, 1 comment)
    4. Is midterm 2 cumulative? (2 points, 3 comments)
    5. Where can we learn about options? (2 points, 2 comments)
    6. How do you calculate the analysis statistics for bps and manual strategy? (1 point, 1 comment)
  46. 21 points, 5 submissions: Jmitchell83
    1. Manual Strategy Grades (12 points, 9 comments)
    2. two-factor (3 points, 6 comments)
    3. Free to use volume? (2 points, 1 comment)
    4. Is MC1-Project-1 different than assess_portfolio? (2 points, 2 comments)
    5. Online Participation Checks (2 points, 4 comments)
  47. 21 points, 5 submissions: Sergei_B
    1. Do we need to worry about missing data for Asset Portfolio? (14 points, 13 comments)
    2. How do you get data from yahoo in panda? the sample old code is below: (2 points, 3 comments)
    3. How to fix import pandas as pd ImportError: No module named pandas? (2 points, 4 comments)
    4. Python Practice exam Question 48 (2 points, 2 comments)
    5. Mac: "virtualenv : command not found" (1 point, 2 comments)
  48. 21 points, 3 submissions: mharrow3
    1. First time reddit user .. (17 points, 37 comments)
    2. Course errors/types (2 points, 2 comments)
    3. Install course software on macOS using Vagrant .. (2 points, 0 comments)
  49. 20 points, 9 submissions: iceguyvn
    1. Manual strategy implementation for future projects (4 points, 15 comments)
    2. Help with correlation calculation (3 points, 15 comments)
    3. Help! maximum recursion depth exceeded (3 points, 10 comments)
    4. Help: how to index by date? (2 points, 4 comments)
    5. How to attach a 1D array to a 2D array? (2 points, 2 comments)
    6. How to set a single cell in a 2D DataFrame? (2 points, 4 comments)
    7. Next assignment after marketsim? (2 points, 4 comments)
    8. Pythonic way to detect the first row? (1 point, 6 comments)
    9. Questions regarding seed (1 point, 1 comment)
  50. 20 points, 3 submissions: JetsonDavis
    1. Push back assignment 3? (10 points, 14 comments)
    2. Final project (9 points, 3 comments)
    3. Numpy versions (1 point, 2 comments)
  51. 20 points, 2 submissions: pharmerino
    1. assess_portfolio test cases (16 points, 88 comments)
    2. ML4T Assignments (4 points, 6 comments)

Top Commenters

  1. tuckerbalch (2296 points, 1185 comments)
  2. davebyrd (1033 points, 466 comments)
  3. yokh_cs7646 (320 points, 177 comments)
  4. rgraziano3 (266 points, 147 comments)
  5. j0shj0nes (264 points, 148 comments)
  6. i__want__piazza (236 points, 127 comments)
  7. swamijay (227 points, 116 comments)
  8. _ant0n_ (205 points, 149 comments)
  9. ml4tstudent (204 points, 117 comments)
  10. gatechben (179 points, 107 comments)
  11. BNielson (176 points, 108 comments)
  12. jameschanx (176 points, 94 comments)
  13. Artmageddon (167 points, 83 comments)
  14. htrajan (162 points, 81 comments)
  15. boyko11 (154 points, 99 comments)
  16. alyssa_p_hacker (146 points, 80 comments)
  17. log_base_pi (141 points, 80 comments)
  18. Ran__Ran (139 points, 99 comments)
  19. johnsmarion (136 points, 86 comments)
  20. jgorman30_gatech (135 points, 102 comments)
  21. dyllll (125 points, 91 comments)
  22. MikeLachmayr (123 points, 95 comments)
  23. awhoof (113 points, 72 comments)
  24. SharjeelHanif (106 points, 59 comments)
  25. larrva (101 points, 69 comments)
  26. augustinius (100 points, 52 comments)
  27. oimesbcs (99 points, 67 comments)
  28. vansh21k (98 points, 62 comments)
  29. W1redgh0st (97 points, 70 comments)
  30. ybai67 (96 points, 41 comments)
  31. JuanCarlosKuriPinto (95 points, 54 comments)
  32. acschwabe (93 points, 58 comments)
  33. pharmerino (92 points, 47 comments)
  34. jgeiger (91 points, 28 comments)
  35. Zapurza (88 points, 70 comments)
  36. jyoms (87 points, 55 comments)
  37. omscs_zenan (87 points, 44 comments)
  38. nurobezede (85 points, 64 comments)
  39. BelaZhu (83 points, 50 comments)
  40. jason_gt (82 points, 36 comments)
  41. shuang379 (81 points, 64 comments)
  42. ggatech (81 points, 51 comments)
  43. nitinkodial_gatech (78 points, 59 comments)
  44. harshsikka123 (77 points, 55 comments)
  45. bkeenan7 (76 points, 49 comments)
  46. moxyll (76 points, 32 comments)
  47. nelsongcg (75 points, 53 comments)
  48. nickzelei (75 points, 41 comments)
  49. hunter2omscs (74 points, 29 comments)
  50. pointblank41 (73 points, 36 comments)
  51. zheweisun (66 points, 48 comments)
  52. bs_123 (66 points, 36 comments)
  53. storytimeuva (66 points, 36 comments)
  54. sva6 (66 points, 31 comments)
  55. bhrolenok (66 points, 27 comments)
  56. lingkaizuo (63 points, 46 comments)
  57. Marvel_this (62 points, 36 comments)
  58. agifft3_omscs (62 points, 35 comments)
  59. ssung40 (61 points, 47 comments)
  60. amchang87 (61 points, 32 comments)
  61. joshuak_gatech (61 points, 30 comments)
  62. fall2017_ml4t_cs_god (60 points, 50 comments)
  63. ccrouch8 (60 points, 45 comments)
  64. nick_algorithm (60 points, 29 comments)
  65. JetsonDavis (59 points, 35 comments)
  66. yjacket103 (58 points, 36 comments)
  67. hilo260 (58 points, 29 comments)
  68. coolwhip1234 (58 points, 15 comments)
  69. chvbs2000 (57 points, 49 comments)
  70. suman_paul (57 points, 29 comments)
  71. masterm (57 points, 23 comments)
  72. RolfKwakkelaar (55 points, 32 comments)
  73. rpb3 (55 points, 23 comments)
  74. venkatesh8 (54 points, 30 comments)
  75. omscs_avik (53 points, 37 comments)
  76. bman8810 (52 points, 31 comments)
  77. snladak (51 points, 31 comments)
  78. dfihn3 (50 points, 43 comments)
  79. mlcrypto (50 points, 32 comments)
  80. omscs-student (49 points, 26 comments)
  81. NellVega (48 points, 32 comments)
  82. booglespace (48 points, 23 comments)
  83. ccortner3 (48 points, 23 comments)
  84. caa5042 (47 points, 34 comments)
  85. gcalma3 (47 points, 25 comments)
  86. krushnatmore (44 points, 32 comments)
  87. sn_48 (43 points, 22 comments)
  88. thenewprofessional (43 points, 16 comments)
  89. urider (42 points, 33 comments)
  90. gatech-raleighite (42 points, 30 comments)
  91. chrisong2017 (41 points, 26 comments)
  92. ProudRamblinWreck (41 points, 24 comments)
  93. kramey8 (41 points, 24 comments)
  94. coderafk (40 points, 28 comments)
  95. niufen (40 points, 23 comments)
  96. tholladay3 (40 points, 23 comments)
  97. SaberCrunch (40 points, 22 comments)
  98. gnr11 (40 points, 21 comments)
  99. nadav3 (40 points, 18 comments)
  100. gt7431a (40 points, 16 comments)

Top Submissions

  1. [Project Questions] Unit Tests for assess_portfolio assignment by reyallan (58 points, 52 comments)
  2. [Project Questions] Unit Tests for optimize_something assignment by agifft3_omscs (53 points, 94 comments)
  3. Proper git workflow by jan-laszlo (43 points, 19 comments)
  4. Exam 2 Information by yokh_cs7646 (39 points, 40 comments)
  5. A little more on Pandas indexing/slicing ([] vs ix vs iloc vs loc) and numpy shapes by davebyrd (37 points, 10 comments)
  6. Project 1 Megathread (assess_portfolio) by davebyrd (34 points, 466 comments)
  7. defeat_learner test case by swamijay (34 points, 38 comments)
  8. Project 2 Megathread (optimize_something) by tuckerbalch (33 points, 475 comments)
  9. project 3 megathread (assess_learners) by tuckerbalch (27 points, 1130 comments)
  10. Deadline extension? by johannes_92 (26 points, 40 comments)

Top Comments

  1. 34 points: jgeiger's comment in QLearning Robot project megathread
  2. 31 points: coolwhip1234's comment in QLearning Robot project megathread
  3. 30 points: tuckerbalch's comment in Why Professor is usually late for class?
  4. 23 points: davebyrd's comment in Deadline extension?
  5. 20 points: jason_gt's comment in What would be a good quiz question regarding The Big Short?
  6. 19 points: yokh_cs7646's comment in For online students: Participation check #2
  7. 17 points: i__want__piazza's comment in project 3 megathread (assess_learners)
  8. 17 points: nathakhanh2's comment in Project 2 Megathread (optimize_something)
  9. 17 points: pharmerino's comment in Midterm study Megathread
  10. 17 points: tuckerbalch's comment in Midterm grades posted to T-Square
Generated with BBoe's Subreddit Stats (Donate)
submitted by subreddit_stats to subreddit_stats [link] [comments]

Cryptocurrencies, Measuring Inflation by Value "siphoning" not by Supply

This is a follow up to this post:
I have been thinking about inflation and market cap a little bit more. In that post I have debunked the hyperinflation claims nonsense, but it got me thinking about the nature of inflation as probabilistic in nature.
I think the supply size doesn’t even matter at all, all of it is market based, and I tend to view inflation now as rather a vacuum of value or a transfer of value rather than a supply increase.
Simply put the supply is just an arbitrary number it has no value, it only has value in the context of a price. Thus the value of an asset is it’s market cap.

MarketCap based valuation & inflation

The market cap is the ultimate value of an asset, relative to a major currency. This still opens up new cans of worms since it’s all relativistic, to get an absolute value you might want to measure it compared to a basket of major currencies like the Dollar Index, and so on.
But the market cap gives the best valuation of an asset, so let’s just use USD as the benchmark.
The market cap is market based so as the market tends towards efficiency, the price will reflect eventually it’s true value.
However the market cap is still an uncertain valuation technique since it assumes that the hard cap is sacrosanct, which I don’t think it is (derivatives, and forks could extend it, not to mention fractional reserving on exchanges). By the way this applies to fiat currencies too.
As demonstrated in the previous post the 21m hard limit of Bitcoin can be extended to 27m assuming the forks are derivatives of the original coins, which is a stretch but currently it does influence the price of eachother (high correlation) so for now it’s true, later it might not be (the forks might decouple).
So we see that the M1,M2,M3 sort of supply classification is reasonable for cryptocurrencies too, the M1 would be the immediately usable blockchain coins out of which M0 would be personally held ones and M1 the ones on exchanges, the M2 would be the “investments” which are the forks too, as speculators put money in there in hopes of them going up in price and of course the savings and lending schemes in many Bitcoin based businesses, and the M3 would be the derivative tokens (like Ethereum’s tokens and Bitcoin’s colored coins) and leverage (many exchanges are allegedly operating on fractional reserves) and so forth.
Now the thing I observed and this made me think about it, is that many new cryptocurrencies are essentially worthless. So what stops people from creating millions of new ones a day? Nothing since it cost’s almost nothing except the minimal electricity and mining operation setup. So perhaps a couple of dollars of hosting and electricity costs to setup a new one, not totally free, but anyone can essentially create millions of new ones.
So what stops the hyperinflation? As pointed out in the other post that the inflation is not in the supply but in the market cap.
So if you create “XYZ coin” with 1 trillion supply but a market cap of only 1$ and a price of 1E-12 . You haven’t created an inflation of 4,762,004.76% to Bitcoin for example.
You have only created an inflation of 1$ worth, that is “stealing” away 1$ worth of value from Bitcoin as you transferred that value from Bitcoin into your worthless coin. You have only created an inflation of 0.00000000063464788980% to Bitcoin.
Also the value doesn’t come out of thin air, you didn’t just print up that 1$ out of nowhere, you had to put in at least that amount of effort into coding your new currency and setting up the web servers and so on.
So inflation is not supply based, it’s value based. And this holds true for fiat as well.

MarketCap Misleading

Now in cryptocurrencies market cap is misleading sometimes. Some exchanges have a minimum price of 1 satoshi. So of course if XYZ coin will have an 1 tn supply it may look like it’s worth a lot , in this case 10,000 $, but we know your XYZ coins is not worth that, so it’s misleading.
Now of course the orders won’t be executed at 1 satoshi, there is no way to create value out of nothing, most of these worthless coins won’t even have a Bid wall, only desperate people trying to sell all of it at 1 satoshi but no buyers, thus the coin may be worth 0 or between 0 and 1 satoshi. If the resolution of the price would be higher ,I am sure the market would find a suitable price for it in that range.
Either way you won’t be able to steal value out of the coin. Printing money simply doesn’t create wealth.

Volume & Probability based inflation

So then what to do with these situations? And by the way fiat currency can be mispriced like this due to capital controls and other regulatory barriers. So simply multiplying the M3 of the EUR with it’s EUUSD price won’t give it’s value.
So I thought an even more accurate way to look at inflation is the volume itself. I mean the dormant coins have no inflationary effect.
For instance Satoshi lost 1 million coins allegedly, now we can’t know for sure,but given that the coins haven’t been moved in almost a decade the probability is high.
So we can just assign a probability to that. Say 90% probability that the coins will never be moved. Okay then that is a -900,000 supply for Bitcoin. Similarly many people lost their wallets and will continue to do so, so the usable supply is shrinking.
So the best metric is to look at the money velocity or the transaction volume, say in a year. That can be a good metric. Some research is needed on this.
Now this gets complicated because we also need to add in the transaction volume on the chain and the transaction volume off chain, like exchanges. As 3rd party middleman do a lot of inhouse micro-transactions.
But basically the big picture can be seen on the transaction volume.
So the most important metric of Bitcoin is the transaction value in BTC, which can be seen here:
As you can see it’s pretty stagnant and stable, I my opinion this is the true metric of inflation of Bitcoin, because this reflects how much coins are active and dormant.
By definition dormant coins are not sold, this not increasing the coins in circulation, so they can’t siphon off value from Bitcoin by increasing it’s tradeable supply.
Thus Bitcoin has a maximum 0.85% “siphon” rate/ day, correlated with it’s true inflation which could be estimated by observing this, removing duplicate transactions and estimating the sell activity on exchanges to be more precise.

M3 & Conclusion

So it’s kind of ironic but I think the FED is right when they say that M3 doesn’t affect inflation that much. They have removed the M3 data in 2006 from their website which I don’t like due to transparency reasons, but they are right in saying that M3 doesn’t affect inflation that much.
I am not saying Keynesian economics gives a perfect answer I am just saying that hard limits aren’t entirely correct either.
Besides the USD M3 can be easily reconstructed and estimated and it really shows not much impact on inflation.
So this concept can be extended to fiat currency too, we know the volumes of Forex markets, at least at the central hubs which are reported by the World Bank periodically, so we could estimate the value of fiat currencies based on their transaction volumes on Forex markets.
This should be a much better approach than silly CPI indices.
submitted by alexander7k to Anarcho_Capitalism [link] [comments]

Potential phone interview with FX traders, need some advice.

Family friend put me in contact with a friend of his who runs a forex trading house in order to get some career advice (and i assume seek employment) and I want to get some advice on how to proceed.
Im in my last year of bachelors computer science and was mainly looking at software dev jobs, not with a particular focus on finance. I have completed one course on computer finance which covered option pricing, some basic stochastic finance like random walks, monte carlo simulations and just a general intro to quant finance (i.e volatilities, correlations).
I have completed a more lengthy paper on Value at Risk and writing a program to calculate it which i am a bit more confident on talking about.
I hadn't really considered a financial career as i was hoping to go into mobile software dev, but I want to make the best of this oppurtunity. From what I gather from their website they use some automated systems to trade so Im guessing thats what made this guy want to speak to me having done some coding related to finance (thats all he about me as of yet).
Hoping I could get some advice on:
submitted by uluvboobs to FinancialCareers [link] [comments]

FOREX CORRELATION: don't fall for the trap! - YouTube How to Do Correlation Scalping The Forex Correlation Code the Correlation Code Forex Correlation Secrets Der Correlation Trader - Korrelationen in Forex & CFD Märkten How Currency Correlation Works in Forex Trading - YouTube Correlation Code!

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