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Oct
27
comment Portfolio Optimization using S&P Universes
This question might be a bit too general to be able to answer. It might be improved by discuss within the context of a particular optimization or factor model.
Oct
27
comment How is stock data objectively different to this random walk?
You can have a random walk with a non-normal distribution. However, if the non-normal distribution is the result of some underlying process (like regimes per @vonjd or stochastic volatility), then it would not be a random walk anymore.
Oct
26
revised Statistical arbitrage using eigen portfolios
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Oct
26
comment Statistical arbitrage using eigen portfolios
If you were implementing Section 5.3-4 in practice, then yes, you'd net things out across all the different arb trades you're making and betas on each portfolio to have to figure out how much of each stock to buy.
Oct
24
answered Statistical arbitrage using eigen portfolios
Oct
22
comment Where can I find a list of VaR and CVaR formulas for continuous distributions?
Other than the one posted by @YuliaV, I'm not aware of any papers like that off the top of my head. In practice, I just don't use the analytic formula often (really only for normal VaR). Not sure how common that is for others.
Oct
22
answered Weighting with restrictions, but no clear objective function?
Oct
22
answered Where can I find a list of VaR and CVaR formulas for continuous distributions?
Oct
22
comment Where can I find a list of VaR and CVaR formulas for continuous distributions?
I disagree with your assertion that CVaR is not a commonly used term. They are interchangeable, as far as I'm concerned.
Oct
20
answered Testing the validity of a factor model for stock returns
Oct
16
comment Expected Shortfall (CVaR) Backtesting
@emcor I had meant simply using the historical CVaR for the purposes of the backtest, rather than rely on any assumptions about the distribution of returns for the strategy. If you want a confidence interval on the ES, you can bootstrap from the historical returns. I've seen some literature on expectiles, but I haven't had the chance to read it yet.
Oct
7
answered “Adding” risk-free asset to covariance matrix after the fact
Oct
3
comment Portfolio Turnover Constraint
@Richard It's not just them being positive, it's the piecewise nature of the constraint. Optimizers that require continuous functions will tend to not like it when you use absolute values. Also, this approach can easily be extended to include transaction costs, though you probably need to add in non-linear constraints $b_{i}s_{i}=0$ to ensure that sells are zero if you have buys, and vice-versa. My recollection is that it's not usually needed for turnover, but there might be cases where it is.
Sep
30
comment How to interpret ACF and PACF plots
I don't see anything interesting in these. Looks stationary.
Sep
30
awarded  Explainer
Sep
29
answered What are the most effective market variables to measure liquidity/illiquidity in the market?
Sep
25
comment Factor model assumptions
Alternately, consider a model like Barra where you use cross-sectional regression. The $B$ term changes in every period, but you can still use that formula to decompose the covariance of $X$.
Sep
25
comment Factor model assumptions
Suppose you regress every stock in $X$ against the Fama-French factors (so this is a time series factor model). If you assume constant 2nd moment, then you can do the covariance matrix of $X$ as is normal for factor models. If you assume Garch volatility for $F$ with constant correlation and assumptions as above for idiosyncratic returns, then you can still use that formula, but you have to adjust it to be a conditional covariance.
Sep
25
answered Factor model assumptions
Sep
17
answered Is this a reasonable approach to determine the relative importance of valuation factors?