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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
answered What is the necessary level of Econometrics-Know-How for a quant
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
26
revised What return equation is Engle referring to in his Nobel lecture?
added 154 characters in body
Feb
26
revised Time-Varying Volatility and Conditional Likelihood
edited title
Feb
25
answered Time-Varying Volatility and Conditional Likelihood
Feb
25
revised Time-Varying Volatility and Conditional Likelihood
added 105 characters in body
Feb
24
revised Pricing options with two assets
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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
21
answered how to back out levels from a forecast of differenced series
Feb
21
revised how to back out levels from a forecast of differenced series
Adding in some Tex and making it a big more readable.
Feb
20
answered Model Validation Criteria
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?