This paper studies the transmission of monetary policy to the stock market through investors’ discount factors. To isolate this channel, we investigate the effect of US monetary policy surprises on the ratio of prices of the same stock listed simultaneously in Hong Kong and Mainland China, and thereby control for revisions in cash-flow expectations. We find this channel to be strong and asymmetric, with the effect driven by surprise monetary policy interest rate cuts. A 100 basis point surprise cut results in a 30 basis point increase in the ratio of stock prices over 5 days. These results suggest significant slow-moving reductions in stock market risk premia following accommodating monetary policy surprises.

We compare the differences between the Chinese and U.S. bond risk premia. We find that the expectations hypothesis fails in the two bond markets: We identify the Chinese and U.S. bond time-varying risk premia by forecasting the corresponding excess return of n-year bond using the n-year forward rate and n-year forward spread, respectively. To focus on the systematical forecasts, we then combine the forward rates at different maturities as the return-forecast factors. Unlike the one-factor model introduced by Cochrane and Piazzesi (2005), a two-factor model including level- and slope-based factors explains significantly Chinese bond premia with R2 up to 68%. More importantly, the slope-based factor sharply improves the performance of test. The results are robust with respect to measurement errors, multicollinearity and small-sample biases. Out-of-sample tests show that, in recent years, the U.S. bond market changes drastically, and tends to be like the Chinese market. We use the empirical results to calibrate the parameters of affine model, and find that the differences of bond premia between the two markets are caused by the differences of dynamics of state variables and risk attitude of investor.

Studies of the dynamics of bond risk premia that do not account for the corresponding dynamics of bond risk are hard to interpret. We propose a new approach to modeling bond risk and risk premia. For each of the US and China, we reduce the government bond market to its first two principal-component bond-factor portfolios. For each bond-factor portfolio, we estimate the joint dynamics of its volatility and Sharpe ratio as functions of yield curve variables, and of VIX in the US. We have three main findings.(1) There is an important second factor in bond risk premia. (2) Time variation in bond return volatility is as important as time variation in bond Sharpe ratios. (3) Bond risk premia are solely compensation for bond risk, as no-arbitrage theory predicts. Our approach also allows us to document interesting cyclical and secular time-variation in the term structure of bond risk premia in both the US and China.

In this paper, using a set of zero yield curve data of China’s government bonds and credit bonds, along with China’s aggregate credit risk measures, and macroeconomic variables from 2006 to 2013, we document a puzzle of counter-credit-risk corporate yield spreads. We interpret this puzzle as a symptom of the immaturity of China’s credit bond market, which reveals a distorted pricing mechanism latent in the fundamental of this market. As by-products of our analysis, we also find interesting results about relations between corporate yield spreads and interest rates as well as risk premia and the stock index, and these results are somewhat attributed to this puzzle.

Our study is the first to examine the effect of policy instability on interest rates. China offers a natural setting for the experiment because financial market liberalization policy flip-flops recur. When a policy is reversed, interest rate level and spread can increase or decrease in the interbank repo market. Accounting for the bureaucratic quality of policymaking, we find that the nonpredictable, non-credible and non-timely reversal of an existing policy is related to higher interest rate spread and volatility, which represent higher risk premia in interest rates. Conversely, predictable, credible and timely reversal is related to lower interest rate spread and volatility. Our results suggest that bureaucratic quality is a moderating factor and high bureaucratic quality can reduce the risk premia of policy instability being priced in interest rates.

We examine the process of stock prices adjusting to information conveyed by the trading process. Using the price impact of a trade to measure its information content, our analysis shows that the weekly price impact of market transactions has significant cross-sectional predictive power for returns in the subsequent week. The effect is sensitive to the level of informational asymmetry and is not due to excess liquidity demands or variations in rational risk premia. This finding suggests that prices may slowly incorporate trading information. We then characterize the key channel through which price underreaction occurs. We find that the price impact contains information that is not fully captured by public order flows and that a lead-lag effect exists regarding the arrival of information to different groups of investors. Hong and Stein’s (1999) gradual-information-diffusion theory seems the most likely explanation for price underreaction.