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1d
comment What kind of front end/ gui is used with trading applications?
Can you recommend a more thorough reference on the subject (preferably starting from the basics and working up)?
1d
comment State Space models with Short Time Series
More to just get a sense if it's working the way that it should.
1d
comment State Space models with Short Time Series
I was focusing on the estimation. Combining that with testing a trading strategy will introduce more complexity. No one right answer, I think. One thing I do sometimes is assume the model is true, then simulate a bunch of paths of data, and then run the trading strategy on simulated data and evaluate it way on the larger sample. Not sure if that makes sense in your case, because I'm really not sure what you're doing.
1d
comment Fixed volatility portfolio with max returns creates skewed results
Yes, it is possible. Assuming you did the non-linear constraint correctly, it could be that with four assets it can't find an optimal portfolio with volatility that low. There are too many potential things it could be to say for sure. Some other tips, draw the efficient frontier (that way you can get a sense of the minimum risk and maximium return portfolios) or switch it around and minimize risk given return (and maybe also draw that frontier).
2d
comment Fixed volatility portfolio with max returns creates skewed results
It is likely an error that can only be evaluated by looking at the code. For instance, it could be that you programmed the non-linear constraint wrong, or it could be that your linear and non-linear constraints are inconsistent somehow. One piece of advice: start with a very simple optimization and gradually make it more complicated, verifying at each stage that you're getting sensible results.
Aug
26
comment State Space models with Short Time Series
Without having a better sense of what you're trying to do, things I would try are 1) increasing frequency of data, 2) leave one out cross validation, 3) Bayesian methods.
Aug
18
comment factor models and using cross section regression
@Viquar I'm more familiar with the approach in that paper as applied to momentum than I am with respect to characteristics-based factors (e.g. P/E). In a cross-sectional approach (as in Barra), one can use a GLS approach to account for the correlation between factors, though I'm not sure how important it is for the level of coefficients versus standard errors.
Aug
12
comment Why maximize expected growth rate?
@RRL Wrt to your first paragraph, it might make it a bit more clear to say that Kelly is maximizing the log of wealth, which is equivalent to saying utility is the log of wealth.
Aug
6
comment Johansen Cointegration Test
@user3126171 So perhaps your problem is that you don't understand cointegration or the Johansen test, rather than necessarily how it is implemented in Matlab. As I said, the Spatial Econometrics toolbox manual is very clear about what the Johnansen test means spatial-econometrics.com/html/mbook.pdf Otherwise, most books on time series econometrics tend to cover it. You can also just google johansen test and there are many results that explain it.
Aug
6
comment Johansen Cointegration Test
Honestly, I tend to use the one in the Spatial Econometrics toolbox (its manual is a bit clearer, though there's a link at the bottom of the Matlab link I have above that provides more details). The Matlab test is testing r=0, r=1, i.e. whether the number of cointegrating relationships is some number. The test rejects r=0, so you can say there is one cointegrating relationship.
Jul
31
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.
Jul
31
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.
Jul
29
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
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
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).