Description: This session presents a summary of actuarial and potential uses of stochastic modeling for health actuaries. Three case studies are presented: rating health plan reimbursement provisions, developing claim liabilities, and defining appropriate reinsurance levels. From the Record of the Society of Actuaries, Volume 30, No. 1, Session 18

Description: This session at the SOA 2001 Toronto Spring Meeting offers an overview of stochastic pricing including stochastic variables, equity market models, interest rate models and policyholder behavior. An example is given using a variable annuity product.

Description: This presentation is a panel discussion, session number 9PD, from the 2000 Valuation Actuary Symposium, held September 14-15 in Washington, DC. A fundamental assumption in stochastic asset/liability modeling is the underlying economic scenario generator. In this session the panelists discuss various scenario generation techniques, assumptions underlying bond and equity scenario generators, and choosing suitable economic scenario generators for different applications. Discussion from participants is included.

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: Presentation from the 41st Actuarial Research Conference with the main topic of analyzing the life insurance industry.

Description: Presented at August 2011 Actuarial Research Conference. Summarizes the Heston model, discusses hedging equity indexed annuities, and provides numerical results of the Black-Scholes and Heston hedging strategies.

Description: This presentation considers the pricing of European derivatives in a Black-Scholes model with stochastic volatility. The presentation shows how Parseval’s theorem may be used to express those prices as Fourier integrals. This is a significant improvement over Monte Carlo simulation in many cases. The main ingredient in this presentation's method is the Laplace transform of the ordinary [constant volatility] price of a put or call in the Black-Scholes model, where the transform is taken with respect to maturity [T]. The presentation derives these formulas and then applies them to the case where volatility is modelled as a Markov chain in continuous time, the so-called 'Markov regime switching model'. This model has been used previously in stochastic volatility modelling, but mostly with only N=2 states. The presentation shows how to use N=3 states without difficulty, and how larger number of states can be handled. Numerical illustrations are given, including the volatility smile in a three-state model.

Description: Presentation discussing modeling of daily and hourly rainfall, both occurrence and amount. These distributions would be needed to price derivative or insurance contracts involving rainfall amounts.

Description: This presentation estimates several models of interest rates, including seven without and four with regime shifts.