49 votes
Accepted

Is R being replaced by Python at quant desks?

My deal is HFT so what I care about is read/load data from file or DB quickly in memory perform very efficient data-munging operations (group,transform) visualize easily the data I think is is ...
  • 1,248
32 votes

Is R being replaced by Python at quant desks?

Instead of wild guesses about R's/python's future in the community, here some facts: The following query on StackExchange Data Explorer counts the number of questions that have ...
  • 481
26 votes

Is R being replaced by Python at quant desks?

This is interesting because I see another trend: Matlab is being replaced by R, but I guess this is another story. I use R for my academic (I am also teaching this stuff) as well as my consulting ...
  • 27k
23 votes

Is R being replaced by Python at quant desks?

I've used both R and Python with Pandas in a professional quantitative financial work to do both large and small scale projects. I would strongly recommend Python with Pandas over R for most new ...
  • 1,561
22 votes

How did James Simons clinch that security prices didn't look random?

I'm sure Simons, as a first-rate pure and applied mathematician, had sufficient understanding of statistics to detect market inefficiencies and anomalies. As far as I know, the development and ...
  • 3,470
13 votes

Is R being replaced by Python at quant desks?

For data analysis, particularly for large data analysis project, pretty much most of the top quant hedge funds and a lot of the banks are using Python (over R) for a couple of reasons but many still ...
  • 782
11 votes
Accepted

What is the total correlation between assets in a portfolio?

This is indeed an interesting question. According to this website, a paper by Goldman Sachs [Tierens and Anadu (2004)] proposes three alternative methods for estimating average stock correlations: ...
  • 27k
11 votes

How did James Simons clinch that security prices didn't look random?

Jim Simons' initial intuitions about nonrandomness were probably driven by the very psychological/evolutionary predispositions to want to find the hidden meaning within noise that affect humanity in ...
9 votes

Book recommendation for time series analysis

I would suggest Time Series Analysis by James Douglas Hamilton
9 votes
Accepted

Correlation between stock prices given correlation between returns

We can obtain a closed-form expression for price correlation given (log) return correlation when the two stocks follow geometric Brownian motion: $$S_1(t) = S_1(0)e^{(\mu_1- \frac{1}{2} \sigma_1^2)t}...
  • 3,470
8 votes

What is the total correlation between assets in a portfolio?

I just want to add to vonjd's answer some info on the comparison of the 3 methods. This is too big for a comment so I'm posting as a separate answer but please upvote his answer, not mine. Do the ...
  • 741
8 votes
Accepted

How can I measure returns such that the average is useful?

Take the log return between days.
7 votes

What are the canonical books for statistics applied to finance?

I think a good book to start in your case is: Attilio Meucci: Risk and Asset Allocation I once had a seminar held by Attilio that was based on the book and it blew my mind. The book is very ...
  • 27k
7 votes

What are the canonical books for statistics applied to finance?

Elements of Statistical Learning by Hastie, Tibshirani and Friedman is one of the most-cited books for your purpose. Although it does not have any direct applications to Finance, this is definitely a ...
  • 289
7 votes

Predict the behavior of a time series (P&L trading desk)

Without seeing your trading desk's P&L it's impossible to say whether it is predictable or not. But here are a few thoughts - There's no reason to think that it isn't predictable. In general, ...
  • 5,638
6 votes

How to fit ARMA+GARCH Model In R?

This should walk you through what you are looking for: https://www.quantstart.com/articles/Generalised-Autoregressive-Conditional-Heteroskedasticity-GARCH-p-q-Models-for-Time-Series-Analysis https://...
  • 207
6 votes

Kalman Filter Equity Example

The following paper gives you a step-by-step presentation of how to use the Kalman filter in an application in a pricing model framework for a spot and futures market. Everything is explained using ...
  • 27k
6 votes

Is R being replaced by Python at quant desks?

For the tasks listed, both Python and R perform very well. There are some packages in Python not in R and vice versa. My solution for this is to simply call R from Python. This allows for the best of ...
  • 2,080
6 votes

Is R being replaced by Python at quant desks?

Also in the high frequency / medium frequency field here. I received a "mixed" consensus regarding the use of R and its prevalence in the field (specifically HFT). Speaking with someone who works in ...
  • 1,142
6 votes
Accepted

How to calculate the JdK RS-Ratio

Reading what I have, I can only offer a guess. 1: Let's say you're looking at 9 sectors compared to \$SPX on a daily chart. Foreach sector, compute relative closing price: 100 * Sector/\$SPX 2: It ...
  • 76
6 votes
Accepted

Interpreting Eigenvalues of Co-variance Matrix

What you basically do here is a Principal Component Analysis (PCA). A good starting point in the financial sphere is Managing Diversification by Attilio Meucci (2010) Page 3: "The most natural ...
  • 27k
6 votes

How did James Simons clinch that security prices didn't look random?

I will disagree with RPL's answer - Simons is not particularly known as an applied mathematician, but he did work for some time at the Institute for Defense Analysis [IDA] (he was fired for ...
6 votes
Accepted

How to test signifcance of a sharpe ratio

The answer above is not correct. Let's go by parts: Denote the mean of returns $\mu$. Denote the standard deviation of returns: $\sigma$. Therefore the sharpe ratio is: $$ SR = \frac{\mu-r_f}{\sigma} $...
  • 6,923
6 votes
Accepted

Shrinkage of the Sample Covariance matrix, theory

Yes. It comes from a core theorem of statics, Stein's Lemma. It shook the foundations of the field of statistics when it came out. It blew up an entire way of viewing mathematical statistics. ...
  • 4,123
6 votes

How can I measure returns such that the average is useful?

What does not work with the geometric mean? The geometric mean is computed with the following formula: $${\displaystyle \left(\prod _{i=1}^{n}x_{i}\right)^{\frac {1}{n}}={\sqrt[{n}]{x_{1}x_{2}\cdots ...
  • 4,922
5 votes

Should I use an arithmetic or a geometric calculation for the Sharpe Ratio?

The correct answer is "arithmetic mean, because Bill Sharpe says so". He invented the thing, and he's pretty clear on which one he was looking at. If you use the geometric mean, which is lower the ...
  • 51
5 votes

What machine learning method is more suitable for prediction of financial time series?

From what I have read, there are 3 popular algorithms for financial time series. Random Forests and SVMs, then followed by Neural Network Architectures. There are a couple of good papers, to name a ...
5 votes
Accepted

How is stock data objectively different to this random walk?

I think the main difference even in this little example is the gain-loss asymmetry which is a known stylized fact: When you look at the big bump both time series posses your artificial one is ...
  • 27k
5 votes

Bayesian or Frequentist in Finance?

I would distinguish between Bayesian inference versus Bayesian portfolio management techniques. Inference includes estimating parameters and credible intervals (the Bayesian version of confidence ...
  • 5,311
5 votes

How to calculate the JdK RS-Ratio

I think the normalisation step is incorrect. Since we would like have 100 as our baseline, it should be 100 + ((value-mean)/stddev + 1). Then we get fairly realistic results. See the following Python ...
  • 57

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