Dynamic Discrete Mixtures For High Frequency Prices
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| Author | : Leopoldo Catania |
| Publisher | : |
| Total Pages | : 39 |
| Release | : 2019 |
| Genre | : |
| ISBN | : |
The tick structure of the financial markets entails that price changes observed at very high frequency are discrete. Departing from this empirical evidence we develop a new model to describe the dynamic properties of multivariate time-series of high frequency price changes, including the high probability of observing no variations (price staleness). We assume the existence of two independent latent/hidden Markov processes determining the dynamic properties of the price changes and the excess probability of the occurrence of zeros. We study the probabilistic properties of the model that generates a zero-inflated mixture of Skellam distributions and we develop an EM estimation procedure with closed-form M step. In the empirical application, we study the joint distribution of the price changes of four assets traded on NYSE. Particular focus is dedicated to the precision of the univariate and multivariate density forecasts, to the quality of the predictions of quantities like the volatility and correlations across assets, and to the possibility of disentangling the different sources of zero price variation as generated by absence of news, microstructural frictions or by the offsetting positions taken by the traders.
| Author | : Luc Bauwens |
| Publisher | : Springer Science & Business Media |
| Total Pages | : 310 |
| Release | : 2007-12-31 |
| Genre | : Business & Economics |
| ISBN | : 3790819921 |
Shedding light on some of the most pressing open questions in the analysis of high frequency data, this volume presents cutting-edge developments in high frequency financial econometrics. Coverage spans a diverse range of topics, including market microstructure, tick-by-tick data, bond and foreign exchange markets, and large dimensional volatility modeling. The volume is of interest to graduate students, researchers, and industry professionals.
| Author | : Álvaro Cartea |
| Publisher | : Cambridge University Press |
| Total Pages | : 360 |
| Release | : 2015-08-06 |
| Genre | : Mathematics |
| ISBN | : 1316453650 |
The design of trading algorithms requires sophisticated mathematical models backed up by reliable data. In this textbook, the authors develop models for algorithmic trading in contexts such as executing large orders, market making, targeting VWAP and other schedules, trading pairs or collection of assets, and executing in dark pools. These models are grounded on how the exchanges work, whether the algorithm is trading with better informed traders (adverse selection), and the type of information available to market participants at both ultra-high and low frequency. Algorithmic and High-Frequency Trading is the first book that combines sophisticated mathematical modelling, empirical facts and financial economics, taking the reader from basic ideas to cutting-edge research and practice. If you need to understand how modern electronic markets operate, what information provides a trading edge, and how other market participants may affect the profitability of the algorithms, then this is the book for you.
| Author | : Sylvia Fruhwirth-Schnatter |
| Publisher | : CRC Press |
| Total Pages | : 388 |
| Release | : 2019-01-04 |
| Genre | : Computers |
| ISBN | : 0429508867 |
Mixture models have been around for over 150 years, and they are found in many branches of statistical modelling, as a versatile and multifaceted tool. They can be applied to a wide range of data: univariate or multivariate, continuous or categorical, cross-sectional, time series, networks, and much more. Mixture analysis is a very active research topic in statistics and machine learning, with new developments in methodology and applications taking place all the time. The Handbook of Mixture Analysis is a very timely publication, presenting a broad overview of the methods and applications of this important field of research. It covers a wide array of topics, including the EM algorithm, Bayesian mixture models, model-based clustering, high-dimensional data, hidden Markov models, and applications in finance, genomics, and astronomy. Features: Provides a comprehensive overview of the methods and applications of mixture modelling and analysis Divided into three parts: Foundations and Methods; Mixture Modelling and Extensions; and Selected Applications Contains many worked examples using real data, together with computational implementation, to illustrate the methods described Includes contributions from the leading researchers in the field The Handbook of Mixture Analysis is targeted at graduate students and young researchers new to the field. It will also be an important reference for anyone working in this field, whether they are developing new methodology, or applying the models to real scientific problems.
| Author | : Stephen J. Taylor |
| Publisher | : Princeton University Press |
| Total Pages | : 544 |
| Release | : 2011-02-11 |
| Genre | : Business & Economics |
| ISBN | : 1400839254 |
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.
| Author | : Istvan Barra |
| Publisher | : |
| Total Pages | : 47 |
| Release | : 2018 |
| Genre | : |
| ISBN | : |
We investigate high-frequency volatility models for analyzing intra-day tick by tick stock price changes using Bayesian estimation procedures. Our key interest is the extraction of intra-day volatility patterns from high-frequency integer price changes. We account for the discrete nature of the data via two different approaches: ordered probit models and discrete distributions. We allow for stochastic volatility by modeling the variance as a stochastic function of time, with intra-day periodic patterns. We consider distributions with heavy tails to address occurrences of jumps in tick by tick discrete prices changes. In particular, we introduce a dynamic version of the negative binomial difference model with stochastic volatility. For each model we develop a Markov chain Monte Carlo estimation method that takes advantage of auxiliary mixture representations to facilitate the numerical implementation. This new modeling framework is illustrated by means of tick by tick data for several stocks from the NYSE and for different periods. Different models are compared with each other based on predictive likelihoods.We find evidence in favor of our preferred dynamic negative binomial difference model.
| Author | : Kenneth Train |
| Publisher | : Cambridge University Press |
| Total Pages | : 399 |
| Release | : 2009-07-06 |
| Genre | : Business & Economics |
| ISBN | : 0521766559 |
This book describes the new generation of discrete choice methods, focusing on the many advances that are made possible by simulation. Researchers use these statistical methods to examine the choices that consumers, households, firms, and other agents make. Each of the major models is covered: logit, generalized extreme value, or GEV (including nested and cross-nested logits), probit, and mixed logit, plus a variety of specifications that build on these basics. Simulation-assisted estimation procedures are investigated and compared, including maximum stimulated likelihood, method of simulated moments, and method of simulated scores. Procedures for drawing from densities are described, including variance reduction techniques such as anithetics and Halton draws. Recent advances in Bayesian procedures are explored, including the use of the Metropolis-Hastings algorithm and its variant Gibbs sampling. The second edition adds chapters on endogeneity and expectation-maximization (EM) algorithms. No other book incorporates all these fields, which have arisen in the past 25 years. The procedures are applicable in many fields, including energy, transportation, environmental studies, health, labor, and marketing.
| Author | : Torben Gustav Andersen |
| Publisher | : Springer Science & Business Media |
| Total Pages | : 1045 |
| Release | : 2009-04-21 |
| Genre | : Business & Economics |
| ISBN | : 3540712976 |
The Handbook of Financial Time Series gives an up-to-date overview of the field and covers all relevant topics both from a statistical and an econometrical point of view. There are many fine contributions, and a preamble by Nobel Prize winner Robert F. Engle.
| Author | : Craig Pirrong |
| Publisher | : Cambridge University Press |
| Total Pages | : 239 |
| Release | : 2011-10-31 |
| Genre | : Business & Economics |
| ISBN | : 1139501976 |
Commodities have become an important component of many investors' portfolios and the focus of much political controversy over the past decade. This book utilizes structural models to provide a better understanding of how commodities' prices behave and what drives them. It exploits differences across commodities and examines a variety of predictions of the models to identify where they work and where they fail. The findings of the analysis are useful to scholars, traders and policy makers who want to better understand often puzzling - and extreme - movements in the prices of commodities from aluminium to oil to soybeans to zinc.
| Author | : Francesco Bartolucci |
| Publisher | : CRC Press |
| Total Pages | : 253 |
| Release | : 2012-10-29 |
| Genre | : Mathematics |
| ISBN | : 1466583711 |
Drawing on the authors' extensive research in the analysis of categorical longitudinal data, this book focuses on the formulation of latent Markov models and the practical use of these models. It demonstrates how to use the models in three types of analysis, with numerous examples illustrating how latent Markov models are used in economics, education, sociology, and other fields. The R and MATLAB routines used for the examples are available on the authors' website.
