By Pierre Lequeux
ISBN-10: 0471981605
ISBN-13: 9780471981602
I am rather on knowing HOW hedge money like Renaissance alternate and stuff, yet considering that I dont comprehend complex math I dont be aware of if I can purchase this...
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Sample text
Another possible explanation for the poor performance of range-based estimators is misspecification of the underlying return-generating process. Range-based variance estimators are more sensitive to misspecification of the underlying process than classical estimators (Heynen and Kat, 1993). If the assumptionsof geometric Brownian motion are violated, estimators derived from the trading rangebewill adversely affected to a larger degree than close-to-close estimators. ISTORIC VOLATILITYUSING THE T R A ~ IRANGE ~G Methods of estimating historic volatility using the trading range of a security are described in this section.
157. 20 The efficiencyof low moment binomial forecasts is much higher than any of the quadratic estimators. 80. 82 mean intra-day estimate). This is not true of the CLOSE estimator, however, which measures about 10 percent more intra-day volatility than daily volatility. The normalized variance and Forecast MSEof all the estimators is lower for intra-day results than daily results, generally10-25 percent lower. This suggests intra-day data contains useful information about rthe e t u r n - ~ e n e r a process ~g that daily data do not contain.
Estimators based on low moments ou~erformedthe higher moment estimatorsby about 10 percentin terms of efficiency. The Mean Square Error of each estimatoris about twice the estimator variance, r i 0 0 0 € ~ c i e n t€ s t i ~ ~ t i oofnIntra-day VoZa~ilify 13 8 m m m o d ooco 14 Ric~ardB. Spurgin and ~ h Sckneeweis ~ ~ s an unsurprising result. If consecutive estimates are independent, the MSE will be twice the varianceof a single estimate. 16Twentydays of data are used in each estimate, so the sample size fordaily results is 20.
Financial Markets Tick By Tick by Pierre Lequeux
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