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VOLATILITY FORECASTING. Steven Poher Ramzi Rached Ricardo Uribe Dongting Zheng. Global Investment Management. AGENDA. Objective Background Information Forecasting Models Data set Methodology Results Conclusion. OBJECTIVE. Objective To establish a variance forecasting model Why? - PowerPoint PPT Presentation

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  • VOLATILITY FORECASTINGSteven PoherRamzi RachedRicardo UribeDongting Zheng

    Global Investment Management

  • AGENDAObjective Background InformationForecasting ModelsData setMethodologyResultsConclusion

  • OBJECTIVEObjectiveTo establish a variance forecasting model

    Why?Important for risk managers (VaR)Used to price optionsVolatility + Return = investment decision

  • BACKGROUND INFORMATIONRealized / observed volatility is measured by squared returnsVolatility displays a positive correlation with its own past

    Simple Model

    PB : Equal weights on the past m observations

  • FORECASTING MODELSMore flexible model Simple GARCH or GARCH (1,1)

    Extended to Local and Global Instruments

    Models to be tested for this projectGARCH (1,1)GARCH (1,1) + LocalGARCH (1,1) + GlobalGARCH (1,1) + Local + Global

  • DATA SETSourceDataStreamPeriod3/27/1998 - 3/28/2008 (10 years)Granularity1 day

    CountryIndexNIKKEI 225CAC 40DAX 30FTSE 100S&P 500

  • DATA SETLocal InstrumentsChange in Exchange RatesEUR / USD / JPY / GBPChange in short-term interest ratesT-Bill (US) / BTAN (FR)

    Global InstrumentsChange in Short-term Eurodollar rateChange in the Term Structure spread

  • METHODOLOGYUsing EXCEL, test our 4 models for each of our 5 markets

    Use Maximum Likelihood Estimation (MLE) to estimate / / / EXCEL Solver

    Test the models using a regression of Squared Returns vs. Forecasted Variance

    Discuss the statistical significance of the regression / Select the best model for a given country

  • METHODOLOGY - EXAMPLE

  • RESULTSBest models for each country

    CountryModelR2GARCH + % Change in Term Structure Spread (G)1.21 %GARCH + % Change in / (L)14.12 %GARCH + % Change in / (L) + % Change in Term Structure Spread (G)15.56 %GARCH (1,1) + % Change in $/ (L) + % Change in ST Eurodollar (G)14.23 %GARCH10.58 %

  • RESULTSBest model for German MarketR2 of 15.56%Final equationSimple GARCH + % Change in / Exchange (L) +% Change in Term Structure Spread (G)

  • RESULTS

  • CONCLUSIONNo universal modelDifferent countries = different modelsGood proxy for DE / Bad for JP

    GARCH could also be extendedLeverage effectsDay-of-week effectsJumps

    Economic intuition & reality check

  • QUESTIONS?THANK YOU

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