The impact of monetary policy on asset prices

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.     

Bid-Ask Spread Estimation For A Correlated Value Innovation Process

Previous studies of bid-ask spread estimators based on serial covariance in returns document high proportions of positive serial covariances and therefore negative spread estimates. These findings may be due to the effects of time-variation in expected returns. Although purging the effects of time-varying expected returns yields more reasonable results, the bid-ask spread estimates from daily and weekly returns are still materially different. We present a method that avoids the need for removing the effects of time-varying expected returns by using a spread estimator developed directly for a correlated value innovation process. The new spread estimator not only yields more reasonable estimates of the bid-ask spread than the Roll (1984) model, but the spread estimates from daily and weekly returns are almost equal.     

Monetary Policy Uncertainty and the Response of the Yield Curve to Policy Shocks

This paper studies the nonlinear response of the term structure of interest rates to monetary policy shocks and presents a new stylized fact. We show that uncertainty about monetary policy changes the way the term structure responds to monetary policy. A policy tightening leads to a significantly smaller increase in long-term bond yields if policy uncertainty is high at the time of the shock. We also look at the decomposition of bond yields into expectations about future policy and the term premium. The weaker response of yields is driven by the fall in term premia, which fall more strongly if uncertainty about policy is high. Conditional on a monetary policy shock, higher uncertainty about monetary policy tends to make securities with longer maturities relatively more attractive to investors. As a consequence, investors demand even lower term premia. These findings are robust to the measurement of monetary policy uncertainty, the definition of the monetary policy shock, and to changing the model specification.     

Credibility in Favor of Unlucky Insureds

Abstract

The classical Bühlmann credibility formula estimates the hypothetical mean of a particular insured, or risk, by a weighted average of the grand mean of the collection of risks with the sample mean of the given insured. If the insured is unfortunate enough to have had large claims in the previous policy period(s), then the estimate of future claims for that risk will also be large. In this paper we provide actuaries with a method for not overly penalizing an unlucky insured while still targeting the goal of accuracy in the estimate. We propose a credibility estimator that minimizes the expectation of a linear combination of a squared-error term and a first-derivative term. The squared-error term measures the accuracy of the estimator, while the first-derivative term constrains the estimator to be close to constant.     

The great moderation of the term structure of UK interest rates

The conduct of monetary policy, the term structure of interest rates and the structure of the economy in the UK have changed over the post-WWII period. We model the interaction between the macroeconomy and financial markets using a time-varying VAR augmented with the factors from the yield curve. There is evidence of a great moderation in the dynamics of the yield curve, with the factors being persistent and volatile before the introduction of inflation targeting in 1992 but becoming stable afterwards. The introduction of time-variation in the Factor Augmented VAR improves the fit of the model and results in expectation hypothesis consistent yields that are close to actual yields, even at long maturities. Monetary policy shocks had a significant impact on the volatility of inflation, output and the policy rate over the pre-inflation targeting era, but their contribution has been negligible under the current regime. Shocks to the level of the yield curve accounted for a large fraction of inflation variability only before 1992.     

Characteristic-based mean-variance portfolio choice

We study empirical mean-variance optimization when the portfolio weights are restricted to be direct functions of underlying stock characteristics such as value and momentum. The closed-form solution to the portfolio weights estimator shows that the portfolio problem in this case reduces to a mean-variance analysis of assets with returns given by single-characteristic strategies (e.g., momentum or value). In an empirical application to international stock return indexes, we show that the direct approach to estimating portfolio weights clearly beats a naive regression-based approach that models the conditional mean. However, a portfolio based on equal weights of the single-characteristic strategies performs about as well, and sometimes better, than the direct estimation approach, highlighting again the difficulties in beating the equal-weighted case in mean-variance analysis. The empirical results also highlight the potential for ‘stock-picking’ in international indexes using characteristics such as value and momentum with the characteristic-based portfolios obtaining Sharpe ratios approximately three times larger than the world market.     

An analysis of contagion among Asian countries using the canonical model of contagion

Understanding the dependence among economies is relevant to policy makers, central banks and investors in the decision-making process. One important issue for study is the existence of contagion among economies. This work considers the Canonical Model of Contagion by Pesaran and Pick (Journal of Economic Dynamics and Control, 2007), which differentiates contagion from interdependence. The ordinary least squares estimator of this model is biased by the endogenous variables in the model. In this study, instrumental variables are used to decrease the bias of the ordinary least squares estimator. The model is extended to the case of heteroskedastic errors, features that are generally found in financial data. We postulate the conditional volatility of the performance indices as instrumental variables and analyze the validity of these instruments using Monte Carlo simulations. Monte Carlo simulations estimate the distributions of the estimators under the null hypothesis. Finally, the canonical model of contagion is used to analyze the contagion among seven Asian countries.     

U.S. Monetary Policy and International Bond Markets

This paper analyzes how U.S. monetary policy affects the pricing of dollar‐denominated sovereign debt. We document that yields on dollar‐denominated sovereign bonds are highly responsive to U.S. monetary policy surprises—during both the conventional and unconventional policy regimes—and that the passthrough of unconventional policy to foreign bond yields is, on balance, comparable to that of conventional policy. In addition, a conventional U.S. monetary easing (tightening) leads to a significant narrowing (widening) of credit spreads on sovereign bonds issued by countries with a speculative‐grade credit rating but has no effect on the corresponding weighted average of bilateral exchange rates for a basket of currencies from the same set of risky countries; this indicates that an unanticipated tightening of U.S. monetary policy widens credit spreads on risky sovereign debt directly through the financial channel, as opposed to indirectly through the exchange rate channel. During the unconventional policy regime, yields on both investment‐ and speculative‐grade sovereign bonds move one‐to‐one with policy‐induced fluctuations in yields on comparable U.S. Treasuries. We also examine whether the response of sovereign credit spreads to US monetary policy differs between policy easings and tightenings and find no evidence of such asymmetry.     

China’s official rates and bond yields

Recent research shows that bond yields are influenced by monetary policy decisions. To learn how this works in a bond market that differs significantly from those in the US and Europe, we model Chinese bond yields using the one-year deposit interest rate as a state variable. We also include the spread between the one-year market interest rate and the one-year deposit interest rate as another factor. The model is developed in an affine framework and closed-form solutions are obtained. We then test the model empirically with a Markov Chain Monte Carlo simulation procedure. The results show that the new model that incorporates the official rate in China characterizes the changing shape of the yield curve well.     

Economic determinants of the nominal treasury yield curve

Macroeconomic shocks account for most of the variability of nominal Treasury yields, inducing parallel shifts in the level of the yield curve. We develop a new approach to identifying macroeconomic shocks that exploits model-based empirical shock measures. Technology shocks shift yields through their effect on expected inflation and the term premium. Shocks to preferences for current consumption affect yields through their impact on real rates and expected inflation. For both shocks, the systematic reaction of monetary policy is an important transmission pathway. We find little evidence that fiscal policy shocks are an important source of interest rate variability.     

Modeling daily price limits

This paper characterizes the behavior of observed asset prices under price limits and proposes the use of two-limit truncated and Tobit regression models to analyze regression models whose dependent variable is subject to price limits. Through a proper arrangement of the sample, these two models, the estimation of which is easy to implement, are applied only to subsets of the sample under study, rather than the full sample. Using the estimation of simple linear regression model as an example, several Monte Carlo experiments are conducted to compare the performance of the maximum likelihood estimators (MLEs) based on these two models and a generalized method of moments (GMM) estimator developed by K. C. John Wei and R. Chiang. The results show that under different price limits and various distributional assumptions for the error terms, the MLEs based on the two-limit Tobit and truncated regression models and the GMM estimator perform reasonably well, while the naive OLS estimator is downward biased. Overall, the MLE based on the two-limit Tobit model outperforms the other estimators.     

Nonlinearities in the Brazilian Yield Curve

ABSTRACT

The article indicates the yield curve can be modeled using a continuous estimator as smooth transition regression, instead of traditional switch models, because bonds are traded continuously in the financial market. The results indicate that nonlinearity in the yield curve explains the pitfalls of monetary policy. The positive correlation between inflation and spread is consistent with a rise on uncertainty due to inflation risk or seems to indicate Brazilian Central Bank’s monetary policy credibility in the sample period. Therefore, if dependence on international capital exists, the Brazilian economic policy makers must monitor the movements in yield and analyze its feedback frequently in order to guide their plans and decisions.     

The Determinants of the Treasury Security Yield Curve

Investors' security demands and two points on the yield curve are jointly determined using a disaggregated structural model of the U.S. Treasury securities market. The empirical results indicate that the structural model is capable of accurately explaining Treasury yields and that changes in a variety of nonyield variables affect the yield curve. Among these nonyield variables are Treasury security supplies, which are found to have significant but somewhat volatile impacts depending on investors' wealth flows. The within-sample predictions from the structural model are also compared to those of a naive model.     

Self-oriented monetary policy,global financial markets and excess volatility of international capital flows

This paper explores the nature of macroeconomic spillovers from advanced economies to emerging market economies (EMEs) and the consequences for independent use of monetary policy in EMEs. We first empirically document that a US contractionary monetary policy shock leads a retrenchment in EME capital flows, a fall in EME GDP, and an exchange rate depreciation. We construct a theoretical model that can help to account for these findings. In the model, macroeconomic spillovers may be exacerbated by financial frictions. Absent financial frictions, international spillovers are minor, and an inflation targeting rule represents an effective policy for the EME. With frictions in financial intermediation, however, spillovers are substantially magnified, and an inflation targeting rule has little advantage over an exchange rate peg. However, an optimal monetary policy markedly improves on the performance of naive inflation targeting or an exchange rate peg. Furthermore, optimal policies don't need to be coordinated across countries. A non-cooperative, self-oriented optimal policy gives results very similar to those of a global cooperative optimal policy.     

The changing relation between the Canadian and U.S. yield curves

The term structures of Canada and of the United States, two countries with historically interdependent economic ties, have been closely linked. We investigate the link between Canadian and U.S. yield curves and show previously strong correlations between yield curve components dissipate after Canadian monetary policy reforms in the early 1990s. We attribute the separated ties to the adoption of explicit inflation targets in 1991 and the maintenance of credibility in price stability as a central policy goal by the Bank of Canada. The effect is particularly evident in the diminished cross-country correlations of the short term bond yields. Additionally, there exists strong evidence of cointegration before the reforms, evidence which weakens after the policy change date. Lastly, the results on the term structure are shown using a vector autoregression with an endogenously determined break date for Canadian and U.S. estimates of the three-factor Nelson and Siegel (1987) yield curve model.     

Structural models of corporate bond pricing with maximum likelihood estimation

This paper empirically examines the proxy, volatility-restriction (VR) and maximum likelihood (ML) approaches to implementing structural corporate bond pricing models, and documents that ML estimation is the best among the three implementation methods. Empirical studies using either the proxy approach or the VR method conclude that barrier-independent models significantly underestimate corporate bond yields. Although barrier-dependent models tend to overestimate the yield on average, they generate a sizable degree of underestimation. The present paper shows that the proxy approach is an upwardly biased estimator of the corporate assets and makes the empirical framework work systematically against structural models of corporate bond pricing. The VR approach may generate inconsistent corporate bond prices or may fail to give a positive corporate bond price for some structural models. When the Merton, LS, BD and LT models are implemented with ML estimation, we find substantial improvement in their performances. Our empirical analysis shows that the LT model is very accurate for predicting short-term bond yields, whereas the LS and BD models are good predictors for medium-term and long-term bonds. The Merton model however significantly overestimates short-term bond yields and underestimates long-term bond yields. Unlike empirical studies in the past, the Merton model implemented with ML estimation does not consistently underestimate corporate bond yields.     

A maximum likelihood approach to volatility estimation for a Brownian motion using high,low and close price data

Abstract

Volatility plays an important role in derivatives pricing, asset allocation, and risk management, to name but a few areas. It is therefore crucial to make the utmost use of the scant information typically available in short time windows when estimating the volatility. We propose a volatility estimator using the high and the low information in addition to the close price, all of which are typically available to investors. The proposed estimator is based on a maximum likelihood approach. We present explicit formulae for the likelihood of the drift and volatility parameters when the underlying asset is assumed to follow a Brownian motion with constant drift and volatility. Our approach is to then maximize this likelihood to obtain the estimator of the volatility. While we present the method in the context of a Brownian motion, the general methodology is applicable whenever one can obtain the likelihood of the volatility parameter given the high, low and close information. We present simulations which indicate that our estimator achieves consistently better performance than existing estimators (that use the same information and assumptions) for simulated data. In addition, our simulations using real price data demonstrate that our method produces more stable estimates. We also consider the effects of quantized prices and discretized time.     

Disentangling the effect of jumps on systematic risk using a new estimator of integrated co-volatility

We propose a new threshold–pre-averaging realized estimator for the integrated co-volatility of two assets using non-synchronous observations with the simultaneous presence of microstructure noise and jumps. We derive a noise-robust Hayashi–Yoshida estimator that allows for very general structure of jumps in the underlying process. Based on the new estimator, different aspects and components of co-volatility are compared to examine the effect of jumps on systematic risk using tick-by-tick data from the Chinese stock market during 2009–2011. We find controlling for jumps contributes significantly to the beta estimation and common jumps mostly dominate the jump’s effect, but there is also evidence that idiosyncratic jumps may lead to significant deviation. We also find that not controlling for noise and jumps in previous realized beta estimations tend to considerably underestimate the systematic risk.     

Endogeneity and the dynamics of internal corporate governance

We use a well-developed dynamic panel generalized method of moments (GMM) estimator to alleviate endogeneity concerns in two aspects of corporate governance research: the effect of board structure on firm performance and the determinants of board structure. The estimator incorporates the dynamic nature of internal governance choices to provide valid and powerful instruments that address unobserved heterogeneity and simultaneity. We re-examine the relation between board structure and performance using the GMM estimator in a panel of 6,000 firms over a period from 1991 to 2003, and find no causal relation between board structure and current firm performance. We illustrate why other commonly used estimators that ignore the dynamic relationship between current governance and past firm performance may be biased. We discuss where it may be appropriate to consider the dynamic panel GMM estimator in corporate governance research, as well as caveats to its use.     

Maximum penalized quasi-likelihood estimation of the diffusion function

We develop a maximum penalized quasi-likelihood estimator for estimating in a non-parametric way the diffusion function of a diffusion process, as an alternative to more traditional kernel-based estimators. After developing a numerical scheme for computing the maximizer of the penalized maximum quasi-likelihood function, we study the asymptotic properties of our estimator by way of simulation. Under the assumption that overnight London Interbank Offered Rates (LIBOR), the USD/EUR, USD/GBP, JPY/USD, and EUR/USD nominal exchange rates, and the 1-month, 3-month Treasury bill yields, and 30-year Treasury bond yields are generated by diffusion processes, we use our numerical scheme to estimate the diffusion function.