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Are your 407 stocks all different? No A and B listings contained that are strongly if not perfectly correlated? The observation that the daily covariance matrix is singular makes me wonder. You can try the package corpcor for another shrinkage estimator.


You need the "adjusted high". However, Yahoo Finance does not provide that: https://help.yahoo.com/kb/SLN2311.html However you can adjust manually. From the Normal Close and the Adjusted Close just compute the adjustment factor and then manually adjust the High.


You're setting an option, not an override. Your code works fine if you replace names(overrides.px) = "periodicity" px = bdh(securities = indices,fields = "px_last",start.date = start.dt,end.date = end.dt, overrides = overrides.px) with names(overrides.px) = "periodicitySelection" px = bdh(securities = indices,fields = "px_last",start.date = ...


At first we considered it to be a bug where the overrides does not propagate correctly. Edit: Here is a corrected examples, thanks to @Sid. Setting it as an options field works: library(Rblpapi) blpConnect() ## initalize data import end.dt <- Sys.Date() start.dt <- end.dt - 100 # keep it simple for example index.growth <- "MXUS000G Index" ...


You can write $$\mathbb{E}\left[ \max(a X_T + b X_S -K,0)\right] = \mathbb{E}\left[ \max(a X_S Y_{S,T} + b X_S -K,0)\right],$$ with $Y_{S,T} = X_T/X_S.$ For a given value of $X_S$ we can write $$\mathbb{E}\left[ \max(a X_S Y_{S,T} + b X_S -K,0)\right] = X_S \mathbb{E}\left[ \max(a Y_{S,T} + b -K/X_s,0)\right],$$ since $Y_{S,T}$ is log-normal this can ...

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