Devavrat shah bitcoin stocks
With the Bitcoin research complete, he says he now feels confident modeling virtually any quantity that varies over time — including, he says half-jokingly, the validity of astrology predictions. If you want to give Bitcoin a try without spending money, have a look at http: Bitcoin is unpredictable,crime however can be predicted along with all the other variables you mentioned because they have been around much longer than bit coin and we at least have a understanding of where it came from.
We still don't even know who configured bit coin which is problematic because for all we know someone is in the system itself. Think about it,whoever made this technology knows the inns and outs. We might not be able to remove Bitcoin volatility at this point, but perhaps having it be predictable will remove the concern over volatility, or lead to more stability as more players enter the market.
These guys are full of it. The correlation they have found won't last; they never do when dealing with the future. Pretty soon they will be telling us that they drive to work by only looking in their rear view mirror.
It will work until the big truck behind them loses its brakes. Oops, hard to predict that. This kind of trading is good for price stability over the short term.
Let's hope it becomes more widely adopted. If you take part in an experiment then you affect the outcome of the experiment. If you observe how cattles graze and the environment that predicts their habits is one thing. But to graze with the cattles is another. By taking part in the experiment the outcome over time is not predictable. You add an element to the unpredictability. There is indeed nothing new with this approach: I used it back in when trading on the interest rate futures for a French bank, then a Houston-based Commodity trading advisor.
The returns were good. Am I missing something? It appears these guys didn't actually trade anything. So these results mean nothing. My algorithm did 80x over 6 months and I'm an undergrad working alone Bayesian regression was used 25 years ago to predict stock returns with no great success. The problem is data-mining bias, which the authors do not address.
They select the best performing models without a correction for multiple comparisons. Obviously, the best model did well but many other models failed. The problem is which model to use forward. Add friction and you get a negative result. Let the algorithm wars commence! If you want to make money, find an unsophisticated place and start a smart war. The algorithm that evolves the quickest wins. Long-Term Capital Management rev 2. Taleb has written extensively on the errors of this general approach.
Interesting how people are attracted to the idea of getting money without producing anything of value. If you give me the ton of money that those guys got to produce such a crappy paper, I will debunk it and explain everything that is wrong with this They would have done better to simply buy at the start and sell at the end.
This is all over fitted. These sort of papers are worth less than the paper to print them. It is a shame that prestigious institutions such as MIT allow to publish such a rubbish. I am in the business of automated trading since years and papers showing such results are seldom reproducible. Authors claiming such a performance should either a provide access to code and data to make their experiments reproducible after all this is science , or b stop working in academia and start their hedge fund.
Those not acting according to a or b are charlatans, see http: Note that someone tried to reproduce the results of the paper here: The heavy math needs the manually picked-up clusters to work Albatross robot takes flight Fleet of autonomous boats could service some cities, reducing road traffic Eight from MIT receive Fulbright awards Exploring the impact of campus sustainability efforts TESS takes initial test image 3 Questions: Helping others broaden their horizons.
These guys are full of it. The correlation they have found won't last; they never do when dealing with the future. Pretty soon they will be telling us that they drive to work by only looking in their rear view mirror.
It will work until the big truck behind them loses its brakes. Oops, hard to predict that. This kind of trading is good for price stability over the short term.
Let's hope it becomes more widely adopted. If you take part in an experiment then you affect the outcome of the experiment. If you observe how cattles graze and the environment that predicts their habits is one thing. But to graze with the cattles is another. By taking part in the experiment the outcome over time is not predictable. You add an element to the unpredictability. There is indeed nothing new with this approach: I used it back in when trading on the interest rate futures for a French bank, then a Houston-based Commodity trading advisor.
The returns were good. Am I missing something? It appears these guys didn't actually trade anything. So these results mean nothing. My algorithm did 80x over 6 months and I'm an undergrad working alone Bayesian regression was used 25 years ago to predict stock returns with no great success. The problem is data-mining bias, which the authors do not address. They select the best performing models without a correction for multiple comparisons.
Obviously, the best model did well but many other models failed. The problem is which model to use forward. Add friction and you get a negative result. Let the algorithm wars commence! If you want to make money, find an unsophisticated place and start a smart war. The algorithm that evolves the quickest wins. Long-Term Capital Management rev 2. Taleb has written extensively on the errors of this general approach.
Interesting how people are attracted to the idea of getting money without producing anything of value. If you give me the ton of money that those guys got to produce such a crappy paper, I will debunk it and explain everything that is wrong with this They would have done better to simply buy at the start and sell at the end.
This is all over fitted. These sort of papers are worth less than the paper to print them. It is a shame that prestigious institutions such as MIT allow to publish such a rubbish. I am in the business of automated trading since years and papers showing such results are seldom reproducible. Authors claiming such a performance should either a provide access to code and data to make their experiments reproducible after all this is science , or b stop working in academia and start their hedge fund.
Those not acting according to a or b are charlatans, see http: Note that someone tried to reproduce the results of the paper here: The heavy math needs the manually picked-up clusters to work Protecting confidentiality in genomic studies Self-driving cars for country roads Building AI systems that make fair decisions Vinod Vaikuntanathan wins Edgerton Faculty Award.
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