Applying operations research techniques to financial markets

Authors:
John Board;Charles Sutcliffe;William T. Ziemba
Affiliations:
Department of Accounting and Finance, London School of Economics and Political Science, London WC2A 2AE, United Kingdom;Accounting and Finance Division, School of Management, University of Southampton, Southampton SO17 1BJ, United Kingdom;Operations and Logistics Division, Faculty of Commerce and Business Administration, University of British Columbia, 2053 Main Mall, Vancouver, British Columbia, Canada V6T 1Z2
Venue:
Interfaces
Year:
2003

Citing 19
Cited 1

True interest cost in municipal bond bidding: an integer programming approach

Management Science
Introduction to operations research, 4th ed.

Introduction to operations research, 4th ed.
A game-theoretic model of corporate takeovers by major stockholders

Management Science
Playing the turn-of-the-year effect with index futures

Operations Research
A financial expert decision support system

Mathematical models for decision support
Operations research analysis of a stock market problem

Computers and Operations Research
Mortgages and Markov chains: a simplified evaluation model

Management Science
Stochastic network programming for financial planning problems

Management Science - Focused issue on financial modeling
A multiple-objective programming technique for structuring tax-exempt serial revenue debt issues

Management Science
An envelopment-analysis approach to measuring the managerial efficiency of banks

Annals of Operations Research
Quasi-Monte Carlo methods in numerical finance

Management Science
Estimating security price derivatives using simulation

Management Science
Path-dependent options: extending the Monte Carlo simulation approach

Management Science
Neural network applications in finance: a review and analysis of literature (1990-1996)

Information and Management
Neural Networks in the Capital Markets

Neural Networks in the Capital Markets
Intelligent Systems for Finance and Business

Intelligent Systems for Finance and Business
Neural Networks in Finance and Investing: Using Artificial Intelligence to Improve Real World Performance

Neural Networks in Finance and Investing: Using Artificial Intelligence to Improve Real World Performance
Optimal Control of Execution Costs for Portfolios

Computing in Science and Engineering
The Innovest Austrian Pension Fund Financial Planning Model InnoALM

Operations Research

Partnerships in Training

Interfaces

Quantified Score

Hi-index	0.00

Visualization

Abstract

OR techniques are applied to nonportfolio problems in financial markets, such as the equity, debt, and foreign exchange markets and the corresponding derivatives markets. Finance problems are an excellent application area for OR researchers. OR techniques are used to value financial instruments, identify market imperfections, design securities, regulate markets, evaluate and control risks, model strategic problems, and understand the functioning of financial markets. Mathematical programming is probably the most widely applied OR technique, but Monte Carlo simulation methods are of increasing importance. With the improvements in the real-time availability of data and the power of computers, the role of OR techniques in financial markets can only increase.