Forecasting Expected Returns in the Financial Markets Book

Forecasting Expected Returns in the Financial Markets


  • Author : Stephen Satchell
  • Publisher : Elsevier
  • Release Date : 2011-04-08
  • Genre: Business & Economics
  • Pages : 304
  • ISBN 10 : 9780080550671

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Forecasting Expected Returns in the Financial Markets Excerpt :

Forecasting returns is as important as forecasting volatility in multiple areas of finance. This topic, essential to practitioners, is also studied by academics. In this new book, Dr Stephen Satchell brings together a collection of leading thinkers and practitioners from around the world who address this complex problem using the latest quantitative techniques. *Forecasting expected returns is an essential aspect of finance and highly technical *The first collection of papers to present new and developing techniques *International authors present both academic and practitioner perspectives

Forecasting Volatility in the Financial Markets Book

Forecasting Volatility in the Financial Markets


  • Author : Stephen Satchell
  • Publisher : Elsevier
  • Release Date : 2011-02-24
  • Genre: Business & Economics
  • Pages : 432
  • ISBN 10 : 9780080471426

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Forecasting Volatility in the Financial Markets Excerpt :

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 define the different models of volatility and return. Editors John Knight and Stephen Satchell have brought together an impressive array of contributors who present research from their area of specialization related to volatility forecasting. Readers with an understanding of volatility measures and risk management strategies will benefit from this collection of up-to-date chapters on the latest techniques in forecasting volatility. Chapters new to this third edition: * What good is a volatility model? Engle and Patton * Applications for portfolio variety Dan diBartolomeo * A comparison of the properties of realized variance for the FTSE 100 and FTSE 250 equity indices Rob Cornish * Volatility modeling and forecasting in finance Xiao and Aydemir * An investigation of the relative performance of GARCH models versus simple rules in forecasting volatility Thomas A. Silvey * Leading thinkers present newest research on volatility forecasting *International authors cover a broad array of subjects related to volatility forecasting *Assumes basic knowledge of volatility, financial mathematics, and modelling

Expected Returns Book
Score: 5
From 1 Ratings

Expected Returns


  • Author : Antti Ilmanen
  • Publisher : John Wiley & Sons
  • Release Date : 2011-04-20
  • Genre: Business & Economics
  • Pages : 352
  • ISBN 10 : 1119990777

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Expected Returns Excerpt :

This comprehensive reference delivers a toolkit for harvesting market rewards from a wide range of investments. Written by a world-renowned industry expert, the reference discusses how to forecast returns under different parameters. Expected returns of major asset classes, investment strategies, and the effects of underlying risk factors such as growth, inflation, liquidity, and different risk perspectives, are also explained. Judging expected returns requires balancing historical returns with both theoretical considerations and current market conditions. Expected Returns provides extensive empirical evidence, surveys of risk-based and behavioral theories, and practical insights.

Expected Returns Book

Expected Returns


  • Author : Antti Ilmanen
  • Publisher : John Wiley & Sons
  • Release Date : 2011-03-14
  • Genre: Business & Economics
  • Pages : 592
  • ISBN 10 : 9781119990727

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Expected Returns Excerpt :

This comprehensive reference delivers a toolkit for harvesting market rewards from a wide range of investments. Written by a world-renowned industry expert, the reference discusses how to forecast returns under different parameters. Expected returns of major asset classes, investment strategies, and the effects of underlying risk factors such as growth, inflation, liquidity, and different risk perspectives, are also explained. Judging expected returns requires balancing historical returns with both theoretical considerations and current market conditions. Expected Returns provides extensive empirical evidence, surveys of risk-based and behavioral theories, and practical insights.

Forecasting Volatility in the Financial Markets Book
Score: 4.5
From 2 Ratings

Forecasting Volatility in the Financial Markets


  • Author : John Knight
  • Publisher : Butterworth-Heinemann
  • Release Date : 2002
  • Genre: Business & Economics
  • Pages : 407
  • ISBN 10 : 0750655151

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Forecasting Volatility in the Financial Markets Excerpt :

'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 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. * Traders will profit by learning to arbitrage opportunities and modify their strategies to account for volatility. * Investment managers will be able to enhance their asset allocation strategies with an improved understanding of likely risks and returns. * Risk managers will understand how to improve their measurement systems and forecasts, enhancing their risk management models and controls. * Derivative specialists will gain an in-depth understanding of volatility that they can use to improve their pricing models. * Students and academics will find the collection of papers an invaluable overview of this field. 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

Updating Expected Returns Based on Consensus Forecasts Book

Updating Expected Returns Based on Consensus Forecasts


  • Author : John Crombez
  • Publisher : Unknown
  • Release Date : 2001
  • Genre: Uncategoriezed
  • Pages : 29
  • ISBN 10 : OCLC:1290403150

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Updating Expected Returns Based on Consensus Forecasts Excerpt :

Investor behavior can explain to some extent the stock market anomalies from a psychological viewpoint. Recent literature suggests a lot of models without testing predictability implied by the models and without a discussion of implications and limitations that are implied by the design. Mostly, these models are descriptive. In these designs, the question about relevant normative models is left aside. In this paper we propose a normative model that allows empirical testing of whether the way investors should behave given the information is useful in making judgments in financial markets. Contrary to most papers, we apply individual priors to form a judgment about the future price change of each asset at each point in time. These priors are considered as the expert opinion and are given by the one-year conensus forecast of earnings yield as provided by analysts. This design allows tests of the predictions for a normative setting using actual market data. Comparing Bayes' rule to a decisions by a price trader, we find that economic loss is lower for the price trader than for the Bayesian trader under several specifications. However, using expert information in the Bayes' rule leads to better predictions for stocks that do not have high-risk characteristics.

Stock Return Predictability Book

Stock Return Predictability


  • Author : Arthur Ritter
  • Publisher : GRIN Verlag
  • Release Date : 2015-05-27
  • Genre: Business & Economics
  • Pages : 15
  • ISBN 10 : 9783656968924

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Stock Return Predictability Excerpt :

Research Paper (postgraduate) from the year 2015 in the subject Business economics - Banking, Stock Exchanges, Insurance, Accounting, grade: 17 (1,3), University of St Andrews (School of Management), course: Investment and Portfolio Management, language: English, abstract: Empirical evidence of stock return predictability obtained by financial ratios or macroeconomic factors has received substantial attention and remains a controversial topic to date. This is no surprise given that the existence of return predictability is not only of interest to practitioners but also introduces severe implications for financial models of risk and return. Founded on the assumption of efficient capital markets, research on capital asset pricing models has instigated this emergence of stock return predictability factors. Analysing these factors categorically, this paper will provide a balanced discussion of advocates as well as sceptics of stock return predictability. This essay will commence by firstly outlining the fundamental assumptions of an efficient capital market and its implications for return predictability. Subsequently, a thorough focus will be placed on the most significant predictability factors, including fundamental financial ratios and macroeconomic indicators as well as the validity of sampling methods used to attain return forecasts. Lastly this essay will reflect on the findings while proposing areas of further research.

Machine Learning for Asset Management Book

Machine Learning for Asset Management


  • Author : Emmanuel Jurczenko
  • Publisher : John Wiley & Sons
  • Release Date : 2020-10-06
  • Genre: Business & Economics
  • Pages : 460
  • ISBN 10 : 9781786305442

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Machine Learning for Asset Management Excerpt :

This new edited volume consists of a collection of original articles written by leading financial economists and industry experts in the area of machine learning for asset management. The chapters introduce the reader to some of the latest research developments in the area of equity, multi-asset and factor investing. Each chapter deals with new methods for return and risk forecasting, stock selection, portfolio construction, performance attribution and transaction costs modeling. This volume will be of great help to portfolio managers, asset owners and consultants, as well as academics and students who want to improve their knowledge of machine learning in asset management.

A Practical Guide to Forecasting Financial Market Volatility Book

A Practical Guide to Forecasting Financial Market Volatility


  • Author : Ser-Huang Poon
  • Publisher : John Wiley & Sons
  • Release Date : 2005-08-19
  • Genre: Business & Economics
  • Pages : 236
  • ISBN 10 : 9780470856154

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A Practical Guide to Forecasting Financial Market Volatility 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.

Financial Risk Forecasting Book

Financial Risk Forecasting


  • Author : Jon Danielsson
  • Publisher : John Wiley & Sons
  • Release Date : 2011-04-20
  • Genre: Business & Economics
  • Pages : 296
  • ISBN 10 : 9781119977117

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Financial Risk Forecasting Excerpt :

Financial Risk Forecasting is a complete introduction to practical quantitative risk management, with a focus on market risk. Derived from the authors teaching notes and years spent training practitioners in risk management techniques, it brings together the three key disciplines of finance, statistics and modeling (programming), to provide a thorough grounding in risk management techniques. Written by renowned risk expert Jon Danielsson, the book begins with an introduction to financial markets and market prices, volatility clusters, fat tails and nonlinear dependence. It then goes on to present volatility forecasting with both univatiate and multivatiate methods, discussing the various methods used by industry, with a special focus on the GARCH family of models. The evaluation of the quality of forecasts is discussed in detail. Next, the main concepts in risk and models to forecast risk are discussed, especially volatility, value-at-risk and expected shortfall. The focus is both on risk in basic assets such as stocks and foreign exchange, but also calculations of risk in bonds and options, with analytical methods such as delta-normal VaR and duration-normal VaR and Monte Carlo simulation. The book then moves on to the evaluation of risk models with methods like backtesting, followed by a discussion on stress testing. The book concludes by focussing on the forecasting of risk in very large and uncommon events with extreme value theory and considering the underlying assumptions behind almost every risk model in practical use – that risk is exogenous – and what happens when those assumptions are violated. Every method presented brings together theoretical discussion and derivation of key equations and a discussion of issues in practical implementation. Each method is implemented in both MATLAB and R, two of the most commonly used mathematical programming languages for risk forecasting with which the reader can implement the models illustrated in the book. The boo

Empirical Asset Pricing Book

Empirical Asset Pricing


  • Author : Wayne Ferson
  • Publisher : MIT Press
  • Release Date : 2019-03-12
  • Genre: Business & Economics
  • Pages : 496
  • ISBN 10 : 9780262039376

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Empirical Asset Pricing Excerpt :

An introduction to the theory and methods of empirical asset pricing, integrating classical foundations with recent developments. This book offers a comprehensive advanced introduction to asset pricing, the study of models for the prices and returns of various securities. The focus is empirical, emphasizing how the models relate to the data. The book offers a uniquely integrated treatment, combining classical foundations with more recent developments in the literature and relating some of the material to applications in investment management. It covers the theory of empirical asset pricing, the main empirical methods, and a range of applied topics. The book introduces the theory of empirical asset pricing through three main paradigms: mean variance analysis, stochastic discount factors, and beta pricing models. It describes empirical methods, beginning with the generalized method of moments (GMM) and viewing other methods as special cases of GMM; offers a comprehensive review of fund performance evaluation; and presents selected applied topics, including a substantial chapter on predictability in asset markets that covers predicting the level of returns, volatility and higher moments, and predicting cross-sectional differences in returns. Other chapters cover production-based asset pricing, long-run risk models, the Campbell-Shiller approximation, the debate on covariance versus characteristics, and the relation of volatility to the cross-section of stock returns. An extensive reference section captures the current state of the field. The book is intended for use by graduate students in finance and economics; it can also serve as a reference for professionals.

Advances in Quantitative Asset Management Book

Advances in Quantitative Asset Management


  • Author : Christian Dunis
  • Publisher : Springer Science & Business Media
  • Release Date : 2012-12-06
  • Genre: Business & Economics
  • Pages : 342
  • ISBN 10 : 9781461543893

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Advances in Quantitative Asset Management Excerpt :

Advances in Quantitative Asset Management contains selected articles which, for the most part, were presented at the `Forecasting Financial Markets' Conference. `Forecasting Financial Markets' is an international conference on quantitative finance which is held in London in May every year. Since its inception in 1994, the conference has grown in scope and stature to become a key international meeting point for those interested in quantitative finance, with the participation of prestigious academic and research institutions from all over the world, including major central banks and quantitative fund managers. The editor has chosen to concentrate on advances in quantitative asset management and, accordingly, the papers in this book are organized around two major themes: advances in asset allocation and portfolio management, and modelling risk, return and correlation.

Neural Networks and the Financial Markets Book

Neural Networks and the Financial Markets


  • Author : Jimmy Shadbolt
  • Publisher : Springer Science & Business Media
  • Release Date : 2012-12-06
  • Genre: Computers
  • Pages : 273
  • ISBN 10 : 9781447101512

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Neural Networks and the Financial Markets Excerpt :

This volume looks at financial prediction from a broad range of perspectives. It covers: - the economic arguments - the practicalities of the markets - how predictions are used - how predictions are made - how predictions are turned into something usable (asset locations) It combines a discussion of standard theory with state-of-the-art material on a wide range of information processing techniques as applied to cutting-edge financial problems. All the techniques are demonstrated with real examples using actual market data, and show that it is possible to extract information from very noisy, sparse data sets. Aimed primarily at researchers in financial prediction, time series analysis and information processing, this book will also be of interest to quantitative fund managers and other professionals involved in financial prediction.