Ying-Lin Hsu

Constant elasticity of variance (CEV) option pricing model: Integration and detailed derivation

In this paper we review the renowned constant elasticity of variance (CEV) option pricing model and give the detailed derivations. There are two purposes of this article. First, we show the details of the formulae needed in deriving the option pricing and bridge the gaps in deriving the necessary formulae for the model. Second, we use a result by Feller to obtain the transition probability density function of the stock price at time T given its price at time t with t

Simulation inferences for an availability system with general repair distribution and imperfect fault coverage

Abstract We study the statistical inferences of an availability system with imperfect coverage. The system consists of two active components and one warm standby. The time-to-failure and time-to-repair of the components are assumed to follow an exponential and a general distribution respectively. The coverage factors for an active-component failure and for a standby-component failure are assumed to be the same. We construct a consistent and asymptotically normal estimator of availability for such repairable system. Based on this estimator, interval estimation and testing hypothesis are performed. To implement the simulation inference for the system availability, we adopt two repair-time distributions, namely, lognormal and Weibull and three types of Weibull distributions characterized by their shape parameters are considered. Finally, all simulation results are displayed in appropriate tables and curves for highlighting the performance of the statistical inference procedures.

Computational analysis of machine repair problem with unreliable multi-repairmen

This paper considers a multi-repairmen problem comprising of M operating machines with W warm standbys (spares). Both operating and warm standby machines are subject to failures. With a coverage probability c, a failed unit is immediately detected and attended by one of R repairmen if available. If the failed unit is not detected with probability 1-c, the system enters an unsafe state and must be cleared by a reboot action. The repairmen are also subject to failures which result in service (repair) interruptions. The failed repairman resumes service after a random period of time. In addition, the repair rate depends on number of failed machines. The entire system is modeled as a finite-state Markov chain and its steady state distribution is obtained by a recursive matrix approach. The major performance measures are evaluated based on this distribution. Under a cost structure, we propose to use the Quasi-Newton method and probabilistic global search Lausanne method to search for the global optimal system parameters. Numerical examples are presented to demonstrate the effectiveness of our approach in solving a highly complex manufacturing system subject to multiple uncertainties.

Original article: Standby system with general repair, reboot delay, switching failure and unreliable repair facility-A statistical standpoint

This study statistically examines an availability system with reboot delay, standby switching failures and an unreliable repair facility, which consists of two active components and one warm standby. The time-to-failure and the reboot time are assumed to be exponentially distributed. The repair time of the service station and the time-to-repair of component are assumed to be generally distributed. A consistent and asymptotically normal estimator of availability of such a repairable system is developed. Based on this estimator, interval estimation and testing hypothesis are performed by using logit transformation. To implement the simulation inference for the system availability, two repair-time distributions, lognormal and Weibull distributions, are used. Three Weibull distributions characterized by distinct shape parameters are considered. Finally, all simulation results are displayed as appropriate tables and curves to reveal the performance of the statistical inference procedures.

On a repairable system with detection, imperfect coverage and reboot: Bayesian approach

Abstract System characteristics of a repairable system are studied from a Bayesian viewpoint with different types of priors assumed for unknown parameters, in which the system consists of one active component and one standby component. The detection of standby, the coverage factor and reboot delay of failed components are possibly considered. Time to failure of the components is assumed to follow exponential distribution. Time to repair and time to reboot of the failed components also follow exponential distributions. When time to failure, time to repair and time to reboot have uncertain parameters, a Bayesian approach is adopted to evaluate system characteristics. Monte Carlo simulation is used to derive the posterior distribution for the mean time to system failure and the steady-state availability. Some numerical experiments are performed to illustrate the results derived in this paper.

A repairable system with imperfect coverage and reboot: Bayesian and asymptotic estimation

System characteristics of a two-unit repairable system are studied from a Bayesian viewpoint with different types of priors assumed for unknown parameters, in which the coverage factor for an operating unit failure is possibly considered. Time to failure and time to repair of the operating units are assumed to follow exponential distributions. In addition, the recovery time and reboot time of the failed units also follow exponential distributions. When time to failure, time to repair, recovery time and reboot time are with uncertain parameters, a Bayesian approach is adopted to evaluate system characteristics. Monte Carlo simulation is used to derive the posterior distribution for the mean time to system failure and the steady-state availability. Some numerical experiments are performed to illustrate the results derived in this paper.

Modeling of multi-server repair problem with switching failure and reboot delay and related profit analysis

This study examines a warm-standby machine repair problem which involves a switching failure probability, reboot delay and a repair pressure coefficient. The machine repair problem has M operating machines with W warm standbys and R repairpersons. When all repairpersons are busy and waiting line is very long (heavy loading), the repairpersons increase their repair rate to reduce the queue length because of the pressure. This phenomenon is very common in many realistic service systems. A matrix-analytic method is adopted to develop a function of the steady-state expected profit per unit time. The probabilistic global search Lausanne (PGSL) method is employed to determine the joint optimal parameter values that maximize the profit and satisfy the availability constraint. Some numerical results of various system performance measures under optimal operating conditions are presented. Finally, several managerial insights are provided by demonstrating an example of the application to assist system analysts for decision making.

Bayesian assessing for a repairable system with standby imperfect switching and reboot delay

System performance measures of a repairable system are studied from a Bayesian viewpoint with different types of priors assumed for unknown parameters, in which the system consists of two active components and one warm standby. There is a failure probability q that switches from standby state to active state. Time-to-failure of components is assumed to be an exponential distribution. The reboot time and repair time are also exponential distributions. When time-to-failure, time-to-repair and reboot time are with uncertain parameters, a Bayesian assessing is adopted to evaluate system performance measures. Monte Carlo simulation is used to derive the posterior distribution for the steady-state availability and the mean time-to-system failure. Some numerical experiments are performed to illustrate the results derived in this article.

On a redundant repairable system with switching failure: Bayesian approach

System characteristics of a redundant repairable system are studied from a Bayesian viewpoint with different types of priors assumed for the unknown parameters. The system consists of two primary units, one standby unit, and one repair facility which is activated when switching to standby fails. Times to failure and times to repair of the operating units are assumed to follow exponential distributions. When time to failure and time to repair have uncertain parameters, a Bayesian approach is adopted to evaluate system characteristics. Monte Carlo simulation is used to derive the posterior distribution for the mean time to system failure and steady-state availability. Some numerical experiments are performed to illustrate the results derived in this paper.

A factor analysis based selection process for predicting successful university color guard club members

The purpose of this paper is to determine how to place students in the most appropriate club, to save training time and expenses, and maximize club performance. To this end, this research utilizes the example of the color guard club at Chienkuo Technology University (CTU). First, the authors researched the characteristics needed to be a color guard member. Second, a series of tests for measuring these characteristics was designed. Third, the authors administered the tests to all the club members and recorded the results. Fourth, after the club members had received one year of training, the authors ran regression analysis by using data from the tests of those who successfully passed the training. From this, the authors obtained a regression model. The authors then ran logistic regression analysis and discriminant analysis on the test data of all initial color guard club members, including those who eventually passed the training and those who eventually withdrew, to establish screening norms. Last, using factor analysis, the authors found the latent factors. These factors, along with the screening norms, can serve as a foundation for future selection of color guard members. This process of selecting club members scientifically may be adopted by other clubs in order to match students and clubs most effectively.