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Aug
9
comment Average correlation of index/portfolio
If I use the method c in that first link, then I get a correlation below 1. I don't know if that method has other issues, though.
Aug
9
comment Average correlation of index/portfolio
When I find the eigenvalues for your proposed correlation matrix, I get a negative value for the smallest. This suggests your choice is not positive definite and thus not a valid correlation matrix. Setting $\rho_{2,3}=0.89$ would result in all positive eigenvalues, but I can confirm that the average correlation by this formula would be greater than 1. So your problem remains.
Aug
8
comment Average correlation of index/portfolio
For the first question, I tried some extreme weights (adding up to 500% or 0%) and did not see any incorrect average correlations (I may have used a modification of that formula because that didn't seem correct). The main reason is that so long as $\sigma^{2}$ is the correct portfolio variance, then the average correlation should be within normal bounds. For the second point, I'm not familiar with anyone writing about it, but you could presumably take a similar approach using the above formula as they do for contribution to variance (I would not take the absolute value).
Aug
7
comment what is a reasonable beta in CAPM?
The point I was trying to make is that I might set it up as the 95th (& 5th) or 99th (& 1st) percentile, or something like that, rather than selecting fixed values. Where to cut it off might be different for different periods of time or different markets or different groups of securities. I'd rather look to the data than make any arbitrary assumptions.
Aug
6
comment what is a reasonable beta in CAPM?
One option would be to winsorize all the betas above or below some quantiles. Alternately, you could model the beta itself as mean-reverting so that the extreme betas gradually go back to 1.
Aug
5
comment Why are indifference equations in mean-variance portfolio theory convex shaped
Do you mean utility function?
Aug
2
comment Trend in Cointegration relationship
@MattWolf That is useful, but I think his problem is more basic, related to the choices he is making in variables. For instance, if you are using the relative inflation rates versus the price levels, then you may or may not have needed to use include the trend term.
Aug
1
answered Derivation of the tangency (maximum Sharpe Ratio) portfolio in Markowitz Portfolio Theory?
Jul
31
comment Real value of small numbers of shares of company stock
What I meant by there not being an objective value is that prices are not determined with reference to some objective value. Saying life has value is a different sort of value than what economists mean usually. If you wanted to sell me water, then the subjective value is very important. If I am in the city, I may not pay more than 1 dollar for a bottle. If I am in the desert and low on supplies but have lots of money, I might pay 500 dollars. What matters is the expected amount of subjective value an additional unit will give me (aka marginal utility).
Jul
31
comment Real value of small numbers of shares of company stock
According to economics, there is no such thing as "real inherent value", aka objective value. There is, however, subjective value, which is why we care about the value of a company being what someone else will pay for it. In your example, people will want to buy XCo because they think its stock price will go up.
Jul
25
comment Shrinkage Estimator for Newey-West Covariance Matrix
You may want to add the link to the preprint in the question. I still am curious as to what is the issue with simply replacing the sample estimate with the Newey West estimate. Anyway, the original paper implies that it is estimated through GMM rather than Maximum Likelihood. I would have suggested finding the Bayesian prior that would be equivalent to whatever shrinkage you want to make and then adopting the approach for the Newey-West estimator, but since it is not based on ML I'm not sure if that would work.
Jul
25
comment Shrinkage Estimator for Newey-West Covariance Matrix
My understanding of Newey-West estimators is that it is used to calculate the covariance matrix of parameters in a regression. I could imagine using it in a robust portfolio optimization (concerned with uncertainty in the mean parameters), but whether it makes sense to use it for estimating the covariance of returns, I don't know. That being said, why are you not able to simply replace the sample covariance in the shrinkage formula with your new Newey-West estimate?
Jul
10
comment Counterintuitive time varying Beta with Kalman filter
I don't quite understand what you're talking about with respect to the $\beta_{t}$ being bigger than zero if $\beta$ is less than zero. Why don't you try to create a data generating process that involves a time-varying $\beta_{t}$ and then run your code on that to see how good it does. I've only ever programmed my own Kalman Filters so I can't say whether you're using the KFAS package correctly or not. It's not terribly challenging and you could use that to help confirm if that's causing a problem with your code.
Jul
10
comment How to make a historical index of a group of materials in which the set of materials changes every month?
Agree with Alexey and Imorin. Would also add that this sounds like an inventory question also, which implies that there are accounting rules on it.
Jul
9
answered Determining the portfolio return distribution to calculate CVaR/ES
Jun
25
answered Principle Component Analysis vs. Cholesky Decomposition for MonteCarlo
Jun
19
comment How to calculate the conditional variance of a time series?
Assuming the Garch model is the same as the one from the paper and the data is the same (and same frequency), I would expect them to look very similar. One difference is that most packages initialize the conditional variance with the long-run variance, so that's one area I would check but if you used the sample variance to initialize though the difference should be small.
Jun
18
comment How to calculate the conditional variance of a time series?
Most Garch packages will output the conditional variances for you. For the centered returns, you could estimate an autoregressive model and subtract out the conditional mean. They are assuming a constant mean, which is also fine.
Jun
12
revised Are minimum-risk and minimum-variance portfolios equivalent?
added 19 characters in body
Jun
12
answered Are minimum-risk and minimum-variance portfolios equivalent?