Federal Deposit Insurance,Regulatory Policy,and Optimal Bank Capital*

This paper seeks to explain the combination of explicit and implicit pricing for deposit insurance employed by the FDIC. Essentially, the FDIC sells two products—insurance and regulation. To span the product space, it must and does set two prices. We argue that the need to establish regulatory disincentives to bank risk-taking is the heart of the controversy over the adequacy of bank capital and that the ability to close risky banks before exhausting their charter value (i.e., the value of their right to continue in business) stands at the center of these disincentives and in front of the FDIC's insurance reserves.     

A Practical Framework for the Analysis of Social Security Reform

‘When I use a word’, Humpty Dumpty said in a rather scornful tone, ‘it means just what I choose it lo mean — neither more nor less’. (Through the Looking Glass, Ch. 6)     

A Nonparametric Approach to Pricing and Hedging Derivative Securities Via Learning Networks

We propose a nonparametric method for estimating the pricing formula of a derivative asset using learning networks. Although not a substitute for the more traditional arbitrage-based pricing formulas, network-pricing formulas may be more accurate and computationally more efficient alternatives when the underlying asset's price dynamics are unknown, or when the pricing equation associated with the no-arbitrage condition cannot be solved analytically. To assess the potential value of network pricing formulas, we simulate Black-Scholes option prices and show that learning networks can recover the Black-Scholes formula from a two-year training set of daily options prices, and that the resulting network formula can be used successfully to both price and delta-hedge options out-of-sample. For comparison, we estimate models using four popular methods: ordinary least squares, radial basis function networks, multilayer perceptron networks, and projection pursuit. To illustrate the practical relevance of our network pricing approach, we apply it to the pricing and delta-hedging of S&P 500 futures options from 1987 to 1991.     

Trading Volume: Implications of an Intertemporal Capital Asset Pricing Model

We derive an intertemporal asset pricing model and explore its implications for trading volume and asset returns. We show that investors trade in only two portfolios: the market portfolio, and a hedging portfolio that is used to hedge the risk of changing market conditions. We empirically identify the hedging portfolio using weekly volume and returns data for U.S. stocks, and then test two of its properties implied by the theory: Its return should be an additional risk factor in explaining the cross section of asset returns, and should also be the best predictor of future market returns.     

The Integration of Insurance and Taxes in Corporate Pension Strategy

This paper examines the implications of the joint effects of insurance and taxes for the optimal corporate pension strategy. It is shown that neither the “mini-max” nor the “maxi-min” strategy advocated by previous authors is necessarily best in corporate pension management. In the presence of capital market imperfections, the analysis via a single-period contingent-claims model indicates that optimal corporate pension strategy in both asset-allocation and funding decisions can be a noncorner interior solution.     

Optimal Hedging in Futures Markets with Multiple Delivery Specifications

Nearly all futures contracts allow delivery of any of several qualities of the underlying asset. Consequently, the price of the futures contract is associated more with the price of the expected cheapest deliverable variety than with the price of the par-delivery variety. The delivery specifications introduce a delivery risk for every hedger in the market. We derive the optimal hedging strategies in these markets. Their hedging effectiveness is evaluated for wheat futures contracts in Chicago. Hedging optimally would have significantly reduced the variance of the rates of return on hedges while yielding similar mean returns.     

How to Discount Cashflows with Time-Varying Expected Returns

While many studies document that the market risk premium is predictable and that betas are not constant, the dividend discount model ignores time‐varying risk premiums and betas. We develop a model to consistently value cashflows with changing risk‐free rates, predictable risk premiums, and conditional betas in the context of a conditional CAPM. Practical valuation is accomplished with an analytic term structure of discount rates, with different discount rates applied to expected cashflows at different horizons. Using constant discount rates can produce large misvaluations, which, in portfolio data, are mostly driven at short horizons by market risk premiums and at long horizons by time variation in risk‐free rates and factor loadings.     

Is the Real Interest Rate Stable?

Univariate time-series models for consumption, nominal interest rates, and prices each appear to have a single unit root before 1979. If nominal interest rates have a unit root but inflation and inflation forecast errors do not, then ex ante real interest rates have a unit root and are therefore nonstationary. This deduction does not depend on the properties of the unobservable ex post observed real return, which combines the ex ante real interest rate and inflation-forecasting errors. The unit-root characteristic of real interest rates is puzzling from at least two perspectives: many models imply that the growth rate of consumption and the real interest rate should have similar time-series characteristics; also, nominal returns for other assets (e.g., stocks and bonds) appear to have different times-series properties from those of treasury bills.