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Mar
3
comment Beta and the Assumption of IID Returns
This answer would be improved by an explanation of what iid means and how it relates to each part.
Mar
3
comment Fitting a sigmoid function to incomplete, structured, data
I'm not entirely sure that sigmoid is optimal in this case, but I'd have to know about what you're trying to do to be sure.
Mar
1
comment How to calculate modeled asset volatility by industry factor?
Try using a factor model?
Feb
28
comment What is the necessary level of Econometrics-Know-How for a quant
Census X12-ARIMA is also pretty popular for de-seasonalizing also.
Feb
27
comment What is the necessary level of Econometrics-Know-How for a quant
@Probilitator I added it as an answer and tried to expand some of the reasoning a little.
Feb
27
comment What is the necessary level of Econometrics-Know-How for a quant
I think that's a good list (though I never really used wavelets myself). I would add missing, mixed frequency, and irregular data as some issues that I'm constantly either dealing with or begrudgingly ignoring. Seasonal adjustment is important too for some types of analysis (like electricity futures), but I might combine that with the ARMA stuff. I would say that the reason not to focus too much on Panel Modelling is that you'd probably get stuck trying to remember random or fixed effects when instead you should just ignore those and read Gelman's Bayesian Data Analysis.
Feb
27
comment Sharpe Ratio, annualized monthly returns vs annual returns vs annual rolling returns?
The best advice I can give is to just do whatever your boss wants. Annualizing monthly returns might be more common, but there's nothing wrong with using yearly returns to calculate Sharpe ratios. Just don't do the first method.
Feb
26
comment Sharpe Ratio, annualized monthly returns vs annual returns vs annual rolling returns?
What you refer to a yearly return, others might refer to as a rolling 1-year return or a year over year (YoY) return. I can't recall anyone ever doing this to calculate Sharpe ratio over a full sample. It is more common to annualize monthly returns. I'm also a little confused on what you want the output to be. Do you want the Sharpe ratio for each year, a rolling Sharpe ratio, or over the whole sample?
Feb
26
comment What return equation is Engle referring to in his Nobel lecture?
Can you edit the title to be more informative?
Feb
23
comment How are quants able to verify whether their calculated prices are any good
When you say their calculated prices, you're referring to the values that are output from models (like pricing an option with BS), right, rather than the bid/ask prices quoted in the market?
Feb
21
comment Consensus on Cauchy distribution for stock prices
Those are important issues. I've tried truncated cauchy and stable as an alternative to their full versions, but I'm not familiar with tempered-stable.
Feb
20
comment Directional View of Volatility
en.wikipedia.org/wiki/Variance_swap
Feb
19
comment How do I simulate stock prices for a 10 asset portfolio, over a period of 10 years in MATLAB?
Use normrnd to simulate daily log returns, then convert to prices. Mvnrnd does the same simulation, but since you're dealing with a diagonal covariance matrix it just transforms it by the cholesky, which is the identity matrix. Note that this only means you simulate from a distribution with 0 correlations. It does not mean that the simulated correlation matrix will be an identity matrix. See this: mathworks.com/matlabcentral/fileexchange/…
Feb
11
comment Is the number of outstanding shares a stationary series?
Why not just make everything on a per share basis and avoid the issue?
Jan
31
comment Smoothing Term Curve
You might look into interpolation techniques that incorporate liquidity (assuming you can get the data). This would effectively put less weight on bonds that aren't being actively traded. Liquidity is an important consideration in volatility surfaces so you should be able to find some research on it. Alternately you can try a parsimonious model, like Nelson-Siegel (which there should be some questions about), and take deviations from that to identify outliers.
Jan
31
comment How to score a portfolio's diversity based on security returns?
I'm not exactly sure what you mean by diversity, but there's a (rather, at least one) question on average correlation. quant.stackexchange.com/questions/8689/…
Jan
29
comment Portfolio Optimization : Shrinkage of Covariance Matrix when data is available
You seem to be focused on shrinkage only to ensure the covariance matrix is positive definite. That's not the only reason to use shrinkage. Reduction of estimation error is another reason. My answer focused on the benefits of reducing estimation error.
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
24
comment What are DGTW adjusted returns?
@Anna you might want to incorporate that comment into the answer.
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)