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Jan
27
comment Where do these Orders come from and what do they mean?
@JoshuaUlrich, I feel this is related to market structure, which is on topic.
Jan
27
accepted Strategies for Liar's Poker
Jan
24
revised What are DGTW adjusted returns?
added 1 characters in body
Jan
24
comment What are DGTW adjusted returns?
@Anna you might want to incorporate that comment into the answer.
Jan
24
reviewed Approve suggested edit on What are DGTW adjusted returns?
Jan
24
comment Estimation of Empirical Expected Shortfall of a heavy tailed distribution
I've been confused by this question since when I estimate the empirical ES/CVaR, I normally don't simulate anything. For instance, for a portfolio of equities, I would use the current portfolio (with some assumption about rebalancing) with the historical returns and then follow the above formulas to get the ES. Are you concerned with securities that wouldn't have historical returns in the same way, like exotic options? (so then you simulate the returns for those conditional on everything else, and calculate the distribution of ES)
Jan
21
comment Co-integration constraints of coint(X,Z) given coint(X,Y) and coint(Y,Z)?
That's where I got stuck on too.
Jan
21
reviewed Reject suggested edit on How can I go about applying machine learning algorithms to stock markets?
Jan
21
comment Co-integration constraints of coint(X,Z) given coint(X,Y) and coint(Y,Z)?
I think doing some kind of simulation might help clarify things, but I'm not sure how to get an analytical answer.
Jan
21
comment Co-integration constraints of coint(X,Z) given coint(X,Y) and coint(Y,Z)?
You prove there is multiple cointegration, but I'm not sure if that necessarily implies cointegration for the third pair. I looked for papers to check if 2 pair-wise cointegrations imply cointegration on the third pair, but didn't find anything. Typically Johansen's test is what you use to test for multiple cointegration. In practice, I don't really spend much time worrying about these issues as I can always just estimate whatever relationships I want.
Jan
17
comment Inflation modelling
With respect to Richard's point, the European HICP inflation data all comes out NSA (non-seasonally adjusted). I checked and the Spanish data from INE is also NSA. You just have to be careful because other countries might provide the SA data (like the US does). Spanish prices are typically weak in winter before recovering in the spring.
Jan
16
revised Normality assumption in Sharpe ratio
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Jan
9
comment How can I calculate the Cumulant-Generating Function in Matlab?
Meucci might have code that does this. mathworks.com/matlabcentral/fileexchange/authors/21105
Jan
6
comment Optimizing Principal Component factor weightings over time
If you have a time-varying covariance matrix (you could construct with Garch volatility and either a constant or time-varying dependence structure), then you can perform PCA on each period or project out to the future. Not sure if that's what you're looking to do.
Jan
6
comment Expected Shortfall (CVaR) Backtesting
Why don't you just try a backtest and to calculate ES and see if it works? I use CVaR all the time in backtests, though I mostly do it with monte carlo simulations.
Jan
6
comment Lagged dependent variable, yes or no?
I probably would probably first emphasize the calculation of standard errors in the presence of autocorrelation before anything like omitted variable bias.
Dec
20
comment How to group timeseries showing similar curve
Do you ever throw in regression coefficients, like regression against indices (including sector/industries)?
Dec
12
comment Optimization: Factor model versus asset-by-asset model
However, if the weight constraints are too restrictive, then it might not work as you'd like.
Dec
12
comment Optimization: Factor model versus asset-by-asset model
I'm not so sure that I've read that portfolio optimization on $\widehat{\Sigma}$ is "easier" than the optimization on $\Sigma$. You're still working with an $N\times N$ matrix, but you've ensured that it is positive definite (which is a good thing). You could always generate some random data and test the idea. It might be possible to set up the optimization in terms of principal portfolios so you're only operating on the first few $K$ principal portfolios and then translating those weights back into normal weights for constraints and TC.
Dec
12
comment What is Quantitative Investing and how does it differ from Quantitative Trading?
Most of the quant AUM is long-only (even if they build long-short factor models internally). In my view the quant managers have better risk control than many other active managers. The good ones can achieve comparable alpha with lower tracking error, giving them higher information ratios. Also, my understanding is that the fees are typically lower for quant managers than other active managers.