Description: This paper discusses some of the models used to quantify risk, note some areas where improvements in standard methods are needed, and in some cases suggest alternative approaches for risks in Property and Casualty Insurance and Life Insurance.

Description: Risk management theory prescribes a few legitimate reasons for management to hedge corporate revenues and reduce income volatility. In this paper we will use the oil tanker industry to illustrate some of these strategic considerations and how management can account for them in their decisions regarding whether and how much to hedge. Further work is needed to incorporate these considerations into a broader theoretical framework. Presented at 2010 Enterprise Risk Management Symposium, Society of Actuaries, April 12-15, 2010.

Description: Regularization, by means of trading restrictions, is an effective way to obtain sparse replicating portfolios. By including only the most relevant replicating instruments, the resulting portfolio is more efficient computationally, easier to interpret, and better able to approximate the liability on an out-of-sample basis. The instruments selected depend largely on their respective trading costs. This paper evaluates a number of alternative methods for specifying trading costs. We find that trading costs based on simple statistics of the instrument and liability cash flows are an effective choice in practice. Presented at 2010 Enterprise Risk Management Symposium, Society of Actuaries, April 12-15, 2010.

Description: The paper o ers a simple framework for ranking the common reinsurance struc- tures in practice with the theory of stochastic orders. The basic idea is to slice the space of reinsurance structures into groups by expected loss cost to facilitate the comparisons within the group and between groups. Given the standard risk aversion assumption in economics, a spectrum of reinsurance structures with the same expected loss cost can be compared analytically with one another and sequenced based on their risk coverages under the convex order. The paper then expands the dimension of the comparison to groups of reinsurance structures with di erent expected loss costs, which can be ranked under the increasing convex order and the usual stochastic order. As such, the paper maps out the ordering for the entire space of reinsurance structures and presents it in a ma- trix format for quick reference. The implication of this stochastic ordering to reinsurance pricing is also investigated.

Description: Provides the actuary with a more satisfactory basis for annuity premiums and reserves. It presents a new mortality basis and offers a description of its construction. It also provides a historical review of past mortality tables for annuities. From the Society of Actuaries 50th Anniversary Monograph, M-AV99-1.

Description: This paper presents a random selection method with the Monte Carlo simulation technique in the estimation of loss reserves. The future loss development factors are randomly selected from a weighted empirical distribution of observed loss development factors. This nonparametric approach provides an estimate of the distribution of total loss reserve.

Description: This paper demonstrates that using a conditional probability approach to analyzing investment data yields investment forecast and stock option pricing models which more closely match actual market data, and it demonstrates the impact that conditional probabilities could have on CAPM beta and risk premia calculations. Reprinted from: Journal of Financial and Economic Practice, Vol. 6 No. 2 Spring 2006.

Description: Obsolescence of physical assets and processes is a major component of operational risk for some companies. A simulation experiment shows that managers, who consider the retirement and replacement of individual assets in isolation, have rational incentives, due to risk aversion and uncertainty, to defer the replacement of assets past a time that is optimal from the perspective of the shareholder who owns the entire portfolio of such assets. This results in measurable wealth destruction, —and a demonstrable opportunity to significantly enhance a company’s value. A practical decision model for the replacement timing of fixed, physical assets, which creates wealth by minimizing the long-term consumption of scarce resources, is provided.

Description: Empirical evidence of reported losses suggests that insurance firms are interconnected in a nontrivial way, making them prone to systemic risk. Systemic risk can be viewed as the result of a cascading process, as it unravels throughout a network structure. In response, this work presents a simple analytical model that can simulate this process. The model is subsequently tested upon an empirical dataset via the means of numerical simulations. This work makes three main contributions. First, it provides a novel methodology for quantitatively and objectively assessing the systemic role of individual firms within the insurance domain. Second, it exemplifies the inability of traditional, firm-based information in serving as proxies for mapping these systemic effects. Third, it provides a practical example where network-based information (e.g., Criticality IDX, Sensitivity IDX) can outperform firm-based information (e.g., admissible assets, excess c apital) resulting in increased efficiency in the decision-making process. These findings strengthen the need to account for the interconnected nature of the domain while showcasing some of the potential benefits that can be harvested by doing so.

Description: Empirical evidence of reported losses suggests that insurance firms are interconnected in a nontrivial way, making them prone to systemic risk. Systemic risk can be viewed as the result of a cascading process, as it unravels throughout a network structure. In response, this work presents a simple analytical model that can simulate this process. The model is subsequently tested upon an empirical dataset via the means of numerical simulations. This work makes three main contributions. First, it provides a novel methodology for quantitatively and objectively assessing the systemic role of individual firms within the insurance domain. Second, it exemplifies the inability of traditional, firm-based information in serving as proxies for mapping these systemic effects. Third, it provides a practical example where network-based information (e.g., Criticality IDX, Sensitivity IDX) can outperform firm-based information (e.g., admissible assets, excess c apital) resulting in increased efficiency in the decision-making process. These findings strengthen the need to account for the interconnected nature of the domain while showcasing some of the potential benefits that can be harvested by doing so.