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on Market Microstructure |
| By: | Ramazan Gencay (Department of Economics, Simon Fraser University); Nikola Gradojevic (Faculty of Business Administration, Lakehead University) |
| Abstract: | We examine a recent set of high-frequency spot EUR-USD foreign exchange transaction data from an electronic foreign exchange market. Our framework is based on a continuous time-sequential microstructure trade model that measures the market makers beliefs directly. We present evidence of the strategic arrival of informed traders on a particular day of the week, time of day and geographic location (market) |
| Keywords: | Foreign Exchange Markets; Volume; Informed Trading; Noise Trading |
| JEL: | G0 G1 F3 |
| Date: | 2009–01 |
| URL: | http://d.repec.org/n?u=RePEc:rim:rimwps:wp24_09&r=mst |
| By: | Ramazan Gencay (Department of Economics, Simon Fraser University); Nikola Gradojevic (Faculty of Business Administration, Lakehead University); Faruk Selcuk (Department of Economics, Bilkent University) |
| Abstract: | Fundamental spot exchange rate models preclude the existence of asymmetric information in foreign exchange markets. This article critically investigates the possibility that private information arises in the spot foreign exchange market. Using a rich dataset, we first empirically detect transaction behavior consistent with the informed trading hypothesis. We then work within the theoretical framework of a high-frequency version of a structural microstructure trade model, which directly measures the market maker’s beliefs. We find that the time-varying pattern of the probability of informed trading is rooted in the strategic arrival of informed traders on a particular hour-of-day, day-of-week, or geographic location (market) |
| Keywords: | Foreign Exchange Markets; Volume; Informed Trading; Noise Trading |
| JEL: | G0 G1 |
| Date: | 2009–01 |
| URL: | http://d.repec.org/n?u=RePEc:rim:rimwps:wp25_09&r=mst |
| By: | Yi Xue (Department of Economics, Simon Fraser University); Ramazan Gencay (Department of Economics, Simon Fraser University) |
| Abstract: | Volatility clustering, with autocorrelations of the hyperbolic decay rate, is unquestionably one of the most important stylized facts of financial time series. This paper presents a market microstructure model, that is able to generate volatility clustering with hyperbolic autocorrelations through traders with multiple trading frequencies using Bayesian information updating in an incomplete market. The model illustrates that signal extraction, which is induced by multiple trading frequency, can increase the persistence of the volatility of returns. Furthermore, we show that the local temporal memory of the underlying time series of returns and their volatility varies greatly varies with the number of traders in the market |
| Keywords: | Trading frequency, Volatility clustering, Signal extraction, Hyperbolic decay |
| JEL: | G10 G11 D43 D82 |
| Date: | 2009–01 |
| URL: | http://d.repec.org/n?u=RePEc:rim:rimwps:wp31_09&r=mst |
| By: | Julien Chevallier; Benoît Sévi |
| Abstract: | The recent implementation of the EU Emissions Trading Scheme (EU ETS) in January 2005 created new financial risks for emitting firms. To deal with these risks, options are traded since October 2006. Because the EU ETS is a new market, the relevant underlying model for option pricing is still a controversial issue. This article improves our understanding of this issue by characterizing the conditional and unconditional distributions of the realized volatility for the 2008 futures contract in the European Climate Exchange (ECX), which is valid during Phase II (2008-2012) of the EU ETS. The realized volatility measures from naive, kernel-based and subsampling estimators are used to obtain inferences about the distributional and dynamic properties of the ECX emissions futures volatility. The distribution of the daily realized volatility in logarithmic form is shown to be close to normal. The mixture-of-distributions hypothesis is strongly rejected, as the returns standardized using daily measures of volatility clearly departs from normality. A simplified HAR-RV model (Corsi, 2009) with only a weekly component, which reproduces long memory properties of the series, is then used to model the volatility dynamics. Finally, the predictive accuracy of the HAR-RV model is tested against GARCH specifications using one-step-ahead forecasts, which confirms the HAR-RV superior ability. Our conclusions indicate that (i) the standard Brownian motion is not an adequate tool for option pricing in the EU ETS, and (ii) a jump component should be included in the stochastic process to price options, thus providing more efficient tools for risk-management activities. |
| Keywords: | CO2 Price, Realized Volatility, HAR-RV, GARCH, Futures Trading, Emissions Markets, EU ETS, Intraday data, Forecasting |
| JEL: | C5 G1 Q4 |
| Date: | 2009 |
| URL: | http://d.repec.org/n?u=RePEc:drm:wpaper:2009-24&r=mst |
| By: | Yi Xue (Department of Economics, Simon Fraser University); Ramazan Gencay (Department of Economics, Simon Fraser University) |
| Abstract: | The rate of information diffusion and consequently price discovery, is conditional upon not only the design of the market microstructure, but also the informational structure. This paper presents a market microstructure model showing that an increasing number of information hierarchies among informed competitive traders leads to a slower information diffusion rate and informational inefficiency. The model illustrates that informed traders may prefer trading with each other rather than with noise traders in the presence of the information hierarchies. Furthermore, we show that momentum can be generated from the predictable patterns of noise traders, which are assumed to be a function of past prices |
| Keywords: | Information hierarchies, Information diffusion rate, Momentum |
| JEL: | G10 G11 D43 D82 |
| Date: | 2009–01 |
| URL: | http://d.repec.org/n?u=RePEc:rim:rimwps:wp29_09&r=mst |
| By: | John M. Maheu (Department of Economics, University of Toronto and RCEA); Thomas H. McCurdy (Rotman School of Management, University of Toronto, and CIRANO) |
| Abstract: | Many finance questions require the predictive distribution of returns. We propose a bivariate model of returns and realized volatility (RV), and explore which features of that time-series model contribute to superior density forecasts over horizons of 1 to 60 days out of sample. This term structure of density forecasts is used to investigate the importance of: the intraday information embodied in the daily RV estimates; the functional form for log(RV ) dynamics; the timing of information availability; and the assumed distributions of both return and log(RV) innovations. We find that a joint model of returns and volatility that features two components for log(RV) provides a good fit to S&P 500 and IBM data, and is a significant improvement over an EGARCH model estimated from daily returns |
| Keywords: | Realized Volatility, multiperiod out-of-sample prediction, term structure of density forecasts, Stochastic Volatility |
| Date: | 2009–01 |
| URL: | http://d.repec.org/n?u=RePEc:rim:rimwps:wp19_09&r=mst |
| By: | Mario Cerrato; Nicholas Sarantis; Alex Saunders |
| Abstract: | This paper examines the effect that heterogeneous customer orders flows have on exchange rates by using a new propreitary dataset of weekly net order flow segmented by customer type across nine of the most liquid currency pairs. We make three contributions. First, we investigate the extent to which order flow can help to explain exchange rate movements over and above the influence of macroeconomic variables. Second, we look at the usefulness of order flow in forecasting exchange rate movements at longer horizons than those generally considered in the microstructure literature. Finally we address the question of whether the out-of-sample exchange rate forecasts generated by order flows can be employed profitably in the foreign exchange markets. |
| Keywords: | Customer order flow; exchange rates; microstructure; forecasting |
| JEL: | F31 F41 G10 |
| Date: | 2009–07 |
| URL: | http://d.repec.org/n?u=RePEc:gla:glaewp:2009_25&r=mst |
| By: | Youki Kohsaka (Graduate School of Economics, Osaka University) |
| Abstract: | This paper examines how the informational efficiency of the Japanese stock markets changed with the introduction of ETFs(Exchange-Traded Funds) by looking at the arbitrage relationships between cash and futures of the Nikkei225. This paper is unique in that it uses tick data, which enable me to measure the degree of arbitrage by four indexes: 1) the frequency and 2) the size of the deviations from non-arbitrage condition, which reflects the magnitude of arbitrage opportunities, 3) the frequency of arbitrage transactions as a measures of the intensity of arbitrage activities and 4) the time during a deviation from non-arbitrage condition for an indicator of the achieved informational efficiency. I found that the frequency and the size of the deviations as well as the frequency of arbitrage transactions increased significantly. However, the deviation time did not change. These results suggest that while arbitrage opportunities increased, the intensified arbitrage activities balanced out it, resulting in the invariant time of deviation. |
| Keywords: | ETF(Exchange-Traded Funds), Arbitrage Relationship, Arbitrage Activity |
| JEL: | G13 G14 |
| Date: | 2009–07 |
| URL: | http://d.repec.org/n?u=RePEc:osk:wpaper:0920&r=mst |
| By: | Neil Shephard; Kevin Sheppard |
| Abstract: | This paper studies in some detail a class of high frequency based volatility (HEAVY) models. These models are direct models of daily asset return volatility based on realized measures constructed from high frequency data. Our analysis identifies that the models have momentum and mean reversion effects, and that they adjust quickly to structural breaks in the level of the volatility process. We study how to estimate the models and how they perform through the credit crunch, comparing their fit to more traditional GARCH models. We analyse a model based bootstrap which allow us to estimate the entire predictive distribution of returns. We also provide an analysis of missing data in the context of these models. |
| Keywords: | ARCH models; bootstrap; missing data; multiplicative error model; multistep ahead prediction; non-nested likelihood ratio test; realised kernel; realised volatility. |
| Date: | 2009 |
| URL: | http://d.repec.org/n?u=RePEc:sbs:wpsefe:2009fe02&r=mst |
| By: | Neil Shephard; Kevin Sheppard |
| Abstract: | This paper studies in some detail a class of high frequency based volatility (HEAVY) models. These models are direct models of daily asset return volatility based on realized measures constructed from high frequency data. Our analysis identifies that the models have momentum and mean reversion effects, and that they adjust quickly to structural breaks in the level of the volatility process. We study how to estimate the models and how they perform through the credit crunch, comparing their fit to more traditional GARCH models. We analysis a model based bootstrap which allow us to estimate the entire predictive distribution of returns. We also provide an analysis of missing data in the context of these models. |
| Keywords: | ARCH models, Bootstrap, Missing data, Multiplicative error model, Multistep ahead prediction, Non-nested likelihood ratio test, Realised kernal, Realised volatility |
| Date: | 2009 |
| URL: | http://d.repec.org/n?u=RePEc:oxf:wpaper:438&r=mst |
| By: | Bernhard Engel |
| Abstract: | Commercial transaction surveys and test market data are important sources for the analysis of consumer behaviour in various markets. The advantage of these surveys is that they do not only rely on “weak” data of consumers but also on “measured” data (eg. sales information, marketing information etc.) The key questions for the analysis of commercial transaction surveys and test market data are the prospective evaluation of market success for launched or relaunched products and services, the influence of marketing and media on product purchases under “real market conditions” and comparison between the test market and the total market. These data are not yet used by the scientific community. There are three major challenges to get access to the data. The owners of the data (market research institutes/”clients”) have to allow data access. The data must be anonymized in various ways (individuals/households, brands/products) without losing relevant information. Furthermore it is necessary to develop quality guidelines for commercial transaction surveys and test market data. In order to setup the process the RATSWD should initiate a project of official statistics, scientific community and commercial market research. |
| Keywords: | Consumer behaviour, test market |
| Date: | 2009 |
| URL: | http://d.repec.org/n?u=RePEc:rsw:rswwps:rswwps31&r=mst |