By Ser-Huang Poon
Monetary industry volatility forecasting is one in all latest most vital components of workmanship for pros and lecturers in funding, choice pricing, and fiscal industry rules. whereas many books handle monetary marketplace modelling, no unmarried ebook is dedicated essentially to the exploration of volatility forecasting and the sensible use of forecasting versions. a realistic advisor to Forecasting monetary industry Volatility offers sensible assistance in this very important subject via an in-depth exam of a number well known forecasting versions. info are supplied on confirmed options for construction volatility versions, with guide-lines for truly utilizing them in forecasting functions.
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Additional resources for A Practical Guide to Forecasting Financial Market Volatility
A decision maker might be more risk-averse towards the larger errors. 1 the impact of using squared returns to proxy daily volatility. Hansen and Lunde (2004b) used a series of simulations to show that ‘. . the substitution of a squared return for the conditional variance in the evaluation of ARCH-type models can result in an inferior model being chosen as [the] best with a probability converges to one as the sample size increases . . ’. Hansen and Lunde (2004a) advocate the use of realized volatility in forecast evaluation but caution the noise introduced by market macrostructure when the intraday returns are too short.
2588, which means that εt2 is 50% greater or smaller than σt2 nearly 75% of the time! √ √ If rt ∼ N 0, σt2 , then E (|rt |) = σt 2/π. Hence, σ t = |rt |/ 2/π if rt has a conditional normal distribution. 4 For example, the maximum likelihood method proposed by Ball and Torous (1984), the high–low method proposed by Parkinson (1980) and Garman and Klass (1980). 4) are generated by a GARCH(1,1) process, Andersen and Bollerslev (1998) show that the population R 2 for the regression εt2 = α + βσ 2t + υt is equal to κ −1 where κ is the kurtosis of the standardized residuals and κ is ﬁnite.
The pricing model relies on a riskless hedge to be followed through until the option reaches maturity. Therefore the required volatility input, or the implied volatility derived, is a cumulative volatility forecast over the option maturity and not a point forecast of volatility at option maturity. The interest in forecasting σ t,T | t−1 goes beyond the riskless hedge argument, however. Volatility Deﬁnition and Estimation 17 weekly or monthly data is better because volatility mean reversion is difﬁcult to adjust using high frequency data.