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11h
comment Why are we obsessed over normalizing financial data?
@BCLC I would consider standardizing a type of normalizing, but most of the time when people talk about normalizing they're talking about standardizing.
12h
comment Why are we obsessed over normalizing financial data?
@BCLC Well you could use logs or log returns with economic and financial data. Depends on what you're doing.
2d
comment Why are we obsessed over normalizing financial data?
Normalization typically means subtract the mean and divide by the standard deviation. That transformation won't make non-normal data normal.
Jul
26
answered Finding a basket of stocks that tracks an index
Jul
22
answered How to deal with extreme cases in normal random numbers generation?
Jul
17
answered Handling Missing values in stocks returns when estimating the co variance matrix
Jul
16
comment Math basics of Equally-weighted Risk contributions
I had first read about risk contributions in Jorian's Value at Risk. There's a paper by Boudt, Carl, and Peterson in the Journal of Risk that does the calculations for CVaR that I sometimes refer to also.
Jul
14
comment How to get permanently growing chart within PCA
I'm pretty sure that all they do is convert returns back to levels.
Jun
27
comment Correlation of Dividend Yield Index/Stock
I haven't done the regressions personally, but I would expect that there is a cointegrating relationship between dividend yields for individual stocks and the yield of the index. There is also a mean-reverting effect in dividend yields more generally that you should incorporate.
Jun
27
comment economic facts that causes the financial time series to be heavy tailed
Providing more details will improve this answer.
Jun
27
comment How to estimate a value for 2 categories with 2 different weights
I'm not really sure what you're asking. Can you clear make this clearer?
Jun
25
answered economic facts that causes the financial time series to be heavy tailed
Jun
21
comment Weighting several returns over different time frames
Ignoring any GIPS-related issues, I think the weighted returns are too complicated for most presentations. That depends on your audience, of course, but people understand a table showing a few different periods of returns so I wouldn't try to fight that too much. If all else fails, do what your boss says.
Jun
20
comment Weighting several returns over different time frames
What's the goal of your analysis?
Jun
20
comment Controling ex-post volatility by ex-ante limits
If people ask, I just tell them that the tracking error limit is a ex ante guideline, rather than an ex post objective. Maybe not the best solution, but no one has complained. Also, what I referring to was whether the portfolio would have better performance with the ex post rule vs. the ex ante rule, not necessarily whether the ex post tracking bound would be contained (as I believed you that it would work as I had tried something similar before).
Jun
13
comment Controling ex-post volatility by ex-ante limits
What you're doing makes sense. I feel like I've done something similar before in my backtesting, but it seemed more complicated than just a regular constant ex ante limit, which works well enough. The bigger question is if there is an advantage to doing this or not.
Jun
12
comment Intuition behind interest rate models
See Section 3.1.2 symmys.com/sites/default/files/…
Jun
3
comment How do I do a mean variance optimization with constraints?
Before I do an optimization, I try to verify that the objective function, its derivatives, the constraints, and derivatives of constraints are all right. Beyond that, I don't use cvxopt so really can't provide more guidance.
Jun
2
comment How do I do a mean variance optimization with constraints?
Any upper or lower bound can be expressed by $A<b$. Just append an identity matrix to $A$ and whatever the upper bound is to $b$ $n$ times.
May
21
comment After PCA on original factors, how to tell which original factors are dominant?
math.nyu.edu/faculty/avellane/LalouxPCA.pdf