Components of Insurance Firm Value and the Present Value of Liabilities

In this paper, we discuss the relation between the market value of insurance company owners' equity and various components that contribute to that value. The effect of firm insolvency risk on each component of value is discussed in turn. One natural consequence of this analysis is a conceptual framework for estimating the value of insurance liabilities.

Economic Valuation Models for Insurers

Recently much attention has been given to the approaches insurers undertake in valuing their liabilities and assets. For example, in 1994 the American Academy of Actuaries created a Fair Valuation of Liabilities Task Force to address the issue. In 1997, the Academy established a Valuation Law Task Force and a Valuation Tools Working Group to investigate the various valuation approaches extant and to make recommendations on which models are best suited to the task. Much of the published work has focused on attributes of the various models, their strengths and shortcomings. Some of the work has addressed the larger questions, but in our view, it is useful and necessary to provide a taxonomy of approaches and evaluate them in a systematic way in accordance with how well they achieve their aims. In this paper we focus primarily on the economic valuation of insurance liabilities, although we do address some valuation issues for assets. We begin in Section I by defining insurance liabilities. Next, in Section II, we discuss the criteria for a good economic valuation model. This is followed by a taxonomy of valuation models in Section III. In Section IV, we examine insurance liabilities in the context of this taxonomy and identify the minimum requirements of an economic valuation approach that purports to value them adequately. An illustration of the application of a modern valuation model is given in Section V. We conclude in Section VI by discussing some limitations of our analysis, and offer some recommendations for implementation.

Evaluating Pension Insurance Pricing

The Pension Benefit Guaranty Corporation (PBGC)’s Pension Insurance Modeling System (PIMS) model has taken on the Herculean task of modeling in detail and under many scenarios the cash outflows associated with the pension obligations they have assumed. This paper’s comments are focused almost entirely upon PBGC’s termination liabilities, and address four pressing issues: (1) the need to discount the liability stream by current riskless interest rates instead of using corporate bond rates that reflect credit risk, call risk, and other risks, or using some ad hoc prescribed average of past rates; (2) the need to use a term structure of interest rates; (3) the need to employ more useful investment management benchmarks; and (4) how to implement a relevant and rigorous liability benchmark

Default risk and the effective duration of bonds

Basis risk is the risk attributable to uncertain movements in the spread between yields associated with a particular financial instrument or class of instruments, and a reference interest rate over time. There are seven types of basis risk: Yields on 1) Long-term versus short-term financial instruments, 2) Domestic currency versus foreign currencies, 3) Liquid versus illiquid investments, 4) Bonds with higher or lower sensitivity to changes in interest rate volatility, 5) Taxable versus tax-free instruments, 6) Spot versus futures contracts and 7) Default-free versus non-default-free securities. Basis risk makes it difficult for the fixed-income portfolio manager to measure the portfolio's exposure to interest rate risk, heightens the anxiety of traders and arbitrageurs who are hedging their investments, and compounds the financial institution's problem of matching assets and liabilities. Much attention has been paid to the first type of basis risk. In recent years, attention has turned toward understanding the relation between credit risk and duration. The authors focus on that, emphasizing the importance of taking credit risk into account when computing measures of duration. The consensus of all work in this area is that credit risk shortens the effective duration of corporate bonds. The authors estimate how much durations shorten because of credit risk, basing their estimates on observable data and easily estimated bond pricing parameters.Banks&Banking Reform,Payment Systems&Infrastructure,International Terrorism&Counterterrorism,Economic Theory&Research,Insurance&Risk Mitigation,Environmental Economics&Policies,Strategic Debt Management,Economic Theory&Research,Banks&Banking Reform,Insurance&Risk Mitigation

A Note on Scenario Analysis in the Measurement of Operational Risk Capital: A Change of Measure Approach

Abstract Since I circulated a working paper (coauthored with Kabir Dutta) entitled "Scenario Analysis in the Measurement of Operational Risk Capital: A Change of Measure Approach" on the Wharton Financials Institutions Center website in March of 2010, many different questions have been received concerning the methodology we used. While we addressed those questions at an individual level, in this note I would like to address the questions for the readers at large

The Effect of Transaction Size on Off-the-Run Treasury Prices

A price pressure effect is implied by segmentation in the market for a security. An empirical property of a segmented market is that the price of the security is sensitive to supply and demand conditions for that specific security, absent changes in risk and absent any new information. This paper examines intra-day trading data from the inter-dealer broker market for U.S. Treasury securities and finds that there is a price pressure effect in the off-the-run Treasury market. Thus, securities that would appear to be very close substitutes, i.e., on-the-run and off-the-run Treasury bonds, behave as if there is some degree of market segmentation. There have been several studies of price pressure in the equity market and Treasury bill market but this is the first study of the off-the-run Treasury note and bond market to investigate a price pressure effect using intra-day data. It is also the first study to analyze price pressure through matched pairs of securities that differ only in liquidity and with high frequency data.

Scenario Analysis in the Measurement of Operational Risk Capital: A Change of Measure Approach

At large financial institutions, operational risk is gaining the same importance as market and credit risk in the capital calculation. Although scenario analysis is an important tool for financial risk measurement, its use in the measurement of operational risk capital has been arbitrary and often inaccurate. We propose a method that combines scenario analysis with historical loss data. Using the Change of Measure approach, we evaluate the impact of each scenario on the total estimate of operational risk capital. The method can be used in stress-testing, what-if assessment for scenario analysis, and Loss Given Default estimates used in credit evaluations

Statistical String Theory for Courts: If the Data Don\u27t Fit . . . .

The primary purpose of this article is to provide courts with an important new tool for applying the correct probability distribution to a given legal question. In areas as diverse as criminal prosecutions and civil lawsuits alleging securities fraud, courts must assess the relevance and reliability of statistical data and the inferences drawn therefrom. But, courts and ex-pert witnesses often make mistaken assumptions about what probability distributions are appropriate for their analyses. Using the wrong probability distribution can lead to invalid factual conclusions and unjustified legal outcomes. To deal with this problem, we propose the use of a unifying statistical string theory - the g-and-h distribution - in legal settings. This parent distribution subsumes many other distributions and spans the widest range of possible skewness-kurtosis combinations. The capacity of the g-and-h distribution to accommodate such a wide variety of data can alleviate judicial fact finders of the difficult task of trying to correctly select among competing distributions. Finally, we report the successful use of this statistical tool in a trial setting for financial data analysis - showing that it can produce more accurate inferences, than those drawn from alternative distributions, and these differences can be judicially decisive