Financial Engineering Applications Research Articles

Contributors

Contributors

Some Sequential Boundary Crossing Results for Geometric Brownian Motion and Their Applications in Financial Engineering

This paper provides new explicit results for some boundary crossing distributions in a multidimensional geometric Brownian motion framework when the boundary is a piecewise constant function of time. Among their various possible applications, they enable accurate and efficient analytical valuation of a large number of option contracts traded in the financial markets belonging to the classes of barrier and look-back options.

Tail Conditional Variance of Portfolio and Applications in Financial Engineering

The optimal portfolio selection is an important issue in financial engineering. It is well-known that downside risk measures such as TCE and CVaR only characterize the tail expectation, and pay no attention to the tail variance beyond the VaR. This is an important deficiency of measuring the extreme financial risk in engineering management, especially for insurance industry and portfolio management. In this paper, we study the optimization portfolio model based on tail conditional variance (TCV) motivated by TCE. We obtain the TCV risk of a portfolio and the explicit solution of optimal portfolio under the assumption of multivariate student t distribution. Finally, we also give an example of empirical study on China Stock Market.

Building acceptable classification models for financial engineering applications

Classification is a popular data mining task, where the value of a discrete (dependent) variable is predicted, based on the values of several independent variables. In this research, we investigate how predictive classification models can be inferred from the available data. The classification models are required to make good predictions, and be comprehensible and intuitive. The aspect of humanly understandable and intuitive models is of crucial importance in any domain where the model needs to be validated before it can be implemented, such as in the medical diagnosis and credit scoring domain. A classification model that is accurate, comprehensible and intuitive is defined in this thesis as acceptable for implementation. Building such acceptable models is the goal of this text. We examine how rule based classifiers can be built that satisfy these requirements. In a first approach, we use rule extraction from Support Vector Machines (SVMs) to extract rules that are accurate, comprehensible, and mimic the SVM model as much as possible. Next, the use of artificial ant colonies for classification is studied, attempting to induce acceptable classification models from data. In a final part, we discuss the application of the investigated algorithms for real-life case studies, such as the prediction of defaults, going concern opinions, software faults, and business/ICT alignment.

Callable Swaps, Snowballs and Videogames

Although economically more meaningful than the alternatives, short rate models have been dismissed for financial engineering applications in favor of market models as the latter are more flexible and best suited to cluster computing implementations. In this paper, we argue that the paradigm shift toward GPU architectures currently taking place in the high performance computing world can potentially change the situation and tilt the balance back in favor of a new generation of short rate models. We find that operator methods provide a natural mathematical framework for the implementation of realistic short rate models that match features of the historical process such as stochastic monetary policy, calibrate well to liquid derivatives and provide new insights on complex structures. In this paper, we show that callable swaps, callable range accruals, target redemption notes (TARNs) and various flavors of snowballs and snowblades can be priced with methods numerically as precise, fast and stable as the ones based on analytic closed form solutions by means of BLAS level-3 methods on massively parallel GPU architectures.

Financial Engineering Applications of Forward Start Options for Structured Products with Capital Protection

Index-linked securities with capital protection have recently been sought by pension funds, institutional investors, hedge funds and other financial institutions looking for downside risk protection while still providing upside equity index participation. The forward start option is the core ingredient for several types of cliquet option that can be integrated into a structured product providing the desired protection of the principal invested. Risk management can be difficult for the issuer and a Monte Carlo exploration reveals some caveats. Pricing forward start options is discussed under the constant-elasticity-of-variance model and new closed formulae are obtained under the square-root process model. <b>TOPICS:</b>Asset-backed securities (ABS)options, statistical methods

CPE: a parallel library for financial engineering applications

The Clustertech parallel environment is an object-oriented C++ library that uses abstractions to simplify parallel programming for financial engineering applications. The message passing interface ensures CPE's portability and performance over a wide range of parallel cluster and symmetric multiprocessing machines.

Multi-factor Stochastic Model and Estimation Procedure for the Valuation and Hedging of Commodity Contingent Claims

In this paper we provide a new multi-factor stochastic model of commodity futures prices and propose a Kalman filter estimation procedure that may be applied to a panel data with missing observations. This model may be used to implement financial engineering applications which require the valuation or hedging of commodity-linked assets. We calibrate our model using daily oil futures prices and analyze its goodness-of-fit to observed prices and empirical volatilities.

Preface(Special Issue on "Theory, Methodology and Applications in Financial Engineering")

Preface(Special Issue on "Theory, Methodology and Applications in Financial Engineering")

The Pricing of Bull and Bear Floating Rate Notes: An Application of Financial Engineering

M Financial engineering can be described as the construction of a security or a portfolio of securities with an otherwise unavailable risk-return configuration. A classic example of financial engineering is the recent issuance of floating rate notes (FRNs) with nontraditional coupon reset formulas. A traditional FRN resets the coupon rate periodically at some fixed margin over (or under) a reference index rate, for example, LIBOR + 0.25%. Since 1986, a number of FRNs have been issued with reset formulas at some fixed rate minus the reference rate. These can be called bull or inverse floaters or, as named by some issuers, yield curve notessee Ogden [8] for further institutional details. The idea is that an investor who is bullish on bond prices would be attracted to a security that has a coupon rate that moves inversely to the market rate. SallieMae (the Student Loan Marketing Association) has issued several bull floaters, including the initial one that had a reset formula of 17.20% LIBOR. Albert Lord, the chief financial officer of SallieMae, said at the time (April 1986):