We compare volatility forecasting performance of two main approaches; historical volatility models and volatility implied from options. Forecasting results are compared across different asset classes and geographical regions. This timely volume is one of the first to draw on a range of international authorities who offer their expertise on market volatility in developed, emerging, and frontier economies.
The expert contributors cover stock market volatility modeling, portfolio management, hedge fund volatility, and volatility in developed countries and emerging markets. They present some of the vocational aspects, emphasizing the equity markets.
It also discusses recent trends in forecasting volatility, along with the newly cultivated trading platform of volatility derivatives. Given the current state of high levels of volatility in global stock markets, money managers, financial institutions, investment banks, financial analysts, and others need to improve their understanding of volatility. Examining key aspects of stock market volatility, this comprehensive reference offers novel suggestions for accurately assessing the field. The volatility has been one of the cores of the financial theory research, in addition to the futures market is an important part of modern financial markets, the futures market volatility is an important part of the theory of financial markets research.
The global financial crisis has reopened discussion surrounding the use of appropriate theoretical financial frameworks to reflect the current economic climate. There is a need for more sophisticated analytical concepts which take into account current quantitative changes and unprecedented turbulence in the financial markets.
This book provides a comprehensive guide to the quantitative analysis of high frequency financial data in the light of current events and contemporary issues, using the latest empirical research and theory.
It highlights and explains the shortcomings of theoretical frameworks and provides an explanation of high-frequency theory, emphasising ways in which to critically apply this knowledge within a financial context. Modelling and Forecasting High Frequency Financial Data combines traditional and updated theories and applies them to real-world financial market situations. It will be a valuable and accessible resource for anyone wishing to understand quantitative analysis and modelling in current financial markets.
Author : Robert Schott Publisher : diplom. Inhaltsangabe:Introduction: Volatility is a crucial factor widely followed in the financial world. The year was in several respects a crucial year for implicit volatility.
The breakdown of the Bretton-Wood-System paved the way for derivative instruments, because of the beginning era of floating currencies. Especially since volatility has become a tremendously debated topic in financial literature with continually new insights in short-time periods.
Volatility is a central feature of option-pricing models and emerged per se as an independent asset class for investment purposes. The implicit volatility, the topic of the thesis, is a market indicator widely used by all option market practitioners.
In the thesis the focus lies on the implicit implied volatility IV. It is the estimation of the volatility that perfectly explains the option price, given all other variables, including the price of the underlying asset in context of the BS model.
At the start the BS model, which is the theoretical basic of model-specific IV models, and its variations are discussed. In the concept of volatility IV is defined and the way it is computed is given as well as a look on historical volatility. Afterwards the implied volatility surface IVS is presented, which is a non-flat surface, a contradiction to the ideal BS assumptions.
Furthermore, reasons of the change of the implied volatility function IVF and the term structure are discussed. The model specific IV model is then compared to other possible volatility forecast models. To ensure a good [ Knight,Stephen Satchell.
Forecasting Volatility Stephen Figlewski. Financial Risk Forecasting Jon Danielsson. Volatility and Correlation Riccardo Rebonato. Multifractal Volatility Laurent E.
Join over It then uses a technical survey to explain the different ways to measure risk and define the different models of volatility and return. The editors have brought together a set of contributors that give the reader a firm grounding in relevant theory and research and an insight into the cutting edge techniques applied in this field of the financial markets.
This book is of particular relevance to anyone who wants to understand dynamic areas of the financial markets. This book is of particular relevance to those wanting to understand the dynamic areas of volatility modeling and forecasting of the financial marketsProvides the latest research and techniques for Traders, Investment Managers, Risk Managers and Derivative Specialists wishing to manage their downside risk exposure Current research on the key forecasting methods to use in risk management, including two new chapters.
It then uses a technical survey to explain the different ways to measure. This new edition of Forecasting Volatility in the Financial Markets 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. Download or read online Forecasting Volatility written by Stephen Figlewski, published by Unknown which was released on Evidence exists that option prices produce biased forecasts of future volatility across a wide variety of options markets.
This paper presents two main results. First, approximately half of the … Expand. View 3 excerpts, references background. The results indicate that the implied volatility is an upward biased … Expand. The Informational Content of Implied Volatility. Implied volatility is widely believed to be informationally superior to historical volatility, because it is the "markets" forecast of future volatility. Predicting Volatility in the Foreign Exchange Market.
Measures of volatility implied in option prices are widely believed to be the best available volatility forecasts. In this article, we examine the information content and predictive power of implied … Expand. Highly Influential. View 4 excerpts, references background.
Forecasting financial market volatility: Sample frequency vis-a-vis forecast horizon. Abstract This paper explores the return volatility predictability inherent in high-frequency speculative returns.
Our analysis focuses on a refinement of the more traditional volatility measures, the … Expand. View 2 excerpts, references methods and background.
Forecasting Volatility in the Financial Markets. This new edition of Forecasting Volatility in the Financial Markets assumes that the reader has a firm grounding in the key principles and methods of understanding volatility measurement and builds … Expand. View 1 excerpt, references background.
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