Financial Econometrics Modeling: Market Microstructure, by Professor Greg N. Gregoriou, Professor Gregoriou Greg N.,

By Professor Greg N. Gregoriou, Professor Gregoriou Greg N., Razvan Pascalau

This e-book proposes new the way to construct optimum portfolios and to investigate marketplace liquidity and volatility below marketplace microstructure results, in addition to new monetary probability measures utilizing parametric and non-parametric ideas. specifically, it investigates the marketplace microstructure of foreign currency and futures markets.

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Extra resources for Financial Econometrics Modeling: Market Microstructure, Factor Models and Financial Risk Measures

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6, upper panel, the highest R2 is achieved by the subsampled AO estimator and by the Fourier estimator. When we include alternative forecasts besides the Fourier estimator in the regression, the R2 slightly increases, but the coefficients φ2 remain not significantly different from zero, while the coefficient estimates for φ1 are generally close to unity and significant at the 5 percent level. The last two regressions in the table provide coefficients which all significantly differ from zero and the highest R2 .

Gregoriou and Razvan Pascalau GREGORIOU-2: “CHAP01” — 2010/11/22 — 17:39 — PAGE 8 — #8 Covariance Estimation and Dynamic Asset-Allocation 9 In the sequel we assume that the observed prices are affected by “microstructure noise” in the form p˜ i (t) = pi (t) + ηi (t) i = 1, . . 8) where pi (t) is the efficient log-price process and ηi (t) is the microstructure noise. We can think of pi (t) as the log-price in equilibrium, that is, the price that would prevail in the absence of market microstructure frictions.

Engle, R. and Colacito, R. (2006) “Testing and Valuing Dynamic Correlations for Asset Allocation,” Journal of Business & Economic Statistics, 24 (2): 238–253. Greg N. Gregoriou and Razvan Pascalau GREGORIOU-2: “CHAP01” — 2010/11/22 — 17:39 — PAGE 30 — #30 Covariance Estimation and Dynamic Asset-Allocation 31 Epps, T. (1979) “Comovements in Stock Prices in the Very Short Run,” Journal of the American Statistical Association, 74 (366): 291–298. , Kirby, C. and Ostdiek, B. (2001) “The Economic Value of Volatility Timing,” The Journal of Finance, LVI (1): 329–352.

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