Download or read book The Quantile Heterogeneous Autoregressive Model of Realized Volatility written by Konstantin Kuck and published by . This book was released on 2018 with total page 20 pages. Available in PDF, EPUB and Kindle. Book excerpt: We provide a comprehensive view on volatility dynamics in precious metals and crude oil markets. Using high-frequency futures data, we construct realized volatilities and estimate (Quantile) Heterogeneous Autoregressive models for the daily volatility of Gold, Silver and Crude Oil futures. We model realized volatility as a linear function of lagged realized volatility measured over different time resolutions to explicitly account for the potentially heterogeneous impact of market participants with different trading motives and investment horizons. Using quantile regression allows us to identify potential non-linearities and asymmetries in the short-, mid- and long-term autoregressive dynamics with respect to different levels of current volatility. We document considerable changes in the relative importance of short-, mid-, and long-term volatility components under varying market conditions. The patterns that we identify are remarkably similar across the three assets. Specifically, past daily and monthly volatility have a strong impact on today's volatility, when current volatility is low (lower quantiles of the volatility distribution). The effect of past weekly volatility, however, increases distinctly from lower to higher quantiles of the conditional volatility distribution. The results might indicate considerable investor attention shifts and changes in the proportions of traders with different time horizons.

Download or read book Financial Mathematics Volatility and Covariance Modelling written by Julien Chevallier and published by Routledge. This book was released on 2019-06-28 with total page 381 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book provides an up-to-date series of advanced chapters on applied financial econometric techniques pertaining the various fields of commodities finance, mathematics & stochastics, international macroeconomics and financial econometrics. Financial Mathematics, Volatility and Covariance Modelling: Volume 2 provides a key repository on the current state of knowledge, the latest debates and recent literature on financial mathematics, volatility and covariance modelling. The first section is devoted to mathematical finance, stochastic modelling and control optimization. Chapters explore the recent financial crisis, the increase of uncertainty and volatility, and propose an alternative approach to deal with these issues. The second section covers financial volatility and covariance modelling and explores proposals for dealing with recent developments in financial econometrics This book will be useful to students and researchers in applied econometrics; academics and students seeking convenient access to an unfamiliar area. It will also be of great interest established researchers seeking a single repository on the current state of knowledge, current debates and relevant literature.

Download or read book A Vector Heterogeneous Autoregressive Index Model for Realized Volatility Measures written by Cianluca Cubadda and published by . This book was released on 2015 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt: This paper introduces a new modelling for detecting the presence of commonalities in a set of realized volatility measures. In particular, we propose a multivariate generalization of the heterogeneous autoregressive model HAR that is endowed with a common index structure. The Vector Heterogeneous Autoregressive Index model has the property to generate a common index that preserves the same temporal cascade structure as in the HAR model, a feature that is not shared by other aggregation methods e.g., principal components. The parameters of this model can be easily estimated by a proper switching algorithm that increases the Gaussian likelihood at each step. We illustrate our approach with an empirical analysis aiming at combining several realized volatility measures of the same equity index for three different markets.

Download or read book Realized Volatility Forecasting Based on Dynamic Quantile Model Averaging written by Zongwu Cai and published by . This book was released on 2020 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt:

Download or read book A Simple Long Memory Model of Realized Volatility written by Fulvio Corsi and published by . This book was released on 2004 with total page 27 pages. Available in PDF, EPUB and Kindle. Book excerpt: In the present work we propose a new realized volatility model to directly model and forecast the time series behavior of volatility. The purpose is to obtain a conditional volatility model based on realized volatility which is able to reproduce the memory persistence observed in the data but, at the same time, remains parsimonious and easy to estimate. Inspired by the Heterogeneous Market Hypothesis and the asymmetric propagation of volatility between long and short time horizons, we propose an additive cascade of different volatility components generated by the actions of different types of market participants. This additive volatility cascade leads to a simple AR-type model in the realized volatility with the feature of considering volatilities realized over different time horizons. We term this model, Heterogeneous Autoregressive model of the Realized Volatility (HAR-RV). In spite of the simplicity of its structure, simulation results seem to confirm that the HAR-RV model successfully achieves the purpose of reproducing the main empirical features of financial data (long memory, fat tail, self-similarity) in a very simple and parsimonious way. Preliminary results on the estimation and forecast of the HAR-RV model on USD/CHF data, show remarkably good out of sample forecasting performance which steadily and substantially outperforms those of standard models.

Download or read book Localized Quantile Regression of Realized Volatility written by Janaki Koralage and published by . This book was released on 2019 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt: Volatility is a financial term that measures the dispersion of asset returns. Calculating and predicting volatility are not simple, but there are several well-known models for determining the volatility of assets. In recent years, researchers have been interested in developing statistical methods to model financial volatility, and new concepts have been applied to achieve better results. Quantile regression is another area gaining increased attention in the analysis of financial data. In this thesis, we propose a new quantile regression model for measuring the volatility of financial assets called the localized quantile regression model. As the name suggests, the proposed model is a local model rather than a global model. It takes care of possible structural changes and makes predictions of volatility more reliable. The initial step in this approach is to identify the longest interval of homogeneity. Identifying this interval of homogeneity involves a sequential testing procedure. After identifying intervals, we can apply quantile regression for each homogeneous time interval. The main advantage of this method is that it does not require any distributional assumptions. Simulation studies are carried out to investigate the performance of the proposed method. Results obtained from the simulation study show that the localized quantile regression model is appropriate for modeling the volatility of financial assets.

Download or read book Quantile Forecast Combinations in Realised Volatility Prediction written by Loukia Meligkotsidou and published by . This book was released on 2015 with total page 43 pages. Available in PDF, EPUB and Kindle. Book excerpt: This paper tests whether it is possible to improve point, quantile and density forecasts of realized volatility by conditioning on macroeconomic and financial variables. We employ quantile autoregressive models augmented with a plethora of macroeconomic and financial variables. Complete subset combinations of both linear and quantile forecasts enable us to efficiently summarise the information content in the candidate predictors. Our findings suggest that no single variable is able to provide more information for the evolution of the volatility distribution beyond that contained in its own past. The best performing variable is the return on the stock market followed by the inflation rate. Our complete subset approach achieves superior quantile, density and point predictive performance relative to the univariate models and the autoregressive benchmark.

Download or read book A Simple Approximate Long Memory Model of Realized Volatility written by Fulvio Corsi and published by . This book was released on 2010 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt: The paper proposes an additive cascade model of volatility components defined over different time periods. This volatility cascade leads to a simple AR-type model in the realized volatility with the feature of considering different volatility components realized over different time horizons and thus termed Heterogeneous Autoregressive model of Realized Volatility (HAR-RV). In spite of the simplicity of its structure and the absence of true long-memory properties, simulation results show that the HAR-RV model successfully achieves the purpose of reproducing the main empirical features of financial returns (long memory, fat tails, and self-similarity) in a very tractable and parsimonious way. Moreover, empirical results show remarkably good forecasting performance.

Download or read book Stock Market Volatility written by Greg N. Gregoriou and published by CRC Press. This book was released on 2009-04-08 with total page 654 pages. Available in PDF, EPUB and Kindle. Book excerpt: Up-to-Date Research Sheds New Light on This Area Taking into account the ongoing worldwide financial crisis, Stock Market Volatility provides insight to better understand volatility in various stock markets. This timely volume is one of the first to draw on a range of international authorities who offer their expertise on market volatility in devel

Download or read book Proceedings of the Fourteenth International Conference on Management Science and Engineering Management written by Jiuping Xu and published by Springer Nature. This book was released on 2020-06-22 with total page 856 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book gathers the proceedings of the 14th International Conference on Management Science and Engineering Management (ICMSEM 2020). Held at the Academy of Studies of Moldova from July 30 to August 2, 2020, the conference provided a platform for researchers and practitioners in the field to share their ideas and experiences. Covering a wide range of topics, including hot management issues in engineering science, the book presents novel ideas and the latest research advances in the area of management science and engineering management. It includes both theoretical and practical studies of management science applied in computing methodology, highlighting advanced management concepts, and computing technologies for decision-making problems involving large, uncertain and unstructured data. The book also describes the changes and challenges relating to decision-making procedures at the dawn of the big data era, and discusses new technologies for analysis, capture, search, sharing, storage, transfer and visualization, and in the context of privacy violations, as well as advances in the integration of optimization, statistics and data mining. Given its scope, it will appeal to a wide readership, particularly those looking for new ideas and research directions.

Download or read book Handbook of Volatility Models and Their Applications written by Luc Bauwens and published by John Wiley & Sons. This book was released on 2012-04-17 with total page 566 pages. Available in PDF, EPUB and Kindle. Book excerpt: A complete guide to the theory and practice of volatility models in financial engineering Volatility has become a hot topic in this era of instant communications, spawning a great deal of research in empirical finance and time series econometrics. Providing an overview of the most recent advances, Handbook of Volatility Models and Their Applications explores key concepts and topics essential for modeling the volatility of financial time series, both univariate and multivariate, parametric and non-parametric, high-frequency and low-frequency. Featuring contributions from international experts in the field, the book features numerous examples and applications from real-world projects and cutting-edge research, showing step by step how to use various methods accurately and efficiently when assessing volatility rates. Following a comprehensive introduction to the topic, readers are provided with three distinct sections that unify the statistical and practical aspects of volatility: Autoregressive Conditional Heteroskedasticity and Stochastic Volatility presents ARCH and stochastic volatility models, with a focus on recent research topics including mean, volatility, and skewness spillovers in equity markets Other Models and Methods presents alternative approaches, such as multiplicative error models, nonparametric and semi-parametric models, and copula-based models of (co)volatilities Realized Volatility explores issues of the measurement of volatility by realized variances and covariances, guiding readers on how to successfully model and forecast these measures Handbook of Volatility Models and Their Applications is an essential reference for academics and practitioners in finance, business, and econometrics who work with volatility models in their everyday work. The book also serves as a supplement for courses on risk management and volatility at the upper-undergraduate and graduate levels.

Download or read book Prediction and Causality in Econometrics and Related Topics written by Nguyen Ngoc Thach and published by Springer Nature. This book was released on 2021-07-26 with total page 691 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book provides the ultimate goal of economic studies to predict how the economy develops—and what will happen if we implement different policies. To be able to do that, we need to have a good understanding of what causes what in economics. Prediction and causality in economics are the main topics of this book's chapters; they use both more traditional and more innovative techniques—including quantum ideas -- to make predictions about the world economy (international trade, exchange rates), about a country's economy (gross domestic product, stock index, inflation rate), and about individual enterprises, banks, and micro-finance institutions: their future performance (including the risk of bankruptcy), their stock prices, and their liquidity. Several papers study how COVID-19 has influenced the world economy. This book helps practitioners and researchers to learn more about prediction and causality in economics -- and to further develop this important research direction.

Download or read book Stochastic Volatility and Realized Stochastic Volatility Models written by Makoto Takahashi and published by Springer Nature. This book was released on 2023-04-18 with total page 120 pages. Available in PDF, EPUB and Kindle. Book excerpt: This treatise delves into the latest advancements in stochastic volatility models, highlighting the utilization of Markov chain Monte Carlo simulations for estimating model parameters and forecasting the volatility and quantiles of financial asset returns. The modeling of financial time series volatility constitutes a crucial aspect of finance, as it plays a vital role in predicting return distributions and managing risks. Among the various econometric models available, the stochastic volatility model has been a popular choice, particularly in comparison to other models, such as GARCH models, as it has demonstrated superior performance in previous empirical studies in terms of fit, forecasting volatility, and evaluating tail risk measures such as Value-at-Risk and Expected Shortfall. The book also explores an extension of the basic stochastic volatility model, incorporating a skewed return error distribution and a realized volatility measurement equation. The concept of realized volatility, a newly established estimator of volatility using intraday returns data, is introduced, and a comprehensive description of the resulting realized stochastic volatility model is provided. The text contains a thorough explanation of several efficient sampling algorithms for latent log volatilities, as well as an illustration of parameter estimation and volatility prediction through empirical studies utilizing various asset return data, including the yen/US dollar exchange rate, the Dow Jones Industrial Average, and the Nikkei 225 stock index. This publication is highly recommended for readers with an interest in the latest developments in stochastic volatility models and realized stochastic volatility models, particularly in regards to financial risk management.

Download or read book Essays on Stochastic Volatility and Jumps written by Diep Ngoc Duong and published by . This book was released on 2013 with total page 184 pages. Available in PDF, EPUB and Kindle. Book excerpt: This dissertation comprises three essays on financial economics and econometrics. The first essay outlines and expands upon further testing results from Bhardwaj, Corradi and Swanson (BCS: 2008) and Corradi and Swanson (2011). In particular, specification tests in the spirit of the conditional Kolmogorov test of Andrews (1997) that rely on block bootstrap resampling methods are first discussed. We then broaden our discussion from single process specification testing to multiple process model selection by discussing how to construct predictive densities and how to compare the accuracy of predictive densities derived from alternative (possibly misspecified) diffusion models. In particular, we generalize simulation steps outlined in Cai and Swanson (2011) to multifactor models where the number of latent variables is larger than three. In the second essay, we begin by discussing important developments in volatility modeling, with a focus on time varying and stochastic volatility as well as the "model free" estimation of volatility via the use of so-called realized volatility, and variants thereof called realized measures. In an empirical investigation, we use realized measures to investigate the role of "small" and large" jumps in the realized variation of stock price returns and show that jumps do matter in the relative contribution to the total variation of the process, when examining individual stock returns, as well as market indices. The third essay examines the predictive content of a variety of realized measures of jump power variations, all formed on the basis of power transformations of instantaneous returns. Our prediction involves estimating members of the linear and nonlinear extended Heterogeneous Autoregressive of the Realized Volatility (HAR-RV) class of models, using S & P 500 futures data as well as stocks in the Dow 30, for the period 1993-2009. Our findings suggest that past "large" jump power variations help less in the prediction of future realized volatility, than past "small" jump power variations. Our empirical findings also suggest that past realized signed jump power variations, which have not previously been examined in this literature, are strongly correlated with future volatility.

Download or read book Nonparametric Realized Volatility Estimation in the International Equity Markets written by Dimitrios I. Vortelinos and published by . This book was released on 2015 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt: Using high-frequency intraday data, we construct, test and model seven new realized volatility estimators for six international equity indices. We detect jumps in these estimators, construct the jump components of volatility and perform various tests on their properties. Then we use the class of heterogeneous autoregressive (HAR) models for assessing the relevant effects of jumps on volatility. Our results expand and complement the previous literature on the nonparametric realized volatility estimation in terms of volatility jumps being examined and modeled for the international equity market, using such a variety of new realized volatility estimators. The selection of realized volatility estimator greatly affects jump detection, magnitude and modeling. The properties each volatility estimator tries to incorporate affect the detection, magnitude and properties of jumps. These volatility-estimation and jump properties are also evident in jump modeling based on statistical and economic terms.

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.

Download or read book Estimating the Degrees of Freedom of the Realized Volatility Wishart Autoregressive Model written by Matteo Bonato and published by . This book was released on 2009 with total page 50 pages. Available in PDF, EPUB and Kindle. Book excerpt: In this paper an in-depth analysis of the estimation of the realized volatility Wishart Autoregressive model is presented. We focus in particular on the estimation of the degrees of freedom. A new estimator is proposed. Monte Carlo simulations show that this novel estimator is more efficient when compared to the standard estimator proposed in literature. We also studied the effect of extreme observation in the variance-covariance process. Analytically and relying on simulation, we show that extreme observations in the variance-covariance process induce a bias toward zero of the estimated degrees of freedom, no matter which estimator one uses. However, the new proposed estimator is more robust compared to the standard one. An empirical application to the Samp;P 500 - NASDAQ 100 futures realized variance-covariance series confirms that the estimated degrees of freedom result sensitively lower when extremely high values in the volatility process are present and they increase with the sampling frequency.