Download or read book Localized and Long Memory Approaches to Forecasting Market Volatility written by Anatoly Nigmatulin and published by . This book was released on 2011 with total page 70 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Download or read book A Practical Guide to Forecasting Financial Market Volatility written by Ser-Huang Poon and published by John Wiley & Sons. This book was released on 2005-08-19 with total page 236 pages. Available in PDF, EPUB and Kindle. Book excerpt: Financial market volatility forecasting is one of today's most important areas of expertise for professionals and academics in investment, option pricing, and financial market regulation. While many books address financial market modelling, no single book is devoted primarily to the exploration of volatility forecasting and the practical use of forecasting models. A Practical Guide to Forecasting Financial Market Volatility provides practical guidance on this vital topic through an in-depth examination of a range of popular forecasting models. Details are provided on proven techniques for building volatility models, with guide-lines for actually using them in forecasting applications.
Download or read book Interdisciplinary Approaches to Understanding and Forecasting Volatility written by Irena Vodenska-Chitkushev and published by . This book was released on 2009 with total page 232 pages. Available in PDF, EPUB and Kindle. Book excerpt: Abstract: Volatility is a measure of financial market risk and understanding the statistical characteristics of volatility is essential for effective risk management. In this thesis we use statistical physics approaches to analyze the stochastic nature of financial markets and explore the existence of a universal law that governs the financial market system. Such universal law will allow us to study the statistical characteristics of extreme events for which the data is limited, by analyzing more common events where the data is abundant. We use the analysis of return intervals to study the volatility of the S&P 500 Index for different periods between 1984 and 2009, and explore the existence of memory and scaling in the return intervals datasets. Our results show that the long memory in volatility leads to a clustering of above-median as well as below-median return intervals. In addition, we find that the short return intervals form larger clusters compared to the long return intervals. We also study specific market crashes and the behavior of the market after such crashes. We find that the crashes are characterized by the Omori law, which describes the decay in the rate of aftershocks of a given size. We find that within the aftercrash period there are smaller shocks that themselves constitute Omori processes on smaller scales, similar to the Omori process after the large crash. To further analyze the statistical characteristics of the S&P 500 index data, we compare the empirical results with two models, autoregressive moving average - fractionally integrated generalized autoregressive conditional heteroskedastic (ARMA-FIGARCH) model and fractional Brownian motion (fBm) model. We observe that in general, the ARMA-FIGARCH model is statistically different from the market behavior for intermediate thresholds, and the fBm model is statistically different from the market data for small and large thresholds. Also, both ARMA-FIGARCH and fBm capture the long-term dependence in return intervals to a certain extent, but only fBm accounts for the scaling. Finally, we propose a novel method for forecasting high and low volatility periods based on the long memory in the S&P 500 return intervals. We then analyze different derivative-based strategies and compare them with the "long only" strategy where only long equity positions are held and no derivatives are used. Our findings suggest that a protective put option strategy significantly outperforms the "long only" strategy during high volatility periods, while it underperforms the "long only" strategy during periods of low volatility. On the other hand, the covered call strategy does not offer proper protection of the portfolio for high volatility periods, and has limited upside potential when volatility is low.
Download or read book Volatility in Financial Markets written by Aleksandr Pereverzin 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 Source of Long Memory in Volatility written by Namwon Hyung and published by . This book was released on 2006 with total page 38 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Download or read book Forecasting Volatility and Volume in the Tokyo Stock Market written by and published by . This book was released on 2004 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt:
Download or read book Volatility Forecasting written by Torben Gustav Andersen and published by . This book was released on 2005 with total page 130 pages. Available in PDF, EPUB and Kindle. Book excerpt: Volatility has been one of the most active and successful areas of research in time series econometrics and economic forecasting in recent decades. This chapter provides a selective survey of the most important theoretical developments and empirical insights to emerge from this burgeoning literature, with a distinct focus on forecasting applications. Volatility is inherently latent, and Section 1 begins with a brief intuitive account of various key volatility concepts. Section 2 then discusses a series of different economic situations in which volatility plays a crucial role, ranging from the use of volatility forecasts in portfolio allocation to density forecasting in risk management. Sections 3, 4 and 5 present a variety of alternative procedures for univariate volatility modeling and forecasting based on the GARCH, stochastic volatility and realized volatility paradigms, respectively. Section 6 extends the discussion to the multivariate problem of forecasting conditional covariances and correlations, and Section 7 discusses volatility forecast evaluation methods in both univariate and multivariate cases. Section 8 concludes briefly.
Download or read book Modelling Long Memory in Stock Market Volatility written by Zacharias G. Psaradakis and published by . This book was released on 1995 with total page 21 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Download or read book Volatility Forecasting written by Jakob Guldbæk Mikkelsen and published by . This book was released on 2013 with total page 88 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Download or read book Long Memory in the Volatility of Indian Financial Market An Empirical Analysis Based on Indian Data written by Dilip Kumar and published by Anchor Academic Publishing (aap_verlag). This book was released on 2014-04-10 with total page 105 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book examines the long memory characteristics in the volatility of the Indian stock market, the Indian exchange rates and the Indian banking sector. This book also reviews the chain of approaches to estimate the long memory parameter. The long memory characteristics of the financial time series are widely studied and have implications for various economics and finance theories. The most important financial implication is related to the violation of the weak-form of market efficiency which encourages the traders, investors and portfolio managers to develop models for making predictions and to construct and implement speculative trading and investment strategies. In an efficient market, the price of an asset should follow a random walk process in which the price change is unaffected by ist lagged price changes and has no memory.
Download or read book Long Memory Modeling and Forecasting of the Returns and Volatility of Exchange Traded Notes ETNs written by and published by . This book was released on 2014 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt:
Download or read book Forecasting Volatility with Time Varying Leverage and Volatility of Volatility Effects written by Leopoldo Catania and published by . This book was released on 2018 with total page 29 pages. Available in PDF, EPUB and Kindle. Book excerpt: The prediction of volatility is of primary importance for business applications in risk management, asset allocation and pricing of derivative instruments. This paper proposes a novel measurement model which takes into consideration the possibly time-varying interaction of realized volatility and asset returns, according to a bivariate model aiming at capturing the main stylised facts: (i) the long memory of the volatility process, (ii) the heavy-tailedness of the returns distribution, and (iii) the negative dependence of volatility and daily market returns. We assess the relevance of "volatility in volatility" and time-varying "leverage" effects in the out-of-sample forecasting performance of the model, and evaluate the density forecasts of the future level of market volatility. The empirical results illustrate that our speci fication can outperform the benchmark HAR-RV, both in terms of point and density forecasts.
Download or read book Time Series Analysis with Long Memory in View written by Uwe Hassler and published by John Wiley & Sons. This book was released on 2018-09-07 with total page 292 pages. Available in PDF, EPUB and Kindle. Book excerpt: Provides a simple exposition of the basic time series material, and insights into underlying technical aspects and methods of proof Long memory time series are characterized by a strong dependence between distant events. This book introduces readers to the theory and foundations of univariate time series analysis with a focus on long memory and fractional integration, which are embedded into the general framework. It presents the general theory of time series, including some issues that are not treated in other books on time series, such as ergodicity, persistence versus memory, asymptotic properties of the periodogram, and Whittle estimation. Further chapters address the general functional central limit theory, parametric and semiparametric estimation of the long memory parameter, and locally optimal tests. Intuitive and easy to read, Time Series Analysis with Long Memory in View offers chapters that cover: Stationary Processes; Moving Averages and Linear Processes; Frequency Domain Analysis; Differencing and Integration; Fractionally Integrated Processes; Sample Means; Parametric Estimators; Semiparametric Estimators; and Testing. It also discusses further topics. This book: Offers beginning-of-chapter examples as well as end-of-chapter technical arguments and proofs Contains many new results on long memory processes which have not appeared in previous and existing textbooks Takes a basic mathematics (Calculus) approach to the topic of time series analysis with long memory Contains 25 illustrative figures as well as lists of notations and acronyms Time Series Analysis with Long Memory in View is an ideal text for first year PhD students, researchers, and practitioners in statistics, econometrics, and any application area that uses time series over a long period. It would also benefit researchers, undergraduates, and practitioners in those areas who require a rigorous introduction to time series analysis.
Download or read book Risk Management written by Nerija Banaitiene and published by BoD – Books on Demand. This book was released on 2012-09-12 with total page 600 pages. Available in PDF, EPUB and Kindle. Book excerpt: Every business and decision involves a certain amount of risk. Risk might cause a loss to a company. This does not mean, however, that businesses cannot take risks. As disengagement and risk aversion may result in missed business opportunities, which will lead to slower growth and reduced prosperity of a company. In today's increasingly complex and diverse environment, it is crucial to find the right balance between risk aversion and risk taking. To do this it is essential to understand the complex, out of the whole range of economic, technical, operational, environmental and social risks associated with the company's activities. However, risk management is about much more than merely avoiding or successfully deriving benefit from opportunities. Risk management is the identification, assessment, and prioritization of risks. Lastly, risk management helps a company to handle the risks associated with a rapidly changing business environment.
Download or read book Long memory in volatility modelling and forecasting in the wavelet domain written by Apostolos Noutsos and published by . This book was released on 2009 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt:
Download or read book Forecasting Realised Volatility Using a Long Memory Stochastic Volatility Model written by and published by . This book was released on 2003 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt:
Download or read book Fractal Approaches for Modeling Financial Assets and Predicting Crises written by Nekrasova, Inna and published by IGI Global. This book was released on 2018-02-09 with total page 324 pages. Available in PDF, EPUB and Kindle. Book excerpt: In an ever-changing economy, market specialists strive to find new ways to evaluate the risks and potential reward of economic ventures. They start by assessing the importance of human reaction during the economic planning process and put together systems to measure financial markets and their longevity. Fractal Approaches for Modeling Financial Assets and Predicting Crises is a critical scholarly resource that examines the fractal structure and long-term memory of the financial markets in order to predict prices of financial assets and financial crises. Featuring coverage on a broad range of topics, such as computational process models, chaos theory, and game theory, this book is geared towards academicians, researchers, and students seeking current research on pricing and predicting financial crises.
