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In the Merton jump diffusion model, the stock price process consists of a continuous part and a discrete part (this one represents the jumps). While deriving the PDE for the riskless portfolio and imposing the riskless evolution, the discrete part can't be instantaneously hedged. In fact, you can assume that the effects of jumps can be nullified on average, ...


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It does create a see-saw. This can be reduced by having it charge a slightly bigger spread, which gets contributed to b. In this way, b effectively becomes a market making fund, and volatility decreases as trade volume increases. This makes the LMSR market maker liquidity sensitive. This makes the market more efficient as spreads decrease over time as ...


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All the Fama-French data is downloadable here: http://mba.tuck.dartmouth.edu/pages/faculty/ken.french/data_library.html and in particular, daily RMRF, SMB and HML data can be downloaded here: http://mba.tuck.dartmouth.edu/pages/faculty/ken.french/ftp/F-F_Research_Data_Factors_daily.zip


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Looking for the same issue, I found an article by de Jong(1997). In section 2 you can find a method for estimation of covariances and correlations between irregularly spaced data. Also look at the article by Jonas Andersson where some interpolation methods and method form de Jong are presented and compared together. Hope it helps.



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