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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 ...
vonjd's user avatar
  • 27.4k
15 votes
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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 ...
Matthew Gunn's user avatar
  • 6,944
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 ...
Alex C's user avatar
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14 votes
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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 ...
NBF's user avatar
  • 1,068
13 votes
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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 ...
mperlow's user avatar
  • 456
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 ...
Helin's user avatar
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12 votes
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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 ...
Jan Stuller's user avatar
  • 6,098
12 votes
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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 ...
amdopt's user avatar
  • 4,338
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 ...
madilyn's user avatar
  • 5,240
10 votes
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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 ...
Alper's user avatar
  • 1,036
10 votes

Does AI-based trading assume efficient market hypothesis?

Most traders that I know have a complex relationship with the Efficient Markets Hypothesis, difficult to summarize. You could say that they accept a "soft version of EMH" but not the ...
nbbo2's user avatar
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9 votes
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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).
Chris Taylor's user avatar
  • 5,911
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 ...
David K. Storrs's user avatar
8 votes
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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 ...
vonjd's user avatar
  • 27.4k
8 votes
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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 "...
databento's user avatar
  • 2,488
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 ...
roz's user avatar
  • 969
7 votes
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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 ...
Hamish Gibson's user avatar
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 ...
databento's user avatar
  • 2,488
7 votes
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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 ...
Sergei Rodionov's user avatar
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 ...
Bob Jansen's user avatar
  • 8,552
6 votes
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What are some quantitative trading strategies used by high-frequency trading companies to make a killing on a market crash day on 24Aug2015?

On aggregate, large shops like Virtu are involved in market making strategies. There's various classes of market making strategies, and it is unnecessary to distinguish further here for the purpose of ...
madilyn's user avatar
  • 5,240
6 votes

What is smart beta, alternative index, factor investing?

In recent years there has been much attention given to defining indexes other than market-cap based indices. While market-cap based indices approximate the theoretical Market Portfolio enshrined in ...
nbbo2's user avatar
  • 11.3k
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 ...
lehalle's user avatar
  • 12.1k
6 votes

Does QuantConnect use both bid and ask data for backtesting?

QuantConnect uses L1 data (bid and ask quotes) for its US Equities Backtesting. QuantConnect has a full break down of the data library, including free data for download in LEAN format at the data ...
JaredBroad's user avatar
6 votes
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Calculating the returns of a long/short strategy

There are two ways to calculate the returns. One way is to calculate the net asset value (NAV) of your portfolio. For the long side the NAV is the value of your stock holdings. For the short side the ...
RRG's user avatar
  • 1,024
6 votes

Is there a non-recursive way of calculating the exponential moving average?

The point of the recursive formula is that you can easily calculate the current EWMA if you have last period's EWMA. Equivalently, you can calculate all the weights directly and sum them that way. $$ ...
msitt's user avatar
  • 741
6 votes
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CAPM and factor modeling: Machine learning

1) In an academic sense could it be enough to use ML to create a new factor portfolio? The original FF papers (92,93) said something deep because they contradicted the dominant theory of the day. ...
jd8's user avatar
  • 468
6 votes
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approach on trading algorithm using machine learning

'Machine learning' describes a very broad spectrum of algorithms. Just briefly here are a few conceptual areas; Neural networks Reinforcement learning Genetic algorithms and genetic programming ...
Attack68's user avatar
  • 10.2k
6 votes

How could one trade volatility skew if you think it's too flat or steep?

Trading the skew is a common practice for traders specializing in options. Let's say you have a 3M skew curve like the blue one below (where I have highlighted a few key strikes) but you think the ...
Brian B's user avatar
  • 14.9k
6 votes
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DB quant research

I think it is not publicly available... I have the paper but I am obviously not allowed to share it publicly. Normally the best is to contact one of the authors but I checked and it seems that all f ...
vonjd's user avatar
  • 27.4k

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