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MIT computer scientists can predict the price of Bitcoin
71–80 of 86 posts
Re: MIT computer scientists can predict the price of Bitcoin
#72Can a HFT-knowledgeable commenter chime in on the viability of the Sharpe ratio here? From a physics perspective, it appears that the Sharpe ratio of 4.1 is roughly equivalent to a 4.1-sigma claim that their algorithm is better than random trading. I can't check easily, but I'd guess that the movement of Bitcoin prices isn't normally-distributed (looking at the paper's time series suggests that there's more low-frequ…
A sharpe of 4 is ok. Most "HFT" type strategies have sharpes so high they don't talk about sharpe anymore as it is meaningless. It is simply a different type of trading. See Virtu's pnl distribution in their S1. As a point of reference, Blair Hull is on record saying they are interested in nothing below a sharpe of 10 (r-finance talk, should be googleable).
Thanks for sharing.
Link: http://www.nasdaq.com/markets/ipos/filing.ashx?filingid=9443...
Re: MIT computer scientists can predict the price of Bitcoin
#73The problem with the paper is not overfit. They claim to have run their simulation with out of band ("live") data. The actual problem with the paper is that we have no idea if their simulator is any good, which means that their result (89% return in 50 days) could be totally bogus. In other words, we don't know if the actual bitcoin exchange would fill their orders at the same prices (if at all) as their simulator do…
Even with live data as a validation set (and ignoring your point about execution friction), it's inappropriate to naively infer expected future return from total return during the validation run, since asset price fluctuations don't follow a normal distribution. Very high volatility events happen far more commonly than a Bell curve predicts, hence a few lucky or unlucky outliers can skew your total. The Sharpe ratio which they used to measure risk exposure also dangerously assumes a normal distribution.
Re: MIT computer scientists can predict the price of Bitcoin
#74The problem with the paper is not overfit. They claim to have run their simulation with out of band ("live") data. The actual problem with the paper is that we have no idea if their simulator is any good, which means that their result (89% return in 50 days) could be totally bogus. In other words, we don't know if the actual bitcoin exchange would fill their orders at the same prices (if at all) as their simulator do…
>we don't know if the actual bitcoin exchange would fill their orders at the same prices
This is the problem with many simulated trading algorithm "success" stories. No one actually knows the effect that the simulated trades would have on the real market, or how others trading against the algorithm would react to these trades. The numbers may be somewhat close to reality if the simulated trades are very small in relation to the trading volume for the asset. However, Bitcoin markets are small to begin with, which probably makes the results in this paper unreliable.
Re: MIT computer scientists can predict the price of Bitcoin
#75Earlier quoted context omitted.
I see no mention of the spread, costs or even ability to put on a short position, exchange lag variability (huge issue when simulating even on modern exchanges, let alone fly-by-night bitcoin markets). Additionally, it is very easy to find trend-following signals that "work" but break down when conditions change very quickly. That seems to make up most of the prediction, along with an order book imbalance signal that…
About 35 million USD in trades on the public bitcoin-paired markets today. About 40 million USD today in total volume for all pairs on these exchanges. http://www.cryptocoincharts.info/coins/info
More than when I last looked, but to put that in perspective, you could trade $40mm in a few price ticks in major currency pairs and CME avg daily turnover alone is > $100bn: http://cmegroup.mediaroom.com/2013-06-07-CME-Group-Sees-Reco...
Public spot FX markets and OTC trading do huge volumes too.
Some BTC exchanges charge like 60 bps per trade. Finding a signal to overcome that cost and do enough trading to make it worthwhile would be quite difficult.
Re: MIT computer scientists can predict the price of Bitcoin
#76I'm late to comment, but something which I'd like to point out is that this is done by the same team behind the Twitter trending topic prediction technique from a few years back, as mentioned also in the article [1].
When their Twitter technique was released, I spend a few weeks reading through Nikolov's PhD thesis (the advisor gets most of the the fame in the press articles but Nikolov's thesis has all the details) and trying to implement it in R. My observations at the time: extremely simple algorithm which would be shot down by most peer reviewers for being not very novel (the affiliation helps a lot here). That said, I believe greatly in pragmatism, and the approach was actually working well. What I did find out however is that their was a great deal of data selection and pre-processing involved making the approach hard to implement in a real-life, real-time setup. I get similar feelings from this work.
[1]: http://newsoffice.mit.edu/2012/predicting-twitter-trending-t...
Re: MIT computer scientists can predict the price of Bitcoin
#77Sometime in 2013, before the bitcoin prices exploded, I downloaded some bitcoin historical price data and ran symbolic regression on it with Eureqa. It came up with a formula that fit the observed data fairly well, and wasn't very complicated. But when I extrapolated it forward a few months, it predicted the price would explode to unreasonable levels. I was disappointed and threw it away, assuming that it must be wro…
Thank you for sharing the Eureqa software. Wasn't aware of it. +1
Re: MIT computer scientists can predict the price of Bitcoin
#78I'm late to comment, but something which I'd like to point out is that this is done by the same team behind the Twitter trending topic prediction technique from a few years back, as mentioned also in the article [1]. When their Twitter technique was released, I spend a few weeks reading through Nikolov's PhD thesis (the advisor gets most of the the fame in the press articles but Nikolov's thesis has all the details)…
Could you specify what kind of data selection and pre-processing was required and why exactly it was hard to implement it in a real-life setup?
Re: MIT computer scientists can predict the price of Bitcoin
#7989% over 2 months. Not bad. My algorithm did 8,000% over 6 months using real money on real exchanges and I have the trade history to back it up.
What exchanges do you recommend for bot trading? ... I've dabbled a bit trading manually on bitfinex but that's all.
Re: MIT computer scientists can predict the price of Bitcoin
#80The problem with the paper is not overfit. They claim to have run their simulation with out of band ("live") data. The actual problem with the paper is that we have no idea if their simulator is any good, which means that their result (89% return in 50 days) could be totally bogus. In other words, we don't know if the actual bitcoin exchange would fill their orders at the same prices (if at all) as their simulator do…
From the article:
>Specifically, every two seconds they predicted the average price movement over the following 10 seconds. If the price movement was higher than a certain threshold, they bought a Bitcoin; if it was lower than the opposite threshold, they sold one; and if it was in-between, they did nothing.
If they are indeed predicting the price at X+10 seconds at second X, they have more than enough time to act on that info without having to do HFT.