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Apr
6
comment How to compare different volatility measures?
But what is your RV estimate? The RV function that is closest to some $VOL_i$ will make the slope coefficient larger for that particular $i$...
Feb
8
comment How can I go about applying machine learning algorithms to stock markets?
This is thoroughly incomplete as this information may already be in the current price. You need another layer to this system to test whether the information is or is not in the price.
Dec
11
comment interpreting huge jumps
I can't answer your question unless you give me your model.
Nov
9
comment Econometric vs ANN models for forecast?
Brilliant answer!
Oct
27
awarded  Yearling
Oct
23
comment evaluation of volatility models using loss functions
Possible duplicate of quant.stackexchange.com/questions/8056/…
Oct
19
accepted So many volatility models. Any comparisons of them?
Aug
18
comment How to compute a sector's volatility within a portfolio?
This question is not clear to me. If you want to calculate the volatility of the sector portfolio why is the correlation of the portfolio's constituents with other sector's constituents relevant?
Aug
18
comment Is variable binning a good thing to do?
@xiaodai Why not? Your answer doesn't actually answer this question.
Aug
16
comment Is variable binning a good thing to do?
This doesn't actually explain why it's better to bin.
Aug
15
comment Is variable binning a good thing to do?
Is there a reference to back these assertions?
Aug
14
comment Is there a copula that can estimate negative tail dependence?
Yes, you have my question right, and very nice addition! Could you please define in more detail what $(k+1)$ is? Also, is there any research on using state space modelling to get a time-varying estimate $\hat{\beta}(t)$?
Aug
10
comment What's the difference between volatility and variance?
Variance is also associated with the underlying process (population variance vs. sample variance).
Aug
10
comment How do I estimate the joint probability of stock B moving, if stock A moves?
The main deficiency of this would be if you want a time-varying estimator of conditional probability, since once you've got large $N$, $\hat{p}_N$ would respond very slowly to a sudden clustering of joint positive returns. Here you would want time-varying copulas (not estimated through MLE).
Aug
10
comment R: Fast and efficient way of running a multivariate regression across a (really) large panel (First pass of Fama MacBeth)
For the non-NA matching try data[complete.cases(data),]
Aug
10
answered How do I estimate the joint probability of stock B moving, if stock A moves?
Aug
9
comment R: Fast and efficient way of running a multivariate regression across a (really) large panel (First pass of Fama MacBeth)
Two ideas; (i) don't run lm(...), use $(X'X)^{-1}X'Y$. (ii) every so often do a write.csv' or a save, and rm() to clear memory, (iii) run the as.character on the whole vector of dates instead of on a single date in each loop iteration..
Aug
7
revised Tools in R for estimating time-varying copulas?
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Aug
7
answered Tools in R for estimating time-varying copulas?
Aug
7
revised Why are regressors squared and not ^1.5 or ^2.2 or ^2.5?
added 49 characters in body