Computational Finance and Its Applications

In the last two years, several major events have characterised the international financial markets. The most significant one was certainly the explosion of the price of commodities, in particular of oil, which has recently reached a level of 74 dollars. Analysts are now divided on where the markets will go next. Some argue that growth will continue, while others are warning that we could be already in the middle of a new stock market bubble. Computational systems have become increasingly important in many financial applications, such as trading strategy, risk management, derivatives pricing, and many others. At the same time, traditional financial techniques have been constantly improved and developed as a result of the increased power of modern computer systems.Featuring papers from the Second International Conference on Computational Finance and its Applications, the text includes papers focussed on the following areas: Financial service technologies in the 21st century; Advanced computing and simulation; Derivatives pricing; Forecasting, advanced computing and simulation; Market analysis, dynamics and simulation; Portfolio management and asset allocation; Risk management; Time series analysis and forecasting.

Table of Contents:
Section 1: Financial service technologies in the 21st century (Special section edited by J. Lawler and D. Anderson) Community e-kiosk portal technology on Wall Street; Management of the productivity of information and communications technology (ICT) in the financial services industry; Collaborative support for on-line banking solutions in the financial services industry; Time value of the Internet banking adoption and customer trust; Financial assurance program for incidents induced by Internet-based attacks in the financial services industry; An innovative interdisciplinary curriculum in financial computing for the financial services industry; Critical success factors in planning for Web services in the financial services industry Section 2: Advanced computing and simulation Integrated equity applications after Sarbanes-Oxley; C++ techniques for high performance financial modelling; Solving nonlinear financial planning problems with 109 decision variables on massively parallel architectures Section 3: Derivatives pricing Mean-variance hedging strategies in discrete time and continuous state space; The more transparent, the better - evidence from Chinese markets; Herd behaviour as a source of volatility in agent expectations; A Monte Carlo study for the temporal aggregation problem using one factor continuous time short rate models; Contingent claim valuation with penalty costs on short selling positions; Geometric tools for the valuation of performance-dependent options; Optimal exercise of Russian options in the binomial model; Exotic option, stochastic volatility and incentive scheme; Applying design patterns for web-based derivatives pricing Section 4: Forecasting, advanced computing and simulation Applications of penalized binary choice estimators with improved predictive fit; The use of quadratic filter for the estimation of time-varying ss; Forecast of the regional EC development through an ANN model with a feedback controller; Section 5: Market analysis, dynamics and simulation The impact of the futures market on spot volatility: an analysis in Turkish derivatives markets; A valuation model of credit-rating linked coupon bond based on a structural model; Dynamics of the top of the order book in a global FX spot market; Seasonal behaviour of the volatility on European stock markets; Simulating a digital business ecosystem; Customer loyalty analysis of a commercial bank based on a structural equation model; Do markets behave as expected? Empirical test using both implied volatility and futures prices for the Taiwan Stock Market; The simulation of news and insiders' influence on stock-market price dynamics in a non-linear model; T-outlier and a novel dimensionality reduction framework for high dimensional financial time series Section 6: Portfolio management and asset allocation Integrating elements in an i-DSS for portfolio management in the Mexican market; Timing inconsistencies in the calculation of funds of funds net asset value; Strategic asset allocation using quadratic programming with case based reasoning and intelligent agents; Heuristic approaches to realistic portfolio optimisation; Selection of an optimal portfolio with stochastic volatility and discrete observations Section 7: Risk management Monte Carlo risk management; Path dependent options: the case of high water mark provision for hedge funds Section 8: Time series analysis and forecasting Macroeconomic time series prediction using prediction networks and evolutionary algorithms; Power Coefficient - a non-parametric indicator for measuring the time series dynamics