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on Market Microstructure |
| By: | Alvaro Cartea; Dimitrios Karyampas |
| Abstract: | Using high frequency data for the price dynamics of equities we measure the impact that market microstructure noise has on estimates of the: (i) volatility of returns; and (ii) variance-covariance matrix of n assets. We propose a Kalman-filter-based methodology that allows us to deconstruct price series into the true efficient price and the microstructure noise. This approach allows us to employ volatility estimators that achieve very low Root Mean Squared Errors (RMSEs) compared to other estimators that have been proposed to deal with market microstructure noise at high frequencies. Furthermore, this price series decomposition allows us to estimate the variance covariance matrix of $n$ assets in a more efficient way than the methods so far proposed in the literature. We illustrate our results by calculating how microstructure noise affects portfolio decisions and calculations of the equity beta in a CAPM setting. |
| Keywords: | Volatility estimation, High-frequency data, Market microstructure theory, Covariation of assets, Matrix process, Kalman filter |
| JEL: | G12 G14 C22 |
| Date: | 2009–12 |
| URL: | http://d.repec.org/n?u=RePEc:cte:wbrepe:wb097609&r=mst |
| By: | Chun Liu; John M Maheu |
| Abstract: | We propose a new joint model of intraday returns and durations to study the dynamics of several Chinese stocks. We include IBM from the U.S. market for comparison purposes. Flexible innovation distributions are used for durations and returns, and the total variance of returns is decomposed into different volatility components associated with different transaction horizons. Our new model strongly dominates existing specifications in the literature. The conditional hazard functions are non-monotonic and there is strong evidence for different volatility components. Although diurnal patterns, volatility components, and market microstructure implications are similar across the markets, there are interesting differences. Durations for lightly traded Chinese stocks tend to carry more information than heavily traded stocks. Chinese investors usually have longer investment horizons, which may be explained by the specific trading rules in China. |
| Keywords: | market microstructure, transaction horizon, high-frequency data, ACD, GARCH |
| JEL: | C22 C11 G10 |
| Date: | 2010–04–06 |
| URL: | http://d.repec.org/n?u=RePEc:tor:tecipa:tecipa-401&r=mst |
| By: | Michael McAleer (Econometric Institute, Erasmus University Rotterdam); Marcelo Cunha Medeiros (Department of Economics PUC-Rio) |
| Abstract: | In this paper we consider a nonlinear model based on neural networks as well as linear models to forecast the daily volatility of the S&P 500 and FTSE 100 indexes. As a proxy for daily volatility, we consider a consistent and unbiased estimator of the integrated volatility that is computed from high frequency intra-day returns. We also consider a simple algorithm based on bagging (bootstrap aggregation) in order to specify the models analyzed in this paper. |
| Keywords: | Financial econometrics, volatility forecasting, neural networks, nonlinear models, realized volatility, bagging. |
| Date: | 2010–03 |
| URL: | http://d.repec.org/n?u=RePEc:rio:texdis:568&r=mst |
| By: | M. FRÖMMEL; N. KISS M; K. PINTÉR; |
| Abstract: | We investigate the relation between the intradaily HUF/EUR exchange rate on the one hand and news announcements and order flow on the other hand. We extend the existing literature on foreign exchange market microstructure by considering a small open transition economy. We find that the intradaily exchange rate depends on both, news announcements and order flow. We conclude that news on the HUF/EUR market are transmitted directly via immediate reactions to news announcements as well as indirectly via order flow. We decompose the news’ total effect on exchange rate and find that order flow accounts for approximately three quarters, compared to one quarter for direct news impact. Although the HUF is pegged to the EUR, the exchange rate shows similar characteristics as reported in the literature for major currencies. It does, however, differ in quantitative terms: the importance of indirect news transmission is remarkably higher on the HUF/EUR market. Furthermore, we extend the commonly used set of news by communication of central bankers and significantly improve the explanatory power of the estimates. Thus, central bank communication can be regarded as an important determinant for the HUF/EUR rate. |
| Keywords: | microstructure, order flow, exchange rate, macroeconomic news, central bank communication, Hungary |
| JEL: | F31 G14 G15 |
| Date: | 2009–12 |
| URL: | http://d.repec.org/n?u=RePEc:rug:rugwps:09/626&r=mst |
| By: | Mancini, Loriano (Swiss Finance Institute at EPFL); Ranaldo, Angelo (Swiss National Bank); Wrampelmeyer, Jan (University of Zurich) |
| Abstract: | This paper develops a liquidity measure tailored to the foreign exchange (FX) market, quantifies the amount of commonality in liquidity across exchange rates, and determines the extent of liquidity risk premiums embedded in FX returns. The new liquidity measure utilizes ultra high frequency data and captures cross-sectional and temporal variation in FX liquidity during the financial crisis of 2007–2008. Empirical results show that liquidity co-moves across currency pairs and that systematic FX liquidity decreases dramatically during the crisis. Extending an asset pricing model for FX returns by the novel liquidity risk factor suggests that liquidity risk is heavily priced. |
| Keywords: | Foreign Exchange Market; Measuring Liquidity; Commonality in Liquidity; Liquidity Risk Premium; Subprime Crisis |
| JEL: | F31 G12 G15 |
| Date: | 2009–11–20 |
| URL: | http://d.repec.org/n?u=RePEc:ris:snbwpa:2010_003&r=mst |
| By: | Hussain, Syed Mujahid (Department of Finance and Statistics, Hanken School of Economics, Helsinki) |
| Abstract: | This paper investigates the return and volatility responses of major European and the US equity indices to monetary policy surprises using extensive intraday data on 5-minute price quotes along with a comprehensive dataset on monetary policy decisions and macroeconomic news. Our results show that monetary policy decisions generally exert an immediate and significant influence on stock index returns and volatilities in both European US markets. Our findings also indicate that European Central Bank’s (ECB) press conferences following monetary policy decisions on the same day have define impacts on European index return volatilities, implying that they convey important information to market participants. However, in contrast to some earlier evidence, we do not find any support for the hypothesis that return volatilities in European and US markets are significantly affected by the path surprises. Overall, our analysis suggests that the use of high frequency data is critical for separating the effects of monetary policy actions from those of macroeconomic news announcements on stock index returns and volatilities. |
| Keywords: | conditional mean; conditional volatility; macroeconomic news; monetary policy; high frequency data |
| JEL: | G14 G15 |
| Date: | 2010–03–10 |
| URL: | http://d.repec.org/n?u=RePEc:hhs:bofrdp:2010_008&r=mst |
| By: | Wolfgang Karl Härdle; Stefan Trück |
| Abstract: | The dynamics of hourly electricity prices in day-ahead markets is an important element of competitive power markets that were only established in the last decade. In electricity markets, the market microstructure does not allow for continuous trading, since operators require advance notice in order to verify that the schedule is feasible and lies within transmission constraints. Instead agents have to submit their bids and offers for delivery of electricity for all hours of the next day before a specified market closing time. We suggest the use of dynamic semiparametric factor models (DSFM) for the behavior of hourly electricity prices. We find that a model with three factors is able to explain already a high proportion of the variation in hourly electricity prices. Our analysis also provides insights into the characteristics of the market, in particular with respect to the driving factors of hourly prices and their dynamic behavior through time. |
| Keywords: | Power Markets, Dynamic Semiparametric Factor Models, Day-ahead Electricity Prices |
| JEL: | G12 C19 C13 |
| Date: | 2010–02 |
| URL: | http://d.repec.org/n?u=RePEc:hum:wpaper:sfb649dp2010-013&r=mst |