nep-mst New Economics Papers
on Market Microstructure
Issue of 2009‒12‒05
three papers chosen by
Thanos Verousis
Swansea University

  1. Jump-Robust Volatility Estimation using Nearest Neighbor Truncation By Torben G. Andersen; Dobrislav Dobrev; Ernst Schaumburg
  2. The Relationship Between the Volatility of Returns and the Number of Jumps in Financial Markets By Álvaro Cartea; Dimitrios Karyampas
  3. Price Discovery, Causality and Volatility Spillovers in European Union Allowances Phase II: A High Frequency Analysis By Rittler, Daniel

  1. By: Torben G. Andersen (Northwestern Univ., NBER, CREATES); Dobrislav Dobrev (Federal Reserve Board of Governors); Ernst Schaumburg (Federal Reserve Bank of New York)
    Abstract: We propose two new jump-robust estimators of integrated variance based on highfrequency return observations. These MinRV and MedRV estimators provide an attractive alternative to the prevailing bipower and multipower variation measures. Specifically, the MedRV estimator has better theoretical efficiency properties than the tripower variation measure and displays better finite-sample robustness to both jumps and the occurrence of “zero” returns in the sample. Unlike the bipower variation measure, the new estimators allow for the development of an asymptotic limit theory in the presence of jumps. Finally, they retain the local nature associated with the low order multipower variation measures. This proves essential for alleviating finite sample biases arising from the pronounced intraday volatility pattern which afflict alternative jump-robust estimators based on longer blocks of returns. An empirical investigation of the Dow Jones 30 stocks and an extensive simulation study corroborate the robustness and efficiency properties of the new estimators.
    Keywords: High-frequency data, Integrated variance, Finite activity jumps, Realized volatility, Jump robustness, Nearest neighbor truncation
    JEL: C14 C15 C22 C80 G10
    Date: 2009–10–31
  2. By: Álvaro Cartea; Dimitrios Karyampas (Department of Economics, Mathematics & Statistics, Birkbeck)
    Abstract: The contribution of this paper is two-fold. First we show how to estimate the volatility of high frequency log-returns where the estimates are not affected by microstructure noise and the presence of Lévy-type jumps in prices. The second contribution focuses on the relationship between the number of jumps and the volatility of log-returns of the SPY, which is the fund that tracks the S&P 500. We employ SPY high frequency data (minute-by-minute) to obtain estimates of the volatility of the SPY log-returns to show that: (i) The number of jumps in the SPY is an important variable in explaining the daily volatility of the SPY log-returns; (ii) The number of jumps in the SPY prices has more explanatory power with respect to daily volatility than other variables based on: volume, number of trades, open and close, and other jump activity measures based on Bipower Variation; (iii) The number of jumps in the SPY prices has a similar explanatory power to that of the VIX, and slightly less explanatory power than measures based on high and low prices, when it comes to explaining volatility; (iv) Forecasts of the average number of jumps are important variables when producing monthly volatility forecasts and, furthermore, they contain information that is not impounded in the VIX.
    Date: 2009–11
  3. By: Rittler, Daniel
    Abstract: This paper deals with the modeling of the relationship of European Union Allowance spot- and futures-prices within the second commitment period of the European Union Emission Trading Scheme. Based on high frequency data, we analyze causality in the first and the second conditional moments. To reveal long run price discovery we compute the common factor weights proposed by Schwarz and Szakmary (1994) and the information share proposed by Hasbrouck (1995) based on the estimated coefficients of a vector error correction model. To analyze the short run dynamics we perform Granger causalty tests. The GARCH-BEKK model introduced by Engle and Kroner (1995) is employed to analyze the volatility transmission structure. We identify the futures market to be the leader of the long run price discovery process whereas a bidirectional short run causality structure is observed. Furthermore we detect unidirectional volatility transmission from the futures to the spot market at highest frequencies.
    Keywords: CO2 Emission Allowances; Causality; Volatility Transmission; Spot Prices; Futures Prices
    Date: 2009–11–25

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