Managing value-at-risk for a bond using bond put options

This paper studies a strategy that minimizes the Value-at-Risk (VaR) of a position in a zero-coupon bond by buying a percentage of a put option, subject to a fixed budget available for hedging. We elaborate a formula for determining the optimal strike price for this put option in case of a Vasicek stochastic interest rate model. We demonstrate the relevance of searching the optimal strike price, since moving away from the optimum implies a loss, either due to an increased VaR or due to an increased hedging expenditure. In this way, we extend the results of [Ahn, Boudoukh, Richardson, and Whitelaw (1999). Journal of Finance, 54, 359–375] who minimize VaR for a position in a share. In addition, we look at the alternative risk measure Tail Value-at-Risk.     

Exotic European options with restrictions on the payoffs

We consider the problem of finding the values of options, portfolios (hedging strategies), and capitals for one kind of exotic European options for buying and selling in binomial and diffusion models of a (B, S) stock market.     

Evolutionary computation and the vega risk of American put options

While European style options and American call options can be priced using analytical exact valuation models, closed-form solutions for the valuation of American puts have not yet been derived. The American put price as well as the corresponding greeks (e.g., delta, gamma, vega) can be calculated using numerical procedures or analytical approximations. We use a parallel implementation of the genetic programming approach and derive analytical approximations for determining the vega of an American put option because calculating vegas numerically requires even more computational effort than determining deltas or gammas. Applying our approximations to experimental data sets we can show that the genetically derived approximations outperform other approximations based on frequently used American put pricing formulas.     

Disaster recovery — options on the market

I must say that over the past few years I have encountered several products that can be classified as disaster recovery down to the byte level. Anyone who has worked in computing for a respectable number of years will have at least a few nightmare stories about accidentally deleted files and unsuccessful restores. Undoing the damage, if that was possible, was always traumatic, but most times it had to be written off as bad luck. There are good products available now that cover all the eventualities we used to fear in that they perform true backup and true recovery. In this piece I will discuss Open File Manager, DoubleTake and SnapBack.     

Pricing American bond options using a penalty method

We develop a novel numerical method to price American options on a discount bond under the Cox–Ingrosll–Ross (CIR) model which is governed by a partial differential complementarity problem. We first propose a penalty approach to this complementarity problem, resulting in a nonlinear partial differential equation (PDE). To numerically solve this nonlinear PDE, we develop a novel fitted finite volume method for the spatial discretization, coupled with a fully implicit time-stepping scheme. We show that this full discretization scheme is consistent, stable and monotone, and hence the convergence of the numerical solution to the viscosity solution of the continuous problem is guaranteed. To solve the discretized nonlinear system, we design an iterative method and prove that the method is convergent. Numerical results are presented to demonstrate the accuracy, efficiency and robustness of our methods.     

A robust upwind difference scheme for pricing perpetual American put options under stochastic volatility

In this paper, we present an upwind difference scheme for the valuation of perpetual American put options, using Heston's stochastic volatility model. The matrix associated with the discrete operator is an M-matrix, which ensure that the scheme is stable. We apply the maximum principle to the discrete linear complementarity problem in two mesh sets and derive the error estimates. Numerical results support the theoretical results.     

Altera业界首推40nm FPGA期待占据市场主导地位专访Altera亚太区副总裁兼董事总经理Erhaan Shaikh先生

<正> Ahera 在中国深圳、杭州、北京三地主办 SOPC World 2008,《电子技术应用》(AET)作为唯一的媒体对此次活动进行跟踪报道。针对目前一些热点问题及 Altera 的发展策略等,我们有幸在杭州对 Altera 亚太区副总裁兼董事总经理 ErhaanShaikh(柯汗青)先生进行专访。AET:您觉得与去年相比,今年贵公司及整个行业有什么改变吗?Shaikh 先生:与去年相比,     

Adoption of electronic options trading at the ISE

US brokerage firms have shown strong interest in a new alternative for trading of equity options since the 26 May 2000 launch of the International Securities Exchange (ISE), an all-electronic trading platform. Although the collective impact of these adoption decisions led to a successful launch and a formidable competitor to the four established options markets in the US, major brokerage firms differ widely in their usage and adoption rates.     

A tree approach to options pricing under regime-switching jump diffusion models

A simple, efficient tree is developed to price options in a very general regime-switching jump diffusion model. Under this model, the switching rates of the switching process depend on the underlying stock price process. Sufficient conditions that guarantee the positivity of branch probabilities are provided. Using the regime-switching tree, we approximate Heston's stochastic volatility model with an additional jump component. Finally, we illustrate the effectiveness of the tree method by several numerical examples.     

Circulant preconditioning technique for barrier options pricing under fractional diffusion models

In recent years, considerable literature has proposed the more general class of exponential Lévy processes as the underlying model for prices of financial quantities, which thus better explain many important empirical facts of financial markets. Finite moment log stable, Carr–Geman–Madan–Yor and KoBoL models are chosen from those above-mentioned models as the dynamics of underlying equity prices in this paper. With such models pricing barrier options, one kind of financial derivatives is transformed to solve specific fractional partial differential equations (FPDEs). This study focuses on numerically solving these FPDEs via the fully implicit scheme, with the shifted Grünwald approximation. The circulant preconditioned generalized minimal residual method which converges very fast with theoretical proof is incorporated for solving resultant linear systems. Numerical examples are given to demonstrate the effectiveness of the proposed preconditioner and show the accuracy of our method compared with that done by the Fourier cosine expansion method as a benchmark.     

The impact of stock market volatility on corporate bond credit spreads

There has been a rapid increase in the number of corporate bonds issued in Australia since the middle of 1998. This increase has stimulated interest in characterising the yield curves and the factors that determine changes in these spreads. The focus of this paper is on measuring any impact of stock market volatility on spreads using two different measures. One measure is based on volatility implied from options prices while the other is derived from a conditional heteroscedastic volatility model of changes in a stock market index. It is found that the former has no significant impact on spreads but the latter is both significant and stable over time. This impact is estimated to be negative implying that an increase in volatility cause a decrease in corporate bond spreads.     

The matching of lead underwriters and issuing firms in the Japanese corporate bond market

The purpose of this paper is to examine the role of reputation in the matching of lead underwriters and issuing firms in the straight corporate bond market in Japan. While the existing literature already investigates how the issuing firm chooses its lead underwriter at the time of issue, this paper uses successive issues of straight corporate bonds to examine how the matching of lead underwriters and issuing firms changes over time.Data on individual issues of straight corporate bonds publicly issued in Japan between 25 February 1994 and 31 December 2009 are used to estimate models which explain how issuing firms match with lead underwriters. We measure the reputations of underwriters and issuing firms using each underwriter's percentile rank in the underwriting market and the issuer's percentile rank in the issuing proceeds, respectively. We construct a data set of straight corporate bond issues which includes many repeated issues. One of the contributions in this paper is to take account of these repeated issues by treating the data as a panel data set, and allowing for an issuer random effect in both probit and logit models of switching. This random effect is found to be significant.The estimation results show that issuing firms match with the same lead underwriter when the difference of the issuer's reputation and the current reputation of the previous lead underwriter is small. Issuing firms with an AAA rating at the time of issue are less likely to match with the same lead underwriters. In addition to reputation effects, there is strong evidence to suggest that issuing firms continue to stay matched with the same underwriter if the lead underwriter is a subsidiary of the issuing firm's main bank.     

Applying option Greeks to directional forecasting of implied volatility in the options market: An intelligent approach

This paper examines movement in implied volatility with the goal of enhancing the methods of options investment in the derivatives market. Indeed, directional movement of implied volatility is forecasted by being modeled into a function of the option Greeks. The function is structured as a locally stationary model that employs a sliding window, which requires proper selection of window width and sliding width. An artificial neural network is employed for implementing and specifying our methodology. Empirical study in the Korean options market not only illustrates how our directional forecasting methodology is constructed but also shows that the methodology could yield a reasonably strong performance. Several interesting technical notes are discussed for directional forecasting.     

Quick energy prediction and comparison of options at the early design stage

The energy-efficient building design requires building performance simulation (BPS) to compare multiple design options for their energy performance. However, at the early stage, BPS is often ignored, due to uncertainty, lack of details, and computational time. This article studies probabilistic and deterministic approaches to treat uncertainty; detailed and simplified zoning for creating zones; and dynamic simulation and machine learning for making energy predictions. A state-of-the-art approach, such as dynamic simulation, provide a reliable estimate of energy demand, but computationally expensive. Reducing computational time requires the use of an alternative approach, such as a machine learning (ML) model. However, an alternative approach will cause a prediction gap, and its effect on comparing options needs to be investigated. A plugin for Building information modelling (BIM) modelling tool has been developed to perform BPS using various approaches. These approaches have been tested for an office building with five design options. A method using the probabilistic approach to treat uncertainty, detailed zoning to create zones, and EnergyPlus to predict energy is treated as the reference method. The deterministic or ML approach has a small prediction gap, and the comparison results are similar to the reference method. The simplified model approach has a large prediction gap and only makes only 40% comparison results are similar to the reference method. These findings are useful to develop a BIM integrated tool to compare options at the early design stage and ascertain which approach should be adopted in a time-constraint situation.