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on Market Microstructure |
| By: | David E. Allen (School of Accounting, Finance and Economics, Edith Cowan University); Michael McAleer (Erasmus University Rotterdam, Tinbergen Institute, The Netherlands, and Institute of Economic Research, Kyoto University); Marcel Scharth (Tinbergen Institute, The Netherlands, Department of Econometrics, VU University Amsterdam) |
| Abstract: | In this paper we show that realized variation measures constructed from high- frequency returns reveal a large degree of volatility risk in stock and index returns, where we characterize volatility risk by the extent to which forecasting errors in realized volatility are substantive. Even though returns standardized by ex post quadratic variation measures are nearly Gaussian, this unpredictability brings greater uncertainty to the empirically relevant ex ante distribution of returns. Explicitly modeling this volatility risk is fundamental. We propose a dually asymmetric realized volatility model, which incorporates the fact that realized volatility series are systematically more volatile in high volatility periods. Returns in this framework display time varying volatility, skewness and kurtosis. We provide a detailed account of the empirical advantages of the model using data on the S&P 500 index and eight other indexes and stocks. |
| Keywords: | Realized volatility, volatility of volatility, volatility risk, value-at-risk, forecasting, conditional heteroskedasticity. |
| Date: | 2010–12 |
| URL: | http://d.repec.org/n?u=RePEc:kyo:wpaper:753&r=mst |
| By: | Ahoniemi, Katja (Aalto University School of Economics); Lanne, Markku (University of Helsinki) |
| Abstract: | No consensus has emerged on how to deal with overnight returns when calculating realized volatility in markets where trading does not take place 24 hours a day. This paper explores several common volatility applications, investigating how the chosen treatment of overnight returns affects the results. For example, the selection of the best volatility forecasting model depends on the way overnight returns are incorporated into realized volatility. The evidence favours weighted estimators over those that have been more commonly used in the existing literature. The definition of overnight returns is particularly challenging for the S&P 500 index, and we propose two alternative measures for its overnight return. |
| Keywords: | realized volatility; forecasting |
| JEL: | C14 C22 C52 |
| Date: | 2010–12–08 |
| URL: | http://d.repec.org/n?u=RePEc:hhs:bofrdp:2010_019&r=mst |
| By: | Silvia Centanni (Department of Economics (University of Verona)); Marco Minozzo (Department of Economics (University of Verona)) |
| Abstract: | To model intraday stock price movements we propose a class of marked doubly stochastic Poisson processes, whose intensity process can be interpreted in terms of the effect of information release on market activity. Assuming a partial information setting in which market agents are restricted to observe only the price process, a filtering algorithm is applied to compute, by Monte Carlo approximation, contingent claim prices, when the dynamics of the price process is given under a martingale measure. In particular, conditions for the existence of the minimal martingale measure Q are derived, and properties of the model under Q are studied. |
| Keywords: | Minimal martingale measure, News arrival, Marked point process, Nonlinear filtering, Reversible jump Markov chain Monte Carlo, Ultra high frequency data |
| JEL: | C01 C15 G12 G13 |
| Date: | 2010–12 |
| URL: | http://d.repec.org/n?u=RePEc:ver:wpaper:22/2010&r=mst |
| By: | Jørgensen, Kjell (Norwegian School of Management BI); Valseth, Siri (University of Stavanger) |
| Abstract: | . |
| Keywords: | . |
| JEL: | G10 G30 |
| Date: | 2010–12–17 |
| URL: | http://d.repec.org/n?u=RePEc:hhs:stavef:2010_011&r=mst |