Description: The main aim of this paper is to apply some of the techniques of modern time series and econometric analysis to analyse investment data in order to better understand the nature of long run relationships in investment series typically used in stochastic investment models. The paper attempts to identify and address fundamental issues that need to be considered before developing a particular stochastic investment model.

Description: This review summarizes the key features of a stochastic model that works with non-life insurance claim incurral, accrual and reporting. More specifically it provides an overview of the claim model components, classical parameter estimators, test statistics, and forecast point estimates and error variances. From Actuarial Research Clearing House 1991, VOL. 1.

Description: One of the most important problems in Finance is the valuation of financial securities written on underlying assets whose prices are subject to uncertainty. This paper presents a technique to estimate the unknown stochastic volatilities by solving the inverse problem associated with the parabolic partial differential equation governing risk neutral derivative security prices. This technique can be applied in a very general multi-factor setting and numerical examples are provided.

Description: This session from the 1995 SOA Boston Meeting covers a general overview of basic interest rate models, the meaning of an arbitrage free model, the considerations in choosing an appropriate interest rate scenario generator, the uses, alternative approaches, the double mean reverting process model - DMRP, and how good the results are in terms of historical rates. From the Record of the Society of Actuaries, Vol. 21, No. 4b.

Description: 1994 SOA Spring Meeting, Orlando. In this session the panel consider the question of uncertainty in loss reserves including discussion of sources and measurement. The panelists analyzed the same data set from different perspectives and discussed the strengths and weaknesses of the approaches.

Description: This paper addresses the evaluation of long-term returns when the short interest rate is modeled by a general diffusion process. By deriving the long-term return dynamics and invoking the Feyman-Kac formula, the long-term return is represented as the solution of a partial differential equation. A finite difference method is derived for the valuation of the long-term return. The method could be used for hedging interest rate risk, pricing and managing interest rate derivatives and interest rate sensitive insurance products. Numerical examples are included.

Description: 2011 SOA Enterprise Risk Management Symposium, Chicago. This paper suggests the use of a policy event-based loss estimation method using expert input and simulation for forecasting long duration expenditures: that is to say, there is an efficient time, which is random and observable to replace a physical asset.

Description: In this article the author cautions against the temptation to extend stochastic modeling into areas of unpredictable parameters and probabilities. He challenges actuaries to rely on their own judgment.

Description: Commentary on practical observations resulting from constructing and running Economic Capital models. Possible standardization of assumptions and result interpretation are morphing even though use of E.C. models has now been around for years.

Description: This article is the first installment of a three-part series that aims to provide an overview of ESGs and will focus on the general motivation for stochastic modeling, its advantages and its limitations. Future articles will further break down the key factors of ESGs and the application of these factors to better understand the Academy Interest Rate Generator (AIRG).