Christian L. Dunis – författare
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5 produkter
5 produkter
Del 232 - Wiley Finance Series
Applied Quantitative Methods for Trading and Investment
Inbunden, Engelska, 2003
1 377 kr
Skickas inom 5-8 vardagar
This book provides a manual on quantitative financial analysis. Focusing on advanced methods for modelling financial markets in the context of practical financial applications, it will cover data, software and techniques that will enable the reader to implement and interpret quantitative methodologies, specifically for trading and investment. Includes contributions from an international team of academics and quantitative asset managers from Morgan Stanley, Barclays Global Investors, ABN AMRO and Credit Suisse First Boston.Fills the gap for a book on applied quantitative investment & trading modelsProvides details of how to combine various models to manage and trade a portfolio
Inbunden, Engelska, 2001
1 437 kr
Skickas inom 5-8 vardagar
Developments in Forecast Combination and Portfolio Choice focuses on the following three themes: model and forecast combinations; structural change and long memory, controlling downside risk and investment strategies. Written by leading international researchers and practitioners, his book deals efficiently with three key questions facing portfolio managers. How to achieve greater forecasting accuracy; how to deal with structural change in asset allocation models and how to control downside risk, i.e. the risk of loss, in portfolio management.
Inbunden, Engelska, 1996
1 528 kr
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Today s financial markets are characterised by a large number ofparticipants, with different appetites for risk, different timehorizons, different motivations and reactions to unexpected news.The mathematical techniques and models used in the forecasting offinancial markets have therefore grown ever more sophisticated astraders, analysts and investors seek to gain an edge on theircompetitors. Written by leading international researchers andpractitioners, this book focuses on three major themes of today sstate of the art financial research: modelling with high frequencydata, the information content of volatility markets, andapplications of neural networks and genetic algorithms to financialtime series. Forecasting Financial Markets includes empiricalapplications to present the very latest thinking on these complextechniques, including:* High frequency exchange rates * Intraday volatility * Autocorrelation and variance ratio tests * Conditional volatility * GARCH processes * Chaotic systems * Nonlinearity * Stochastic and EXPAR models * Artificial neural networks * Genetic algorithms
Inbunden, Engelska, 1998
1 395 kr
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Nonlinear Modelling of High Frequency Financial Time Series Edited by Christian Dunis and Bin Zhou In the competitive and risky environment of today's financial markets, daily prices and models based upon low frequency price series data do not provide the level of accuracy required by traders and a growing number of risk managers. To improve results, more and more researchers and practitioners are turning to high frequency data. Nonlinear Modelling of High Frequency Financial Time Series presents the latest developments and views of leading international researchers and market practitioners, in modelling high frequency data in finance. Combining both nonlinear modelling and intraday data for financial markets, the editors provide a fascinating foray into this extremely popular discipline. This book evolves around four major themes. The first introductory section focuses on high frequency financial data. The second part examines the exact nature of the time series considered: several linearity tests are presented and applied and their modelling implications assessed. The third and fourth parts are dedicated to modelling and forecasting these financial time series.
Inbunden, Engelska, 2017
1 102 kr
Skickas inom 10-15 vardagar
As technology advancement has increased, so to have computational applications for forecasting, modelling and trading financial markets and information, and practitioners are finding ever more complex solutions to financial challenges. Neural networking is a highly effective, trainable algorithmic approach which emulates certain aspects of human brain functions, and is used extensively in financial forecasting allowing for quick investment decision making. This book presents the most cutting-edge artificial intelligence (AI)/neural networking applications for markets, assets and other areas of finance. Split into four sections, the book first explores time series analysis for forecasting and trading across a range of assets, including derivatives, exchange traded funds, debt and equity instruments. This section will focus on pattern recognition, market timing models, forecasting and trading of financial time series. Section II provides insights into macro and microeconomics and how AI techniques could be used to better understand and predict economic variables. Section III focuses on corporate finance and credit analysis providing an insight into corporate structures and credit, and establishing a relationship between financial statement analysis and the influence of various financial scenarios. Section IV focuses on portfolio management, exploring applications for portfolio theory, asset allocation and optimization. This book also provides some of the latest research in the field of artificial intelligence and finance, and provides in-depth analysis and highly applicable tools and techniques for practitioners and researchers in this field.