Narrow Results

We have developed a model for a life-insurance policy. In this model, the net gain is calculated by computer simulation for a particular type of lifetime distribution function. We observed that the net gain becomes maximum for a particular value of upper age for last premium.

We present an analytical study of an insurance company. We model the company's performance on a statistical basis and evaluate the predicted annual income of the company in terms of insurance parameters namely the premium, the total number of insured, average loss claims etc. We restrict ourselves to a single insurance class the so-called automobile insurance. We show the existence of a crossover premium p_c below which the company is operating at a loss. Above p_c, we also give a detailed statistical analysis of the company's financial status and obtain the predicted profit along with the corresponding risk as well as ruin probability in terms of premium. Furthermore we obtain the optimal premium p_opt which maximizes the company's profit.

We propose a solution to the closed-end fund puzzle in financial markets without a free lunch with vanishing risk. Our results are consistent with both the time-series and the cross-sectional aspect of the closed-end fund puzzle. It turns out that a closed-end fund cannot exist if the fund manager is supposed to receive a fee although he is not able to find mispriced assets in the market. By contrast, a premium can typically be observed at the initial public offering because the fund manager has access to information that enables him to create a dominant strategy. As soon as this weak arbitrage opportunity evaporates, a premium can no longer occur. The reason why a premium quickly turns into a discount might be that the fund manager stops applying a superior trading strategy at some point in time. Another possibility is that abnormal profits are transient in a competitive financial market. In any case, when the fund manager is no longer willing or able to maintain a superior strategy, the fund must trade at a discount in order to compensate for his management fee.

This paper investigates the application of option pricing to calculate the premium of deposit insurance in Thailand during the 1992-1996 period. In addition to applying the traditional Black- Scholes model, the barrier model of Boyle and Lee (1994) is examined. The barrier model takes the management (owners) action into account: the management (owners) may have a strong incentive to increase the volatility of the bank's assets, since this action increases the value of their equity. As suggested by the stylized evidence, most financial institutions in Thailand were "family owned", and there was inadequate corporate governance to prevent the incentive problems. The barrier model seems to fit the description of financial institutions in Thailand. The overall results show that the deposit insurance premiums of failed financial institutions are higher than the premiums of non-failed institutions. The evidence suggests that the option framework seems to be appropriate for pricing the premium: higher risk institutions pay higher insurance premiums. The results also show that the risk-based insurance premiums vary across time and on average are less than the premiums charged by the Financial Institutions Development Fund (FIDF).

The paper summarizes the results of a fundamental research project to understand the perception of high-end products by consumers. The first part consisted of a series of in-depth qualitative interviews with over 75 global leaders of luxury and premium companies, star designers and thought leaders. The analysis of the collected data identified five dimensions of high-end offerings, with each dimension having a unique set of four factors. The second part included a massive quantitative (based on Rule Developing Experimentation) survey conducted in the US, UK, Italy and China with about 1800 qualified middle- to upper-class respondents participating in a total of 20 distinct conjoint-based surveys to discover the driving forces behind their perceptions of high-end products. This paper considers in depth one of the five dimensions — leadership and innovation. The analysis of the quantitative part includes mind-set segmentation and demographic subgroups. The research addresses one aspect of today's big question: "How can global brands migrate from being cost-driven commodities to higher margins and profits?" The answer is in the high-end.

The uncertainty premium is the premium that is derived from not knowing the sure outcome (risk premium) and from not knowing the precise odds of outcomes (ambiguity premium). We generalize Pratt's risk premium to uncertainty premium based on Klibanoff et al.'s (2005) smooth model of ambiguity. We show that the uncertainty premium can decrease with an increase in decision maker's risk aversion. This happens because increasing risk aversion always results in a lower ambiguity premium. The positive ambiguity premium may provide an additional explanation to the equity premium puzzle.

This paper considers an epidemiological model, referred to as SEIDRS disease model design for a communicable disease insurance policy. Epidemiologically, the individual population has five demographic groups, which includes: susceptibles (S), exposed (E), infectives undergoing treatments (I), infectives but dead (D) and (R) infectives but recovered from the communicable disease as stipulated in the insurance policy. The latter rejoined the susceptible group and then, continues with the insurance company by paying premium until such insured becomes infected again. The class of infectives comprises a union of those groups that are under treatment and the dead policy holders (PHs). The susceptible and exposed individuals constantly face the risks of being infected by the disease, while the infective class faces the risks of death resulting from the disease. Again, the probability function of a PH to remain susceptible under the SEIDRS disease model is considered, in this paper. Consequently, we obtain, for the insurance policy, the probability density function and cumulative distribution function under the SEIDRS disease model. Using the actuarial principles and techniques, we determine the parties’ insurance financial obligations as well as the insurance quantities. Some empirical results arising from the model analyses, in this paper are considered.

Using epidemiological and actuarial analysis, this paper formulates some new actuarial mathematical models, called S-I-DR-S models, for insuring the susceptibles of a population exposed to a communicable disease. Epidemiologically, the population is structured into four demographic groups, namely: susceptibles $(S)$, infectives $(I)$, diseased $(D)$ and recovered $(R)$, with the latter automatically re-entering the group of susceptibles $(S)$. The insurance policies are targeted at the members of the susceptible group who face the risk of infection and death due to the disease. Using actuarial techniques and principles, we determine some interesting features of the model, namely, (a) financial obligations of the parties, (b) present value of premiums, (c) quantum of claims by infected policy holders (PHs), (d) quantum of claims on behalf of deceased PHs, (e) cumulative insurance reserve for annuity and (f) lump sum plan. To check the risk of insolvency, premium adjustment for the PHs is also considered.