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14h
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.
16h
answered Weighting with restrictions, but no clear objective function?
16h
answered Where can I find a list of VaR and CVaR formulas for continuous distributions?
17h
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.
2d
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?
Sep
15
comment Exporting Time Series Data For Securities Prices From Bloomberg to Excel
Just get your firm to pay for the add-in.
Sep
9
comment How do Return.portfolio and Return.rebalancing work in Performance Analytics in R?
I do not see your motivating example in the PerformanceAnalytics pdf. The closest comparable thing I see is round(Return.rebalancing(edhec,weights),4). You'll note that the 2007-01-01 return matches up with edhec[121,1:11]%*%t(weights[8,]), ignoring the rounding.
Aug
29
answered Estimate correlation of time series whose histories differ in length
Aug
28
comment What kind of front end/ gui is used with trading applications?
Can you recommend a more thorough reference on the subject (preferably starting from the basics and working up)?
Aug
28
comment State Space models with Short Time Series
More to just get a sense if it's working the way that it should.