What's good for GM...? Using auto industry stock returns to forecast business cycles and test the Q-theory of investment

Business cycles ; General Motors Corporation ; Investments

Asymmetric cross-sectional dispersion in stock returns: evidence and implications

This paper documents that daily stock returns of both firms and industries are more dispersed when the overall stock market rises than when it falls. This positive relation is conceptually distinct from - and appears unrelated to - asymmetric return correlations. I argue that the source of the relation is positive skewness in sector-specific return shocks. I use this asymmetric behavior to explain a previously-observed puzzle: aggregate trading volume tends to be higher on days when the stock market rises than when it falls. The idea proposed here is that trading is more active on days when the market rises because on those days there is more non-market news on which to trade. I find that empirically, the bulk of the relation between volume and the signed market return is explained by variations in non-market volatility.Stock market ; Econometric models

Term premia and interest rate forecasts in affine models

I find that the standard class of affine models produces poor forecasts of future changes in Treasury yields. Better forecasts are generated by assuming that yields follow random walks. The failure of these models is driven by one of their key features: the compensation that investors receive for facing risk is a multiple of the variance of the risk. This means that risk compensation cannot vary independently of interest rate volatility. I also describe and empirically estimate a class of models that is broader than the standard affine class. These 'essentially affine' models retain the tractability of the usual models, but allow the compensation for interest rate risk to vary independently of interest rate volatility. This additional flexibility proves useful in forming accurate forecasts of future yields.Government securities ; Econometric models ; Forecasting

Forecasting with the term structure: The role of no-arbitrage restrictions

No-arbitrage term structure models impose cross-sectional restrictions among yields and can be used to impose dynamic restrictions on risk compensation. This paper evaluates the importance of these restrictions when using the term structure to forecast future bond yields. It concludes that no cross-sectional restrictions are helpful, because cross-sectional properties of yields are easy to infer with high precision. Dynamic restrictions are useful, but can be imposed without relying on the no-arbitrage structure. In practice, the most important dynamic restriction is that the first principal component of Treasury yields follows a random walk. A simple model built around this assumption produces out-of-sample forecasts that are more accurate than those of a variety of alternative dynamic models

Sharpe ratios in term structure models

Conditional maximum Sharpe ratios implied by fully flexible four-factor and five-factor Gaussian term structure models are astronomically high. Estimation of term structure models subject to a constraint on their Sharpe ratios uncovers properties that hold for a wide range of Sharpe ratios. These robust properties include (a) an inverse relation between a bond's maturity and its average Sharpe ratio; (b) between 15 and 20 percent of annual excess returns to bonds are predictable; and (c) variations in expected excess bond returns are driven by two factors. These factors operate at different frequencies. Nonrobust features include the mean level of the term structure. Unconstrained models imply that investors anticipated much of the decline of interest rates in the 1990s. Constrained models disagree

Forecasting interest rates

This chapter discusses what the asset-pricing literature concludes about the forecastability of interest rates. It outlines forecasting methodologies implied by this literature, including dynamic, no-arbitrage term structure models and their macro-finance extensions. It also reviews the empirical evidence concerning the predictability of future yields on Treasury bonds and future excess returns to holding these bonds. In particular, it critically evaluates theory and evidence that variables other than current bond yields are useful in forecasting. - -Term structure ; affine models ; predicting bond returns ; predicting bond yield

Credit Derivatives in Banking: Useful Tools for Managing Risk?

We model the effects on banks of the introduction of a market for credit derivatives; in particular, credit-default swaps. A bank can use such swaps to temporarily transfer credit risks of their loans to others, reducing the likelihood that defaulting loans trigger the bank's financial distress. Because credit derivatives are more flexible at transferring risks than are other, more established tools such as loan sales without recourse, these instruments make it easier for banks to circumvent the "lemons" problem caused by banks' superior information about the credit quality of their loans. However, we find that the introduction of a credit-derivatives market is not necessarily desirable because it can cause other markets for loan risk-sharing to break down.

Information in (and not in) the Term Structure

Standard approaches to building and estimating dynamic term structure models rely on the assumption that yields can serve as the factors. However, the assumption is neither theoretically necessary nor empirically supported. This paper documents that almost half of the variation in bond risk premia cannot be detected using the cross section of yields. Fluctuations in this hidden component have strong forecast power for both future short-term interest rates and excess bond returns. They are also negatively correlated with aggregate economic activity, but macroeconomic variables explain only a small fraction of variation in the hidden factor

Financial Market Implications of the Federal Debt Paydown

U.S. Treasury securities fill several crucial roles in financial markets: they are a risk-free benchmark, a reference and hedging benchmark, and a reserve asset to the Federal Reserve and other financial institutions. Many of the features that make the Treasury market an attractive benchmark and reserve asset are likely to be adversely affected by the paydown of the federal debt, and recent developments suggest that this may be happening already. Market participants are responding by moving away from Treasuries as a reference and hedging benchmark toward agency debt securities, corporate debt securities, and interest rate swaps. The Federal Reserve is taking steps to adjust its portfolio and should be able to do so with minimal implications for monetary policy