Applied Quantitative Methods for Trading and Investment

This much–needed book, from a selection of top international experts, fills a gap by providing a manual of applied quantitative financial analysis. It focuses on advanced empirical methods for modelling financial markets in the context of practical financial applications.
Data, software and techniques specifically aligned to trading and investment will enable the reader to implement and interpret quantitative methodologies covering various models.
The unusually wide–ranging methodologies include not only the ′traditional′ financial econometrics but also technical analysis systems and many nonparametric tools from the fields of data mining and artificial intelligence. However, for those readers wishing to skip the more theoretical developments, the practical application of even the most advanced techniques is made as accessible as possible.
Depending on the model being described, different software will be used, and examples included on the accompanying CD. Data and details will be provided to enable the reader to transfer the routines to a different software package.
The book will be read by quantitative analysts and traders, fund managers, risk managers; graduate students in finance and MBA courses.


Spis treści:
About the Contributors.
Preface.
1. Applications of Advanced Regression Analysis for Trading and Investment (Christian L. Dunis and Mark Williams).
2. Using Cointegration to Hedge and Trade International Equities (A. Neil Burgess).
3. Modelling the Term Structure of Interest Rates: An Application of Gaussian Affine Models to the German Yield Curve (Nuno Cassola and Jorge Barros Lu .
4. Forecasting and Trading Currency Volatility: An Application of Recurrent Neural Regression and Model Combination (Christian L. Dunis and Xuehuan Huang).
5. Implementing Neural Networks, Classification Trees, and Rule Induction Classification Techniques: An Application to Credit Risk (George T. Albanis).
6. Switching Regime Volatility: An Empirical Evaluation (Bruno B. Roche and Michael Rockinger). 
7. Quantitative Equity Investment Management with Time–Varying Factor Sensitivities (Yves Bentz).
8. Stochastic Volatility Models: A Survey with Applications to Option Pricing and Value at Risk (Monica Billio and Domenico Sartore).
9. Portfolio Analysis Using Excel (Jason Laws).
10. Applied Volatility and Correlation Modelling Using Excel (Frédérick Bourgoin).
11. Optimal Allocation of Trend–Following Rules: An Application Case of Theoretical Results Pierre Lequeux).
12. Portfolio Management and Information from Over–the–Counter Currency Options (Jorge Barros Luís.
13. Filling Analysis for Missing Data: An Application to Weather Risk Management (Christian L. Dunis and Vassilios Karalis.).
Index.

Nota biograficzna:
CHRISTIAN L. DUNIS is Girobank Professor of Banking and Finance at Liverpool Business School, and Director of its Centre for International Banking, Economics and Finance (CIBEF). He is also a consultant to asset management firms, a Visiting Professor of International Finance at Venice International University and an Official Reviewer attached to the European Commission for the evaluation of applications to finance of emerging software technologies. He is an Editor of the European Journal of Finance, and has widely published in the field of financial markets analysis and forecasting. He has organised the Forecasting Financial Markets Conference since 1994.
JASON LAWS is a Lecturer in International Banking and Finance at Liverpool John Moores University. He is also the Course Director for the M.Sc. in International Banking, Economics and Finance at Liverpool Business School. He has taught extensively in the area of investment theory and derivative securities at all levels, both in the UK and in Asia. Jason is also an active member of CIBEF, and has published in a number of academic journals. His research interests are focussed on volatility modelling and the implementation of trading strategies.
PATRICK NAÏM is an engineer of the École Centrale de Paris. He is the founder and chairman of Elseware, a company specialising in the application of nonlinear methods to financial management problems. He is currently working for some of the largest French institutions and co–ordinating research projects in the field at European level.


Okładka tylna:
This much–needed book, from a selection of top international experts, fills a gap by providing a manual of applied quantitative financial analysis. It focuses on advanced empirical methods for modelling financial markets in the context of practical financial applications.
Data, software and techniques specifically aligned to trading and investment will enable the reader to implement and interpret quantitative methodologies covering various models.
The unusually wide–ranging methodologies include not only the ′traditional′ financial econometrics but also technical analysis systems and many nonparametric tools from the fields of data mining and artificial intelligence. However, for those readers wishing to skip the more theoretical developments, the practical application of even the most advanced techniques is made as accessible as possible.
Depending on the model being described, different software will be used, and examples included on the accompanying CD. Data and details will be provided to enable the reader to transfer the routines to a different software package.
The book will be read by quantitative analysts and traders, fund managers, risk managers; graduate students in financ e and MBA courses.