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Estimating the response of asset prices to changes in monetary policy is complicated by the endogeneity of policy decisions and the fact that both interest rates and asset prices react to numerous other variables. This paper develops a new estimator that is based on the heteroskedasticity that exists in high-frequency data. We show that the response of asset prices to changes in monetary policy can be identified based on the increase in the variance of policy shocks that occurs on days of FOMC meetings and of the Chairman's semi-annual monetary policy testimony to Congress. The identification approach employed requires a much weaker set of assumptions than needed under the “event-study” approach that is typically used in this context. The results indicate that an increase in short-term interest rates results in a decline in stock prices and in an upward shift in the yield curve that becomes smaller at longer maturities. The findings also suggest that the event-study estimates contain biases that make the estimated effects on stock prices appear too small and those on Treasury yields too large.

There is a considerable amount of interest in understanding the interactions between asset prices and monetary policy. In previous research (Rigobon and Sack, 2003), we found that short-term interest rates react significantly to movements in broad equity price indexes, likely reflecting the expected endogenous response of monetary policy to the impact of stock price movements on aggregate demand. This paper attempts to estimate the other side of the relationship: how asset prices react to changes in monetary policy. This relationship is an important topic for several reasons. From the perspective of monetary policymakers, having reliable estimates of the reaction of asset prices to the policy instrument is a critical step in formulating effective policy decisions. Much of the transmission of monetary policy comes through the influence of short-term interest rates on other asset prices, as it is the movements in these other asset prices—including longer-term interest rates and stock prices—that determine private borrowing costs and changes in wealth, which in turn influence real economic activity. Financial market participants are likely to be equally interested in this topic. Monetary policy exerts a considerable influence on financial markets, as evidenced by the extensive attention that the Federal Reserve receives in the financial press. Thus, having accurate estimates of the responsiveness of asset prices to monetary policy is an important component of formulating effective investment and risk management decisions. Several difficulties arise in estimating the responsiveness of asset prices to monetary policy, though. First, short-term interest rates are simultaneously influenced by movements in asset prices, resulting in a difficult endogeneity problem. Second, a number of other variables, including news about the economic outlook, likely have an impact on both short-term interest rates and asset prices. These two considerations complicate the identification of the responsiveness of asset prices under previously used methods. To address these issues, we develop an estimator that identifies the response of asset prices based on the heteroskedasticity of monetary policy shocks. In particular, we assume that the variance of monetary policy shocks is higher on days of FOMC meetings and of the Chairman's semi-annual monetary policy testimony to Congress, when a larger portion of the news hitting markets is about monetary policy. We show that the shift in the variance of the policy shocks on those dates is sufficient to measure the responsiveness of asset prices to monetary policy. Our approach allows us to identify the parameter of interest under a weaker set of assumptions than required under the approach that other papers have taken in this context. In particular, other papers have typically estimated ordinary-least-squares (OLS) regressions on FOMC dates, which has been called the “event-study” method. We show that the event-study approach is an extreme case of our heteroskedasticity-based estimator in which the shift in the variance of the policy shock is large enough to dominate all other shocks. In contrast, the heteroskedasticity-based estimator that we develop requires only an increase in the relative importance of the policy shock. Thus, our estimator can be used to test whether the stronger assumptions under the event-study approach are valid, and, correspondingly, the extent to which the event-study estimates are biased. The paper proceeds as follows. Section 2 discusses the problems of simultaneous equations and omitted variables in estimating the responsiveness of asset prices, demonstrating that some bias may remain in the coefficients estimated under the event-study approach unless some strong assumptions are met. Section 3 describes our identification approach based on the heteroskedasticity of monetary policy shocks and compares the assumptions needed to those required under the event-study approach. It demonstrates that the identification method can be implemented as a simple instrumental variables regression or as a generalized-method-of-moments estimator. Results on the responsiveness of stock prices and longer-term interest rates to monetary policy using both the event-study and the heteroskedasticity procedures are presented in Section 4, and Section 5 concludes.

This paper has demonstrated that the response of equity prices and market interest rates to changes in monetary policy can be estimated from the heteroskedasticity of policy shocks that takes place on particular dates, including days of FOMC meetings and of the Chairman's semi-annual monetary policy testimony to Congress. We show that the correlation between the policy rate and these other asset prices shifts importantly on those dates, as one would expect given the greater importance of policy shocks. Using this time series property, we define a heteroskedasticity-based estimator of the response of asset prices to monetary policy. We implement this method using two alternative approaches—simple instrumental variables regression and GMM. The results indicate that increases in the short-term interest rate have a negative impact on stock prices, with the largest effect on the Nasdaq index. According to the estimates, a 25 basis point increase in the three-month interest rate results in a 1.7% decline in the S&P 500 index and a 2.4% decline in the Nasdaq index. The results also indicate that the short-term rate has a significant positive impact on market interest rates, with the largest effect on rates with shorter maturities. Indeed, in response to a 25 basis point increase in the three-month rate, near-term eurodollar futures rates increase by more than 25 basis points, and the effect gradually diminishes as the contract horizon lengthens. Similarly, short- and intermediate-term Treasury yields increase considerably, and longer-term Treasury yields increase little or not at all. Perhaps most importantly, our approach can be used to test the assumptions implicit in the event-study method. The event-study method can be seen as an extreme case of our heteroskedasticity-based estimator, in which the shift in the variance of the policy shock is so large that it dominates all other shocks. However, such a strong assumption is not needed, as our heteroskedasticity-based estimator requires only a shift in the relative importance of the shocks. Thus, the differences across the coefficients found under the event study and the heteroskedastic-based methods can be used to statistically test whether the assumptions underlying the event-study approach are satisfied. Such an evaluation has been absent from the literature, despite the widespread use of the event-study approach. The results suggest that there is some modest bias in the event-study estimates. In particular, the heteroskedasticity-based results find a larger negative impact of monetary policy on the stock market and a smaller positive impact on market interest rates. The differences in the estimates for equity prices are not statistically significant, indicating that the event-study assumptions cannot be formally rejected in that case. For futures rates and Treasury yields, the results are mixed, with the bias in the event-study estimates found to be statistically significant in some cases but not others. Regardless of the significance of these tests, though, the heteroskedasticity-based estimator, by requiring weaker assumptions than the event-study estimator, likely provides a more accurate measure of the responsiveness of various asset prices to monetary policy.