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Author: Yi Xue
Publisher:
ISBN:
Category :
Languages : en
Pages : 61
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Book Description
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.
Author: Yi Xue
Publisher:
ISBN:
Category :
Languages : en
Pages : 61
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Book Description
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.
Author: Thomas Lux
Publisher:
ISBN: 9783931052027
Category :
Languages : en
Pages : 28
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Book Description
Author: Vadhindran K. Rao
Publisher:
ISBN:
Category :
Languages : en
Pages : 302
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Book Description
Author: Gilles Teyssière
Publisher: Springer Science & Business Media
ISBN: 3540346252
Category : Business & Economics
Languages : en
Pages : 394
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Book Description
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.
Author: Ben Jacobsen
Publisher:
ISBN:
Category :
Languages : en
Pages :
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Book Description
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.
Author: Ben Jacobsen
Publisher:
ISBN:
Category :
Languages : en
Pages : 31
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Book Description
Author: Thomas Lux
Publisher:
ISBN: 9783931052027
Category :
Languages : en
Pages : 28
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Book Description
Author: Ramazan Gençay
Publisher: Elsevier
ISBN: 008049904X
Category : Business & Economics
Languages : en
Pages : 411
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Book Description
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.
Author:
Publisher:
ISBN:
Category :
Languages : en
Pages :
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Book Description
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.
Author: Stephen J. Taylor
Publisher: Princeton University Press
ISBN: 1400839254
Category : Business & Economics
Languages : en
Pages : 544
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Book Description
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.
