CH19 estimating volatilities and correlations

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CH19 estimating volatilities and correlations

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. Estimating Volatilities and Correlations Chapter 20 Standard Approach to Estimating Volatility (page 461)  Define σ n as the volatility per day between day n-1 and day n, as estimated. (Table 19.1, page 469)  Start with trial values of ω, α, and β  Update variances  Calculate  Use solver to search for values of ω, α, and β that maximize this objective function  Important. =1 2 1 2 1 2 −− βσ+α+γ=σ nnLn uV GARCH (1,1) continued Setting ω = γV the GARCH (1,1) model is and β−α− ω = 1 L V 2 1 2 1 2 −− βσ+α+ω=σ nnn u Example (Example 19.2, page 465)  Suppose  The

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Mục lục

  • Slide 1

  • Standard Approach to Estimating Volatility (page 461)

  • Simplifications Usually Made (page 462)

  • Weighting Scheme

  • ARCH(m) Model (page 463)

  • EWMA Model

  • Attractions of EWMA

  • GARCH (1,1) page 465

  • GARCH (1,1) continued

  • Example (Example 19.2, page 465)

  • Example continued

  • GARCH (p,q)

  • Maximum Likelihood Methods

  • Example 1

  • Example 2

  • Application to GARCH

  • Excel Application (Table 19.1, page 469)

  • Variance Targeting

  • How Good is the Model?

  • Forecasting Future Volatility (equation 19.3, page 472)

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