Applied Quantitative Methods for Trading and Investment

Christian Dunis, Jason Laws, Patrick Naïm

406 pages, parution le 26/09/2003

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Résumé

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.

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

L'auteur - Patrick Naïm

Patrick Naïm est ingénieur de l'École centrale de Paris et fondateur d'Elseware, société spécialisée dans la modélisation quantitative et le data mining appliqués aux domaines de la finance, des télécommunications et du commerce électronique. Il est l'auteur de plusieurs livres sur les technologies du data mining et leurs applications.

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Caractéristiques techniques

	PAPIER
Éditeur(s)	Wiley
Auteur(s)	Christian Dunis, Jason Laws, Patrick Naïm
Parution	26/09/2003
Nb. de pages	406
Format	17 x 25
Couverture	Broché
Poids	906g
Intérieur	Noir et Blanc
EAN13	9780470848852
ISBN13	978-0-470-84885-2