15
votes
Usage of Random forests in Quantitative analysis of stocks
Recently I attended a presentation by the first author of the following paper who gave us quite a creative and illuminating (kind of meta-)use of random forests in Quant Finance:
All that Glitters Is ...
- 27.2k
15
votes
Accepted
Why do trading strategies lose effectiveness over time?
There are two key concerns (which in practice, may be difficult to distinguish):
Previous research overestimated an effect.
The effect shrinks over time.
1. Problems with reproducibility and ...
- 6,824
15
votes
Doing opposite of what the model says
If you do this, you would destroy the value of the statistical tests that you performed on the backtest. You had a hypothesis that the strategy would make money, but the hypothesis was rejected. You ...
- 9,222
14
votes
Accepted
Why are there so few published research papers that apply Deep Learning to Algorithmic Trading?
I would say that most ML methods risk overfitting and it depends very much on the asset class. The only area where more sophisticated ML methods such as deep learning appear to make a major difference ...
- 1,058
13
votes
Quantitative strategies in the Fixed Income space
Here are some general directions:
Alternative Risk Premia
The ARP, or "smart beta," space has gained a lot of tractions over the past few years. These are rule-based strategies that provide ...
- 11.2k
12
votes
Accepted
Orderbook Arbitrage
A public order book gives traders information not only on the current price of a security, but also the volume and structure of the entire supply and demand schedule.
Such information can be used for ...
- 286
12
votes
Accepted
What are the "sniffing" or "stalking" algorithms?
Sniffing (or stalking) algo indeed detects other algorithms. How does that work in practice?
Imagine the order book for a particular equity is: Bid 1 = 99 (size 10,000), Bid 2 = 98 (size 25,000), Bid ...
- 5,723
12
votes
Accepted
How long do algorithmic trading strategies typically remain profitable?
Is there a typical "half-life" of a strategy?
This is a really subjective question, and I don't think any singular answer will generalize well. That being said, I will give some examples ...
- 4,315
11
votes
How to calculate Sharpe Ratio from $ returns?
Let's say your cumulative return series is $\{R_i \mid i=0,1,...,N-1\}$ of length $N$ days.
There's 3 conventional ways to do this at this stage. You may convert the cumulative dollar return curve ...
- 5,224
10
votes
Orderbook Arbitrage
I am not sure Dark Pools (DP) have been created to avoid "market manipulation". They have been created by firms because they found an advantage to create them (see Market Microstructure in Practice, L ...
- 11.2k
10
votes
Accepted
statistical arbitrage vs factor trading
1) Why would you trade the error on the residual instead of creating a long/short factor model and trade expected returns?
I would posit that the biggest reason people do this is for orthogonality of ...
- 416
9
votes
What is the best alternative of Quantlib library
The Strata project is the new pure Java market risk quant library from OpenGamma. For more information, see the documentation and GitHub. It is Apache v2 licensed.
Strata takes the experience of the ...
- 292
9
votes
Why are Quantquote historical trades different vom ActiveTick historical trades
Let me guess, you fell for one of the fake Quantquote reviews and decided to purchase their buggy data?
The reason for the missing quotes is Quantquote data is more of a snap-shot of market activity. ...
- 91
9
votes
Accepted
What is an acceptable Sharpe Ratio for a prop desk?
A Sharpe ratio of at least 1 in backtesting is a promising start, but that is just one of many statistics of interest. The Sharpe ratio measures return per unit volatility, i.e., return per unit risk....
- 405
9
votes
Accepted
What is the appropriate benchmark for a Long/Short VIX futures strategy?
If your strategy truly has no directional bias, then the benchmark should be cash (ie whatever you would earn using the capital in your trading account and taking no risk).
- 5,778
9
votes
Accepted
Online sources for quantitative finance research
Below are some of the sources one can use to search for and view or download research articles and other publications on quantitative finance (QF). Many include non-peer-reviewed articles in their ...
- 956
8
votes
Why are Quantquote historical trades different vom ActiveTick historical trades
This is an old post, but I thought I would offer the following facts:
1) QQ claims to be sited in the Empire State Building, Suite 2100. (https://quantquote.com/contact.php) That is false. They do ...
8
votes
Accepted
What mathematical models did Harry Markopolos run to prove that Bernie Madoff 1% a month gain was a Ponzi scheme?
You can find everything you want to know about this here (and in a very readable and easily reproducible form):
How Students Can Backtest Madoff’s Claims by Michael J. Stutzer (2009)
From the ...
- 27.2k
8
votes
Is trading mean reversion of small principal components of prices profitable?
Within the fixed income space, there's a lot of literature on PCA trading.
The first 2-3 principal component factors (PCs) can typically explain 90-99% of the total variances in yield curve movement....
- 11.2k
8
votes
Accepted
Why do anomalies disappear after they get detected?
The best explanation I have seen so far is the so-called Adaptive Market Hypothesis by Andrew Lo:
The adaptive market hypothesis, as proposed by Andrew Lo, is an
attempt to reconcile economic ...
- 27.2k
8
votes
Accepted
What is the reason for using log prices in Pairs Trading (Cointegration)?
I'm assuming that the paper you're referring to uses the Engle-Granger test for cointegration. The standard test procedure checks for unit roots in the residuals of a linear regression. It is a "...
- 2,233
7
votes
How useful is the genetic algorithm for financial market forecasting?
I just made a Genetic Algorithms calculator you can try at http://www.gregthatcher.com/Stocks/GeneticAlgorithmCalculator.aspx
I'm not a "quant expert" like all of you (I'm just a programmer), but ...
- 266
7
votes
Is it possible to make profit by reversing client trades for a market maker?
If you are market making equities or futures you tend to make your profits over the short term by flipping your inventory. So if I'm showing 3.00 bid at 3.01 ask on a stock I'm going to tend to flip ...
- 929
7
votes
Accepted
Algorithmic Trading: Python vs SQL
Python has lots of excellent libraries to compute Technical indicators for you, ta and ta-lib are great. These libraries have ...
- 637
7
votes
Known mispricing opportunities only available for small traders
The claim that there are small opportunities that are overlooked by large institutions is increasingly untrue. Some large firms specialize specifically in aggregating a large number of low capacity ...
- 2,233
7
votes
Accepted
Formerly profitable algorithmic trading strategies?
Take a look at compilations such as 151 Trading Strategies.
I wouldn't expect this information to be widely disclosed. After all, a non-profitable strategy is a supermartingale which means there is an ...
- 1,152
7
votes
If 90% of retail traders lose money, doesn’t that mean price movements are not random?
Markets might be nonrandom but retail traders losing money on average is insufficient evidence of this. Most folks lose money playing roulette despite the outcome being random. As noob2 suggests in ...
- 8,258
6
votes
What is the best alternative of Quantlib library
I did not tested it by now, but Google released a library similar to quantlib written in TensorFlow (tf-quant-finance). It may be worthwhile to test it (and to post here your views on it), because ...
- 11.2k
6
votes
Accepted
Binomial tree vs trinomial tree in pricing options
you have to be careful to distinguish between trinomial trees in a theoretical sense which do not give unique prices, and trinomial trees chosen as an approximation to the risk-neutral measure of the ...
- 6,843
6
votes
Accepted
Covariance between two stocks in a two-factor model
Your questions is unclear but I guess you mean that for the return of stock A you find a model
$$
r_A = (0.5, 0.75) (r_F^1, r_F^2) + \epsilon_A
$$
where $r_F^i$ are the factor returns and $\...
- 13.5k
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