Decision Technologies for Computational Finance

1. Volatility Modeling and Option Pricing

   1. Using Illiquid Option Prices to Recover Probability Distributions

      • F. González Miranda, A. N. Burgess

      Pages 219-232

      PDF

   2. Modeling Financial Time Series Using State Space Models

      • Jens Timmer, Andreas S. Weigend

      Pages 233-246

      PDF

   3. Forecasting Properties of Neural Network Generated Volatility Estimates

      • Parvez Ahmed, Steve Swidler

      Pages 247-258

      PDF

   4. Interest Rates Structure Dynamics: A Non Parametric Approach

      • Marie Cottrell, Eric de Bodt, Philippe Grégoire

      Pages 259-266

      PDF

   5. State Space Arch: Forecasting Volatility with a Stochastic Coefficient Model

      • Álvaro Veiga, Marcelo C. Medeiros, Cristiano Fernandes

      Pages 267-274

      PDF

2. Term Structure and Factor Models

   1. Front Matter

      Pages 275-275

      PDF

   2. Empirical Analysis of the Australian and Canadian Money Market Yield Curves: Results Using Panel Data

      • S. H. Babbs, K. B. Nowman

      Pages 277-289

      PDF

   3. Time-Varying Factor Sensitivities in Equity Investment Management

      • Y. Bentz, J. T. Connor

      Pages 291-308

      PDF

   4. Discovering Structure in Finance Using Independent Component Analysis

      • Andrew D. Back, Andreas S. Weigend

      Pages 309-322

      PDF

   5. Fitting No Arbitrage Term Structure Models Using a Regularisation Term

      • N. Towers, J. T. Connor

      Pages 323-332

      PDF

   6. Quantification of Sector Allocation at the German Stock Market

      • Elmar Steurer

      Pages 333-351

      PDF

3. Corporate Distress Models

   1. Front Matter

      Pages 353-353

      PDF

   2. Predicting Corporate Financial Distress Using Quantitative and Qualitative Data: A Comparison of Standard and Collapsible Neural Networks

      • Queen Booker, John D. Johnson, Robert E. Dorsey

      Pages 355-363

      PDF

   3. Credit Assessment Using Evolutionary MLP Networks

      • E. F. F. Mendes, A. C. P. L. F. Carvalho, A. B. Matias

      Pages 365-371

      PDF

   4. Exploring Corporate Bankruptcy with Two-Level Self-Organizing Map

      • K. Kiviluoto, P. Bergius

      Pages 373-380

      PDF

   5. The Ex-ante Classification of Takeover Targets Using Neural Networks

      • David Fairclough, John Hunter

      Pages 381-388

      PDF

4. Advances on Methodology—Short Notes

   1. Front Matter

      Pages 389-389

      PDF

   2. Forecasting Non-Stationary Financial Data with OIIR-Filters and Composed Threshold Models

      • Marc Wildi

      Pages 391-402

      PDF

   3. Portfolio Optimisation with Cap Weight Restrictions

      • Niklas F. Wagner

      Pages 403-416

      PDF

   4. Are Neural Network and Econometric Forecasts Good for Trading? Stochastic Variance Models as a Filter Rule

      • R. Bramante, R. Colombo, G. Gabbi

      Pages 417-424

      PDF

This volume contains selected papers that were presented at the International Conference COMPUTATIONAL FINANCE 1997 held at London Business School on December 15-17 1997. Formerly known as Neural Networks in the Capital Markets (NNCM), this series of meetings has emerged as a truly multi-disciplinary international conference and provided an international focus for innovative research on the application of a multiplicity of advanced decision technologies to many areas of financial engineering. It has drawn upon theoretical advances in financial economics and robust methodological developments in the statistical, econometric and computer sciences. To reflect its multi-disciplinary nature, the NNCM conference has adopted the new title COMPUTATIONAL FINANCE. The papers in this volume are organised in six parts. Market Dynamics and Risk, Trading and Arbitrage strategies, Volatility and Options, Term-Structure and Factor models, Corporate Distress Models and Advances on Methodology. This years' acceptance rate (38%) reflects both the increasing interest in the conference and the Programme Committee's efforts to improve the quality of the meeting year-on-year. I would like to thank the members of the programme committee for their efforts in refereeing the papers. I also would like to thank the members of the computational finance group at London Business School and particularly Neil Burgess, Peter Bolland, Yves Bentz, and Nevil Towers for organising the meeting.

• Arbitrage
• capital market
• controlling
• dynamics
• econometrics
• finance
• investment
• learning
• modeling
• networks
• optimization
• risk management
• strategy
• time series
• volatility

• London Business School, UK

  Apostolos-Paul N. Refenes, Andrew N. Burgess

• Oregon Graduate Institute, Portland, USA

  John E. Moody

Policies and ethics