The monetary policy dilemma: Will interest rates have to rise?

UK interest rates are now at their lowest level for more than two decades, and the government is hoping that interest rates can be kept at a low and sustainable level comparable to the 1960s. Indeed, some commentators are calling for still lower interest rates to offset the risk that the £12bn tax increases and cuts in government spending that will come into effect in the next financial year will lead to stagnant consumer spending and a stalled recovery. Against this must be weighed the risk that the recent very good run of inflation figures will prove temporary. Both headline and underlying inflation will be pushed up by indirect tax increases and there is the possibility that wages will follow too, as employees seek to maintain their living standards in a tightening labour market. That risk would point to a much more cautious monetary policy stance and the possibility that the government may need to raise rates from their present level if it is to achieve its inflation objective. The Chancellor faces a clear dilemma. In this Viewpoint, we assess the evidence available to guide him in his decisions and draw out the implications for the future path of interest rates.     

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)     

Evidence on the Timing and Determinants of Overfunded Pension Plan Termination

This paper examines the factors associated with the timing of overfunded pension plan termination.     

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.     

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.     

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.     

Multimarket Trading and Liquidity: Theory and Evidence

We develop a new model of multimarket trading to explain the differences in the foreign share of trading volume of internationally cross‐listed stocks. The model predicts that the trading volume of a cross‐listed stock is proportionally higher on the exchange in which the cross‐listed asset returns have greater correlation with returns of other assets traded on that market. We find robust empirical support for this prediction using stock return and volume data on 251 non‐U.S. stocks cross‐listed on major U.S. exchanges.