Quantitative Finance
8 total works
The practical aspects of optimization rarely receive global, balanced examinations. Stephen Satchell’s nuanced assembly of technical presentations about optimization packages (by their developers) and about current optimization practice and theory (by academic researchers) makes available highly practical solutions to our post-liquidity bubble environment. The commercial chapters emphasize algorithmic elements without becoming sales pitches, and the academic chapters create context and explore development opportunities. Together they offer an incisive perspective that stretches toward new products, new techniques, and new answers in quantitative finance.
Return Distributions in Finance
by Emeritus Professor of Economics and Fellow of St Edmund Hall John Knight and Stephen Satchell
Published 1 January 2000
Quantitative methods have revolutionised the area of trading, regulation, risk management, portfolio construction, asset pricing and treasury activities, and governmental activity such as central banking.
One of the original contributions in this area is the classic by Cootner entitled 'The Random Nature of Stock Market Prices'. This work investigated the statistical properties of asset prices and was one of the first works to investigate this area in a rigorous manner.
Much has happened in this field in the last 35 years and 'Return Distributions in Finance' contains much new information that reflects this huge growth.
The authors combined experience reflects not only the new theory but also the new practice in this fascinating area. The rise of financial engineering now allows us to change the nature of asset returns to whatever pattern we desire, albeit at a cost. Benefits and costs can only be understood if we understand the underlying processes. 'Return Distributions in Finance' allows us to gain that understanding.
One of the original contributions in this area is the classic by Cootner entitled 'The Random Nature of Stock Market Prices'. This work investigated the statistical properties of asset prices and was one of the first works to investigate this area in a rigorous manner.
Much has happened in this field in the last 35 years and 'Return Distributions in Finance' contains much new information that reflects this huge growth.
The authors combined experience reflects not only the new theory but also the new practice in this fascinating area. The rise of financial engineering now allows us to change the nature of asset returns to whatever pattern we desire, albeit at a cost. Benefits and costs can only be understood if we understand the underlying processes. 'Return Distributions in Finance' allows us to gain that understanding.
Quantitative methods have revolutionized the area of trading, regulation, risk management, portfolio construction, asset pricing and treasury activities, and governmental activity such as central banking to name but some of the applications. Downside-risk, as a quantitative method, is an accurate measurement of investment risk, because it captures the risk of not accomplishing the investor's goal.
'Downside Risk in Financial Markets' demonstrates how downside-risk can produce better results in performance measurement and asset allocation than variance modelling. Theory, as well as the practical issues involved in its implementation, is covered and the arguments put forward emphatically show the superiority of downside risk models to variance models in terms of risk measurement and decision making. Variance considers all uncertainty to be risky. Downside-risk only considers returns below that needed to accomplish the investor's goal, to be risky.
Risk is one of the biggest issues facing the financial markets today. 'Downside Risk in Financial Markets' outlines the major issues for Investment Managers and focuses on "downside-risk" as a key activity in managing risk in investment/portfolio management. Managing risk is now THE paramount topic within the financial sector and recurring losses through the 1990s has shocked financial institutions into placing much greater emphasis on risk management and control.
Free Software Enclosed
To help you implement the knowledge you will gain from reading this book, a CD is enclosed that contains free software programs that were previously only available to institutional investors under special licensing agreement to The pension Research Institute. This is our contribution to the advancement of professionalism in portfolio management.
The Forsey-Sortino model is an executable program that:
1. Runs on any PC without the need of any additional software.
2. Uses the bootstrap procedure developed by Dr. Bradley Effron at Stanford University to uncover what could have happened, instead of relying only on what did happen in the past. This is the best procedure we know of for describing the nature of uncertainty in financial markets.
3. Fits a three parameter lognormal distribution to the bootstrapped data to allow downside risk to be calculated from a continuous distribution. This improves the efficacy of the downside risk estimates.
4. Calculates upside potential and downside risk from monthly returns on any portfolio manager.
5. Calculates upside potential and downside risk from any user defined distribution.
Forsey-Sortino Source Code:
1. The source code, written in Visual Basic 5.0, is provided for institutional investors who want to add these calculations to their existing financial services.
2. No royalties are required for this source code, providing institutions inform clients of the source of these calculations. A growing number of services are now calculating downside risk in a manner that we are not comfortable with. Therefore, we want investors to know when downside risk and upside potential are calculated in accordance with the methodology described in this book.
Riddles Spreadsheet:
1. Neil Riddles, former Senior Vice President and Director of Performance Analysis at Templeton Global Advisors, now COO at Hansberger Global Advisors Inc., offers a free spreadsheet in excel format.
2. The spreadsheet calculates downside risk and upside potential relative to the returns on an index
'Downside Risk in Financial Markets' demonstrates how downside-risk can produce better results in performance measurement and asset allocation than variance modelling. Theory, as well as the practical issues involved in its implementation, is covered and the arguments put forward emphatically show the superiority of downside risk models to variance models in terms of risk measurement and decision making. Variance considers all uncertainty to be risky. Downside-risk only considers returns below that needed to accomplish the investor's goal, to be risky.
Risk is one of the biggest issues facing the financial markets today. 'Downside Risk in Financial Markets' outlines the major issues for Investment Managers and focuses on "downside-risk" as a key activity in managing risk in investment/portfolio management. Managing risk is now THE paramount topic within the financial sector and recurring losses through the 1990s has shocked financial institutions into placing much greater emphasis on risk management and control.
Free Software Enclosed
To help you implement the knowledge you will gain from reading this book, a CD is enclosed that contains free software programs that were previously only available to institutional investors under special licensing agreement to The pension Research Institute. This is our contribution to the advancement of professionalism in portfolio management.
The Forsey-Sortino model is an executable program that:
1. Runs on any PC without the need of any additional software.
2. Uses the bootstrap procedure developed by Dr. Bradley Effron at Stanford University to uncover what could have happened, instead of relying only on what did happen in the past. This is the best procedure we know of for describing the nature of uncertainty in financial markets.
3. Fits a three parameter lognormal distribution to the bootstrapped data to allow downside risk to be calculated from a continuous distribution. This improves the efficacy of the downside risk estimates.
4. Calculates upside potential and downside risk from monthly returns on any portfolio manager.
5. Calculates upside potential and downside risk from any user defined distribution.
Forsey-Sortino Source Code:
1. The source code, written in Visual Basic 5.0, is provided for institutional investors who want to add these calculations to their existing financial services.
2. No royalties are required for this source code, providing institutions inform clients of the source of these calculations. A growing number of services are now calculating downside risk in a manner that we are not comfortable with. Therefore, we want investors to know when downside risk and upside potential are calculated in accordance with the methodology described in this book.
Riddles Spreadsheet:
1. Neil Riddles, former Senior Vice President and Director of Performance Analysis at Templeton Global Advisors, now COO at Hansberger Global Advisors Inc., offers a free spreadsheet in excel format.
2. The spreadsheet calculates downside risk and upside potential relative to the returns on an index
In this book, Editors Fishwick and Satchell present a unified view of portfolio investment risk. Although the emphasis in on equity investment, the book also addresses fixed income and multi-asset investment. These issues are currently of great importance as the financial industry grapples with the challenge or risk management in a volatile and rapidly evolving world. Chapters within the book are authored by both academics and practitioners to ensure comprehensive coverage of the latest methods in this area. The unifying theme of this work is that the effective analysis and management of investment risk requires a combination of rigorous quantitative methodology, a sympathetic understanding of theory, and a strong appreciation of real-world practicalities. It provides practical guidance on the latest developments in investment risk analysis. There is full coverage of the latest cutting-edge research on measuring portfolio risk, alternatives to mean variance analysis, and linear multi-factor models. Combination of academics and practitioners provide a comprehensive overview.
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.
Analytics of Risk Model Validation
by George A Christodoulakis and Stephen Satchell
Published 20 August 2008
Performance Measurement in Finance
by Emeritus Professor of Economics and Fellow of St Edmund Hall John Knight
Published 1 January 2002
The distinction between out-performance of an Investment fund or plan manager vs rewards for taking risks is at the heart of all discussions on Investment fund performance measurement of fund managers. This issue is not always well-understood and the notion of risk adjusting performance is not universally accepted. Performance Measurement in Finance addresses this central issue.
The topics covered include evaluation of investment fund management, evaluation of the investment fund itself, and stock selection performance. The book also surveys and critiques existing methodologies of performance measurement and covers new innovative approaches to performance measurement. The contributors to the text include both academics and practitioners providing comprehensive coverage of the topic areas.
Performance Measurement in Finance is all about how to effectively measure financial performance of the fund manager and investment house managers, what measures need to be put in place and technically what works and what doesn't. It covers risk, and what's acceptable and what isn't, how, in short, to manage risk.
The topics covered include evaluation of investment fund management, evaluation of the investment fund itself, and stock selection performance. The book also surveys and critiques existing methodologies of performance measurement and covers new innovative approaches to performance measurement. The contributors to the text include both academics and practitioners providing comprehensive coverage of the topic areas.
Performance Measurement in Finance is all about how to effectively measure financial performance of the fund manager and investment house managers, what measures need to be put in place and technically what works and what doesn't. It covers risk, and what's acceptable and what isn't, how, in short, to manage risk.
Forecasting Volatility in the Financial Markets
by Emeritus John Knight and Stephen Satchell
Published 19 February 2007
Forecasting Volatility in the Financial Markets, Third Edition 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
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