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Trading Frequency And Volatility Clustering
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Book Synopsis Trading Frequency and Volatility Clustering by : Yi Xue
Download or read book Trading Frequency and Volatility Clustering written by Yi Xue and published by . This book was released on 2009 with total page 61 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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 with the number of traders in the market.
Book Synopsis Volatility Clustering in Financial Markets by : Thomas Lux
Download or read book Volatility Clustering in Financial Markets written by Thomas Lux and published by . This book was released on 1998 with total page 28 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Book Synopsis Price Change, Trading Volume, Volatility Clustering and the Mixture of Distributions Hypothesis by : Vadhindran K. Rao
Download or read book Price Change, Trading Volume, Volatility Clustering and the Mixture of Distributions Hypothesis written by Vadhindran K. Rao and published by . This book was released on 1996 with total page 302 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Book Synopsis Volatility Clustering in Monthly Stock Returns by : Ben Jacobsen
Download or read book Volatility Clustering in Monthly Stock Returns written by Ben Jacobsen and published by . This book was released on 2007 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt: We investigate volatility clustering using a modeling approach based on the temporal aggregation results for generalized autoregressive conditional heteroscedasticity (GARCH) models in Drost and Nijman [Econometrica, 1993]. Our findings highlight that volatility clustering, contrary to widespread belief, is not only present in high-frequency financial data. Monthly data also exhibit significant serial dependence in the second moments. We show that the use of temporal aggregation to estimate low-frequency models reduces parameter uncertainty substantially.
Book Synopsis Long Memory in Economics by : Gilles Teyssière
Download or read book Long Memory in Economics written by Gilles Teyssière and published by Springer Science & Business Media. This book was released on 2006-09-22 with total page 394 pages. Available in PDF, EPUB and Kindle. Book excerpt: Assembles three different strands of long memory analysis: statistical literature on the properties of, and tests for, LRD processes; mathematical literature on the stochastic processes involved; and models from economic theory providing plausible micro foundations for the occurrence of long memory in economics.
Book Synopsis Volatility Clustering in Stock Returns at Low Frequencies by : Ben Jacobsen
Download or read book Volatility Clustering in Stock Returns at Low Frequencies written by Ben Jacobsen and published by . This book was released on 1995 with total page 31 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Book Synopsis Volatility Clustering in Financial Markets by : Thomas Lux
Download or read book Volatility Clustering in Financial Markets written by Thomas Lux and published by . This book was released on 1998 with total page 28 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Book Synopsis An Introduction to High-Frequency Finance by : Ramazan Gençay
Download or read book An Introduction to High-Frequency Finance written by Ramazan Gençay and published by Elsevier. This book was released on 2001-05-29 with total page 411 pages. Available in PDF, EPUB and Kindle. Book excerpt: Liquid markets generate hundreds or thousands of ticks (the minimum change in price a security can have, either up or down) every business day. Data vendors such as Reuters transmit more than 275,000 prices per day for foreign exchange spot rates alone. Thus, high-frequency data can be a fundamental object of study, as traders make decisions by observing high-frequency or tick-by-tick data. Yet most studies published in financial literature deal with low frequency, regularly spaced data. For a variety of reasons, high-frequency data are becoming a way for understanding market microstructure. This book discusses the best mathematical models and tools for dealing with such vast amounts of data. This book provides a framework for the analysis, modeling, and inference of high frequency financial time series. With particular emphasis on foreign exchange markets, as well as currency, interest rate, and bond futures markets, this unified view of high frequency time series methods investigates the price formation process and concludes by reviewing techniques for constructing systematic trading models for financial assets.
Book Synopsis Volatility Clustering in the Forex Market - An Interacting Agents Approach by :
Download or read book Volatility Clustering in the Forex Market - An Interacting Agents Approach written by and published by . This book was released on 2015 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt: Financial time series have been shown to exhibit market regularities, so-called stylized facts, which have challenged the rational expectations and efficient market theory. In order to explain those market regularities, behavioral finance economists developed a broad range of agent-based models consisting of agents with heterogeneous expectations on future prices. Agents were not only assumed to have heterogeneous expectations and different trading strategies, they were furthermore assumed to be able to switch between the strategies. The present paper focuses on one particular market regularity, which is volatility clustering of financial time series in the framework of the foreign exchange market. The goal is to explain the phenomenon of volatility clustering from a behavioral finance perspective. In a first step, an overview over common Forex market characteristics is provided, followed by some traditional models of exchange rate determination and the subsequent paradigm shift in the concept of expectations. After having presented the main behavioral explanations on volatility clustering, an agent-based model is introduced, capturing the idea of agent's inertia, as one possible driver of volatility clustering in financial markets. The introduced agent-based model represents an extension of the original model by Frank Westerhoff (2010). The present paper contributes to the behavioral finance literature by enlightening one novel aspect of agent's behavior that may affect price dynamics in financial markets.
Book Synopsis Volatility Clustering by : Xuezhong He
Download or read book Volatility Clustering written by Xuezhong He and published by . This book was released on 2016 with total page 45 pages. Available in PDF, EPUB and Kindle. Book excerpt: This paper verifies the endogenous mechanism and economic intuition on volatility clustering using the coexistence of two locally stable attractors proposed by Gaunersdorfer, Hommes and Wagener (2008). By considering a simple asset pricing model with two types of boundedly rational traders, fundamentalists and trend followers, and noise traders, we provide conditions on the coexistence of locally stable steady state and invariant cycle of the underlying nonlinear deterministic financial market model and show numerically that the interaction of the coexistence of the deterministic dynamics and noise processes can endogenously generate volatility clustering and long range dependence in volatility observed in financial markets. Economically, volatility clustering occurs when neither the fundamental nor trend following traders dominate the market and when traders switch more often between the two strategies.
Book Synopsis The Key Role of Inter-Event Times in Volatility Clustering by : Jaroslaw Klamut
Download or read book The Key Role of Inter-Event Times in Volatility Clustering written by Jaroslaw Klamut and published by . This book was released on 2019 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: Over 50 years ago, two physicists Montroll and Weiss in the physical context of dispersive transport and diffusion introduced stochastic process, named Continuous-Time Random Walk (CTRW). The trajectory of such a process is created by elementary events 'spatial' jumps preceded by waiting time. Since introduction, CTRW found innumerable application in different fields including high-frequency finance, where jumps are considered as price increments and waiting times represent inter-trade times. In this manuscript we show that dependencies between inter-trade times are the key element to explain long-term memory in financial time-series, even when taking into account intraday seasonality (so-called "lunch effect”). We introduce the new CTRW model with long-term memory in waiting times, able to successfully describe power-law decaying time autocorrelation of the absolute values of price changes. We test our model on the empirical data from Polish stock market.
Book Synopsis Two-sided Markets and Intertemporal Trade Clustering by :
Download or read book Two-sided Markets and Intertemporal Trade Clustering written by and published by . This book was released on 2006 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt:
Book Synopsis Volatility Trading with Machine Learning Forecasting Methods by : Sergio Andrés González Orjuela
Download or read book Volatility Trading with Machine Learning Forecasting Methods written by Sergio Andrés González Orjuela and published by . This book was released on 2018 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt: Volatility trading has become a prominent alternative to the traditional stock trading as the rapid development of web-trading in recent years has reduced significantly the costs of operating in the market. Moreover, machine learning techniques have enabled traders to rely heavily on statistical decision-making models to enhance the commonly used technical analysis. In this paper, a machine learning approach is used to predict proxies of short-term implied volatility clusters with high-frequency data, in order to perform trading strategies using vanilla options on a commercial platform. The empirical results indicate that tree-based methods outperform linear models in classifying these clusters using the time of the day as a key variable in the forecasting task. Financial results were mixed due to the high costs of operating in a 5-hour horizon, but it was found that long positions on at the money straddle strategies expiring in one day were profitable. The framework developed here can be used by small investors as a guidance to implement and assess theoretical strategies in accessible markets.
Book Synopsis Three Essays on Market Microstructure and Financial Econometrics by : Yi Xue
Download or read book Three Essays on Market Microstructure and Financial Econometrics written by Yi Xue and published by . This book was released on 2009 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: This thesis consists of three essays that study three interdependent topics: microstructure foundation of volatility clustering, inefficiency of information diffusion and jump detection in high frequency financial time series data. Volatility clustering, with autocorrelations of the hyperbolic decay rate, is unquestionably one of the most important stylized facts of financial time series. The first essay forms Chapter 1 which 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, it is shown that the local temporal memory of the underlying time series of returns and their volatility varies greatly with the number of traders in the market. The second essay, Chapter 2, 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, it is shown that momentum can be generated from the trend following behavior pattern of noise traders. I propose a new nonparametric test based on wavelets to detect jump arrivals in high frequency financial time series data, in the third essay, Chapter 3. It is demonstrated that the test is robust for different specifications of price processes and the presence of market microstructure noise and it has good size and power. Further, I examine the multi-scale jump dynamics in U.S. equity markets and the findings are as follows. First, the jump dynamics of equities are entirely different across different time scales. Second, although arrival densities of positive jumps and negative jumps are symmetric across different time scales, the magnitude of jumps is distributed asymmetrically at high frequencies. Third, only twenty percent of jumps occur in the trading session from 9:30AM to 4:00PM, suggesting that jumps are largely determined by news rather than liquidity shocks.
Book Synopsis High Frequency Trading and Limit Order Book Dynamics by : Ingmar Nolte
Download or read book High Frequency Trading and Limit Order Book Dynamics written by Ingmar Nolte and published by Routledge. This book was released on 2016-04-14 with total page 325 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book brings together the latest research in the areas of market microstructure and high-frequency finance along with new econometric methods to address critical practical issues in these areas of research. Thirteen chapters, each of which makes a valuable and significant contribution to the existing literature have been brought together, spanning a wide range of topics including information asymmetry and the information content in limit order books, high-frequency return distribution models, multivariate volatility forecasting, analysis of individual trading behaviour, the analysis of liquidity, price discovery across markets, market microstructure models and the information content of order flow. These issues are central both to the rapidly expanding practice of high frequency trading in financial markets and to the further development of the academic literature in this area. The volume will therefore be of immediate interest to practitioners and academics. This book was originally published as a special issue of European Journal of Finance.
Book Synopsis Asset Price Dynamics, Volatility, and Prediction by : Stephen J. Taylor
Download or read book Asset Price Dynamics, Volatility, and Prediction written by Stephen J. Taylor and published by Princeton University Press. This book was released on 2007-09-02 with total page 544 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book shows how current and recent market prices convey information about the probability distributions that govern future prices. Moving beyond purely theoretical models, Stephen Taylor applies methods supported by empirical research of equity and foreign exchange markets to show how daily and more frequent asset prices, and the prices of option contracts, can be used to construct and assess predictions about future prices, their volatility, and their probability distributions. Stephen Taylor provides a comprehensive introduction to the dynamic behavior of asset prices, relying on finance theory and statistical evidence. He uses stochastic processes to define mathematical models for price dynamics, but with less mathematics than in alternative texts. The key topics covered include random walk tests, trading rules, ARCH models, stochastic volatility models, high-frequency datasets, and the information that option prices imply about volatility and distributions. Asset Price Dynamics, Volatility, and Prediction is ideal for students of economics, finance, and mathematics who are studying financial econometrics, and will enable researchers to identify and apply appropriate models and methods. It will likewise be a valuable resource for quantitative analysts, fund managers, risk managers, and investors who seek realistic expectations about future asset prices and the risks to which they are exposed.
Book Synopsis Forecasting Volatility in the Financial Markets by : Stephen Satchell
Download or read book Forecasting Volatility in the Financial Markets written by Stephen Satchell and published by Elsevier. This book was released on 2011-02-24 with total page 428 pages. Available in PDF, EPUB and Kindle. Book excerpt: Forecasting Volatility in the Financial Markets, Third Edition assumes that the reader has a firm grounding in the key principles and methods of understanding volatility measurement and builds on that knowledge to detail cutting-edge modelling and forecasting techniques. It provides a survey of ways to measure risk and define the different models of volatility and return. Editors John Knight and Stephen Satchell have brought together an impressive array of contributors who present research from their area of specialization related to volatility forecasting. Readers with an understanding of volatility measures and risk management strategies will benefit from this collection of up-to-date chapters on the latest techniques in forecasting volatility. Chapters new to this third edition:* What good is a volatility model? Engle and Patton* Applications for portfolio variety Dan diBartolomeo* A comparison of the properties of realized variance for the FTSE 100 and FTSE 250 equity indices Rob Cornish* Volatility modeling and forecasting in finance Xiao and Aydemir* An investigation of the relative performance of GARCH models versus simple rules in forecasting volatility Thomas A. Silvey Leading thinkers present newest research on volatility forecasting International authors cover a broad array of subjects related to volatility forecasting Assumes basic knowledge of volatility, financial mathematics, and modelling
