Download A Practical Guide to Forecasting Financial Market Volatility by Ser-Huang Poon PDF

By Ser-Huang Poon

Monetary marketplace volatility forecasting is one in every of brand new most vital components of craftsmanship for execs and teachers in funding, alternative pricing, and fiscal industry rules. whereas many books tackle monetary industry modelling, no unmarried publication is dedicated basically to the exploration of volatility forecasting and the sensible use of forecasting types. a pragmatic consultant to Forecasting monetary industry Volatility presents functional assistance in this very important subject via an in-depth exam of a number of renowned forecasting types. info are supplied on confirmed innovations for development volatility versions, with guide-lines for truly utilizing them in forecasting purposes.

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In the latter case, pricing error in the option model will be cancelled out when the option implied volatility is reintroduced into the pricing formula. So it is not surprising that evaluation which involves comparing option pricing errors often prefers the implied volatility method to all other time series methods. Research in financial market volatility has been concentrating on modelling and less on forecasting. Work on combined forecast is rare, probably because the groups of researchers in time series models and option pricing do not seem to mix.

For j period) is taken to be the sum of individual multi-step point forecasts sj=1 h T + j|T . These multi-step point forecasts are produced by recursive substitution and using the fact that εT2 +i|T = h T +i|T for i > 0 and εT2 +i|T = εT2 +i for T + i ≤ 0. g. ) and the forecast horizon. If returns are iid (independent and identically distributed, or strict white noise), then variance of returns over a long horizon can be derived as a simple multiple of single-period variance. 2. 7 Complication in relation to the choice of forecast horizon is partly due to volatility mean reversion.

3 Historical Volatility Models Compared with the other types of volatility models, the historical volatility models (HIS) are the easiest to manipulate and construct. The wellknown Riskmetrics EWMA (equally weighted moving average) model from JP Morgan is a form of historical volatility model; so are models that build directly on realized volatility that have became very popular in the last few years. Historical volatility models have been shown to have good forecasting performance compared with other time series volatility models.

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