Online Surveillance Of Volatility Forecasting Models
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Online Surveillance Of Volatility Forecasting Models
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Author : Vasyl Golosnoy
language : en
Publisher:
Release Date : 2010
Online Surveillance Of Volatility Forecasting Models written by Vasyl Golosnoy and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2010 with categories.
Statistical Surveillance Of Volatility Forecasting Models
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Author : Vasyl Golosnoy
language : en
Publisher:
Release Date : 2011
Statistical Surveillance Of Volatility Forecasting Models written by Vasyl Golosnoy and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2011 with categories.
This paper elaborates sequential procedures for monitoring the validity of a volatility model. A state space representation describes dynamics of daily integrated volatility. The observation equation relates the integrated volatility to its measures such as the realized volatility or bipower variation. On-line control procedures, based on volatility forecasting errors, allow us to decide whether the chosen representation remains correctly specified. A signal indicates that the assumed volatility model may no longer be valid. The performance of our approach is analyzed within a Monte Carlo simulation study and illustrated in an empirical application for selected US stocks.
Volatility Forecasting
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Author : Arabinda Basistha
language : en
Publisher:
Release Date : 2019
Volatility Forecasting written by Arabinda Basistha and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2019 with categories.
Recent empirical literature shows that Internet search activity is closely associated with volatility prediction in financial and commodity markets. In this study, we search for a benchmark model with available market-based predictors to evaluate the net contribution of the Internet search activity data in forecasting volatility. We conduct in-sample analysis and window-size robust out-of-sample forecasting analysis in multiple markets for robust model validation. The predictive power of the Internet search activity data disappears in the financial markets and substantially diminishes in the commodity markets once the model includes implied volatility. A further common component analysis shows that most of the predictive information contained in the Internet search activity is also present in implied volatility while implied volatility has additional predictive information that is not contained in the Internet search activity data.
Hybrid Volatility Forecasting Models Based On Machine Learning Of High Frequency Data
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Author : Xiaolin Wang
language : en
Publisher:
Release Date : 2022
Hybrid Volatility Forecasting Models Based On Machine Learning Of High Frequency Data written by Xiaolin Wang and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2022 with Statistics categories.
Volatility modeling and forecasting are crucial in risk management and pricing derivatives. High-frequency financial data are dynamic and affected by the microstructure noise. For the univariate case, we define the two-scale realized volatility estimator as the measure of the volatility of high-frequency financial data. Two main models for volatility, Generalized Autoregressive Conditional Heteroscedastic (GARCH) and Heterogeneous Autoregressive (HAR), are evaluated and compared for the realized volatility forecast of four major stock indices high-frequency data. We also consider the measures of jump component and heteroskedasticity of the error in the extended HAR models. For the improvement of forecasting accuracy of realized volatility, this dissertation develops hybrid forecasting models combining the GARCH and HAR family models with the machine learning methods, Support Vector Regression(SVR), Extreme Gradient Boosting (XGBoost), Long Short-Term Memory (LSTM) and Transformer. We construct hybrid models using the outputs of the GARCH and HAR family models. In the empirical application, we demonstrate improvements of the hybrid models for one-day ahead realized volatility forecast accuracy. The results show that the hybrid LSTM and Transformer based models provide more accurate forecasts than the other models. In the financial markets, it is well accepted that the volatilities are time-varying correlated across the indices. We construct two portfolios, the Index portfolio and the Forex portfolio. The Index portfolio contains three major stock indices, and the Forex portfolio includes three major exchange rates. We model the conditional covariances of the two portfolios with BEKK, DCC-GARCH, and Vector HAR. The hybrid models combine the estimations of traditional multivariate models and the machine learning framework. Results of the study indicate that for one-day ahead volatility matrix forecasting, these hybrid models can achieve better performance than the traditional models for the two portfolios.
Handbook Of Financial Econometrics And Statistics
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Author : Cheng-Few Lee
language : en
Publisher: Springer
Release Date : 2014-09-28
Handbook Of Financial Econometrics And Statistics written by Cheng-Few Lee and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2014-09-28 with Business & Economics categories.
The Handbook of Financial Econometrics and Statistics provides, in four volumes and over 100 chapters, a comprehensive overview of the primary methodologies in econometrics and statistics as applied to financial research. Including overviews of key concepts by the editors and in-depth contributions from leading scholars around the world, the Handbook is the definitive resource for both classic and cutting-edge theories, policies, and analytical techniques in the field. Volume 1 (Parts I and II) covers all of the essential theoretical and empirical approaches. Volumes 2, 3, and 4 feature contributed entries that showcase the application of financial econometrics and statistics to such topics as asset pricing, investment and portfolio research, option pricing, mutual funds, and financial accounting research. Throughout, the Handbook offers illustrative case examples and applications, worked equations, and extensive references, and includes both subject and author indices.
Data Science For Economics And Finance
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Author : Sergio Consoli
language : en
Publisher: Springer Nature
Release Date : 2021
Data Science For Economics And Finance written by Sergio Consoli and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2021 with Application software categories.
This open access book covers the use of data science, including advanced machine learning, big data analytics, Semantic Web technologies, natural language processing, social media analysis, time series analysis, among others, for applications in economics and finance. In addition, it shows some successful applications of advanced data science solutions used to extract new knowledge from data in order to improve economic forecasting models. The book starts with an introduction on the use of data science technologies in economics and finance and is followed by thirteen chapters showing success stories of the application of specific data science methodologies, touching on particular topics related to novel big data sources and technologies for economic analysis (e.g. social media and news); big data models leveraging on supervised/unsupervised (deep) machine learning; natural language processing to build economic and financial indicators; and forecasting and nowcasting of economic variables through time series analysis. This book is relevant to all stakeholders involved in digital and data-intensive research in economics and finance, helping them to understand the main opportunities and challenges, become familiar with the latest methodological findings, and learn how to use and evaluate the performances of novel tools and frameworks. It primarily targets data scientists and business analysts exploiting data science technologies, and it will also be a useful resource to research students in disciplines and courses related to these topics. Overall, readers will learn modern and effective data science solutions to create tangible innovations for economic and financial applications.
Economic Analysis Of The Digital Economy
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Author : Avi Goldfarb
language : en
Publisher: University of Chicago Press
Release Date : 2015-05-08
Economic Analysis Of The Digital Economy written by Avi Goldfarb and has been published by University of Chicago Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2015-05-08 with Business & Economics categories.
There is a small and growing literature that explores the impact of digitization in a variety of contexts, but its economic consequences, surprisingly, remain poorly understood. This volume aims to set the agenda for research in the economics of digitization, with each chapter identifying a promising area of research. "Economics of Digitization "identifies urgent topics with research already underway that warrant further exploration from economists. In addition to the growing importance of digitization itself, digital technologies have some features that suggest that many well-studied economic models may not apply and, indeed, so many aspects of the digital economy throw normal economics in a loop. "Economics of Digitization" will be one of the first to focus on the economic implications of digitization and to bring together leading scholars in the economics of digitization to explore emerging research.
Volatility And Correlation
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Author : Riccardo Rebonato
language : en
Publisher: John Wiley & Sons
Release Date : 2005-07-08
Volatility And Correlation written by Riccardo Rebonato and has been published by John Wiley & Sons this book supported file pdf, txt, epub, kindle and other format this book has been release on 2005-07-08 with Business & Economics categories.
In Volatility and Correlation 2nd edition: The Perfect Hedger and the Fox, Rebonato looks at derivatives pricing from the angle of volatility and correlation. With both practical and theoretical applications, this is a thorough update of the highly successful Volatility & Correlation – with over 80% new or fully reworked material and is a must have both for practitioners and for students. The new and updated material includes a critical examination of the ‘perfect-replication’ approach to derivatives pricing, with special attention given to exotic options; a thorough analysis of the role of quadratic variation in derivatives pricing and hedging; a discussion of the informational efficiency of markets in commonly-used calibration and hedging practices. Treatment of new models including Variance Gamma, displaced diffusion, stochastic volatility for interest-rate smiles and equity/FX options. The book is split into four parts. Part I deals with a Black world without smiles, sets out the author’s ‘philosophical’ approach and covers deterministic volatility. Part II looks at smiles in equity and FX worlds. It begins with a review of relevant empirical information about smiles, and provides coverage of local-stochastic-volatility, general-stochastic-volatility, jump-diffusion and Variance-Gamma processes. Part II concludes with an important chapter that discusses if and to what extent one can dispense with an explicit specification of a model, and can directly prescribe the dynamics of the smile surface. Part III focusses on interest rates when the volatility is deterministic. Part IV extends this setting in order to account for smiles in a financially motivated and computationally tractable manner. In this final part the author deals with CEV processes, with diffusive stochastic volatility and with Markov-chain processes. Praise for the First Edition: “In this book, Dr Rebonato brings his penetrating eye to bear on option pricing and hedging.... The book is a must-read for those who already know the basics of options and are looking for an edge in applying the more sophisticated approaches that have recently been developed.” —Professor Ian Cooper, London Business School “Volatility and correlation are at the very core of all option pricing and hedging. In this book, Riccardo Rebonato presents the subject in his characteristically elegant and simple fashion...A rare combination of intellectual insight and practical common sense.” —Anthony Neuberger, London Business School
Eighth Periodic Monitoring Report On The Status Of Implementation Plans In Response To Board Endorsed Ieo Recommendations
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Author : International Monetary Fund
language : en
Publisher: International Monetary Fund
Release Date : 2017-06-23
Eighth Periodic Monitoring Report On The Status Of Implementation Plans In Response To Board Endorsed Ieo Recommendations written by International Monetary Fund and has been published by International Monetary Fund this book supported file pdf, txt, epub, kindle and other format this book has been release on 2017-06-23 with Business & Economics categories.
Monitoring Report (PMR) on the Status of Management Implementation Plans (MIPs) in Response to Board-Endorsed IEO Recommendations assesses the progress made over the last year on actions contained in the four MIPs arising from recent IEO evaluations, and another four for which individual management actions were classified as still “in progress” in the Seventh PMR. Overall, 34 of the 77 actions included in the eight MIPs covered in this PMR remain open. Progress on the actions envisaged in the management implementation plans has been somewhat uneven, with more progress being made on the most recent MIPs. Of the 19 actions that have been implemented over the past year, only three relate to the older management actions. Many of the older actions are more broadly worded, and in many instances have no clear timetable. The actions that are progressing more slowly also tend to involve fundamental changes to institutional culture and practices, and therefore require a continuous, long-term effort. In spite of the slower progress on the older actions, significant advances have been made in several key areas. These include: Fund-wide risk analysis and management; the mainstreaming of macro financial surveillance; training on financial sector topics and macro forecasting; acknowledgement, discussion, and dissemination of information on IMF forecasts; the shift towards increasing reliance on quota resources, relative to borrowing; and the approval of the new Statement of Principles and Best Practices in Self-Evaluation. In addition, the 2015 Staff Survey showed significant improvements in several indicators related to the Fund’s internal culture and institutional values. Overall, management and staff appear committed to ensuring that open actions remain on track. Progress on all open actions will be assessed in future PMRs.
Dynamic Models For Volatility And Heavy Tails
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Author : Andrew C. Harvey
language : en
Publisher: Cambridge University Press
Release Date : 2013-04-22
Dynamic Models For Volatility And Heavy Tails written by Andrew C. Harvey and has been published by Cambridge University Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2013-04-22 with Business & Economics categories.
The volatility of financial returns changes over time and, for the last thirty years, Generalized Autoregressive Conditional Heteroscedasticity (GARCH) models have provided the principal means of analyzing, modeling and monitoring such changes. Taking into account that financial returns typically exhibit heavy tails - that is, extreme values can occur from time to time - Andrew Harvey's new book shows how a small but radical change in the way GARCH models are formulated leads to a resolution of many of the theoretical problems inherent in the statistical theory. The approach can also be applied to other aspects of volatility. The more general class of Dynamic Conditional Score models extends to robust modeling of outliers in the levels of time series and to the treatment of time-varying relationships. The statistical theory draws on basic principles of maximum likelihood estimation and, by doing so, leads to an elegant and unified treatment of nonlinear time-series modeling.