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This paper explores a particularly simple model of choice under risk, based on geometric means and entropy. Despite its simplicity, it satisfies various prudence and risk aversion conditions, is consistent with the Allais paradox, and generates various insurance-related results. Within a portfolio framework with compounded reinvestments, our index fits the risks/rewards data from post-war US stock market returns and recent international markets, at least as well as does the standard deviation measures more typically used. It also generates returns that are consistent with the equity premium puzzle.

House price indices are needed to assess house price risk in households’ portfolio allocation decisions and in many housing-related financial products such as reverse mortgages, mortgage insurance and real estate derivatives. This paper first introduces nine widely-used house price models to the insurance, risk management and actuarial literature and provides new evidence on the relative performance of these models. We then show how portfolio-level house price indices for properties with specific physical and locational characteristics can be constructed for these different models. All analyses are based on a large dataset of individual property transactions in Sydney, Australia, for the period 1971-2011. The unrestricted hedonic model and a hybrid hedonic repeat-sales model provide a good model fit and reliable portfolio-level house price indices. Our results are important for banks, insurers and investors that have exposure to house price risks.

In this paper, we examine whether risk premiums are significant in explaining the deviations from the uncovered interest rate parity (UIP) condition in an emerging Indian currency futures market. In particular, we explore the unbiasedness of futures quotes as a predictor of the future spot exchange rate to understand the forward premium anomaly condition. We report huge deviations from the UIP condition for all currencies considered and show that these deviations are explained by the risk premium. The realized risk premiums for all currencies are found to be negative and significantly different from zero, which suggests that investors are awarded for taking short positions in the foreign currency. The realized risk premiums in turn are found to be negatively related to the current spot rate returns and positively to the futures premium, conditional variance of spot rate returns, and the dividend yield.

Mortality-linked securities such as longevity bonds or longevity swaps usually depend on not only mortality risk but also interest rate risk. However, in the existing pricing methodologies, it is often the case that only the mortality risk is modeled to change in a stochastic manner and the interest rate is kept fixed at a pre-specified level. In order to develop large and liquid longevity markets, it is essential to incorporate the interest rate risk into pricing mortality-linked securities. In this paper we tackle the issue by considering the pricing of longevity derivatives under stochastic interest rates following the CIR model. As for the mortality modeling, we use a two-factor extension of the Lee-Carter model by noting the recent studies which point out the inconsistencies of the original Lee-Carter model with observed mortality rates due to its single factor structure. To address the issue of parameter uncertainty, we propose using a Bayesian methodology both to estimate the models and to price longevity derivatives in line with (Kogure, A., and Y. Kurachi. 2010. “A Bayesian Approach to Pricing Longevity Risk Based on Risk Neutral Predictive Distributions.” Insurance: Mathematics and Economics 46:162–172) and (Kogure, A., J. Li, and S. Y. Kamiya. 2014. “A Bayesian Multivariate Risk-neutral Method for Pricing Reverse Mortgages.” North American Actuarial Journal 18:242–257). We investigate the actual effects of the incorporation of the interest rate risk by applying our methodology to price a longevity cap with Japanese data. The results show significant differences according to whether the CIR model is used or the interest rate is kept fixed.

We extend Kliger and Levikson’s approach for pricing insurance contracts by considering the influence of insurer capital on the price of insurance contracts. In the context of a multi-line insurer, we analyze how to arrive at the optimal price, number of policies, and capital level of the insurer. Our results differ from prior literature on capital allocation even in incomplete markets with friction in that we show that even with multiple lines of business, the insurer still only needs to hold a single amount of overall capital. Finally, our results show that the relation between the number of policies and price is important in the pricing and capital decision.