Estimates of canonical affine term structure model parameters are highly sensitive to sample periods. For example, depending on whether the sample starts in 1961 or 1981, the 5-5 forward risk-neutral rate for September 1981 differs by 4.6 percentage points or 98% of the latter. The estimated response of this rate to high-frequency monetary policy shocks differs by a factor of three, even within a fixed sample for the monetary policy transmission regression. We suggest that a shifting endpoint model can mitigate these issues. Additionally, we provide new estimates of the effects of monetary policy shocks on long-term risk-neutral rates.

We construct a daily Chinese Housing Market Sentiment Index by applying GPT-4o to Chinese news articles. Our method outperforms traditional models in several validation tests, including a test based on a suite of machine learning models. Applying this index to household-level data, we find that after monetary easing, an important group of homebuyers (who have a college degree and are aged between 30 and 50) in cities with more optimistic housing sentiment have lower responses in non-housing consumption, whereas for homebuyers in other age-education groups, such a pattern does not exist. This suggests that current monetary easing might be more effective in boosting non-housing consumption than in the past for China due to weaker crowding-out effects from pessimistic housing sentiment. The paper also highlights the need for complementary structural reforms to enhance monetary policy transmission in China, a lesson relevant for other similar countries. Methodologically, it offers a tool for monitoring housing sentiment and lays out some principles for applying generative AI models, adaptable to other studies globally.

We examine how Federal Open Market Committee (FOMC) meetings influence international stock returns, highlighting that the standard Fed news channel creates an even-week pattern in the United States and other highly integrated developed markets. By analyzing the Chinese market, we demonstrate that the news channel contributes to higher returns, operating in non-US countries even without international equity flows. Additionally, we identify an uncertainty channel that produces a contrasting odd-week pattern. Placebo tests indicate that the effectiveness of the uncertainty channel may depend on the financial market’s openness. Overall, our research enriches and extends the existing view on how the Federal Reserve, as the leader of central banks, shapes international stock market returns throughout the entire FOMC cycle.

Using a proprietary granular database of a major Chinese stock exchange, we examine heterogenous investors’ trading dynamics around one of the most important macro announcements of the Chinese central bank, the monthly release of monetary aggregates data. Exploiting the trading heterogeneity across assets and across investor types, we find that before announcements, institutional investors reduce their aggregate stock exposure while over-weighing riskier stocks of smaller caps, whereas retail investors provide liquidity by increasing their aggregate stock exposure and avoiding the riskier stocks. Large retail and institutional investors become more informed before announcements and trade in correct directions consistent with the news surprises after announcements, while smaller retail investors trade in opposite directions. While the institutional investors accumulate positive returns with risk compensated, the market realizes sizable pre-announcement equity premium.

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.

Using a proprietary granular database of a major Chinese stock exchange, we examine heterogenous investors’ trading dynamics around one of the most important macro announcements of the Chinese central bank, the monthly release of monetary aggregates data. Exploiting the trading heterogeneity across assets and across investor types, we find that before announcements, institutional investors reduce their aggregate stock exposure while over-weighing riskier stocks of smaller caps, whereas retail investors provide liquidity by increasing their aggregate stock exposure and avoiding the riskier stocks. Large retail and institutional investors become more informed before announcements and trade in correct directions consistent with the news surprises after announcements, while smaller retail investors trade in opposite directions. While the institutional investors accumulate positive returns with risk compensated, the market realizes sizable pre-announcement equity premium.

Using a proprietary database of stock transactions in China, we document significant trading disparities between retail and institutional investors around important macro announcements. These disparities are driven by differences in information positions. We find that before the monthly releases of China’s key monetary aggregates data, institutional investors reduce their stock exposure and shift towards riskier, smaller-cap stocks. In contrast, retail investors increase their stock exposure and avoid riskier stocks. The risk positions of institutional investors are compensated by the pre-announcement premium in smaller stocks. Following the announcements, institutional investors trade in line with news surprises, contributing to price discovery and reinforcing monetary policy transmission into asset prices. Our findings have implications for understanding announcement-related equity premium and for evaluating the general efficiency of stock market in China.

We examine the interest rate pass-through in Hong Kong (HK) and Macao to see if the monetary policy transmission mechanism has been impaired since the Global Financial Crisis (GFC). Our results show that, in the post-GFC period, both the long-run and short-run interest rate pass-through from policy rates to prime rates have disappeared in Macao and weakened significantly in HK. The long-term relationship between deposit rates and policy rates no longer exists in either market while the short-term relationship has been reduced significantly. The results indicate that the effectiveness of the monetary policy in HK and Macao has been seriously undermined after the GFC and alternative monetary policy tools were needed.

There is mixed evidence of a positive relationship between the stock market risk and return. We reexamine this critical implication of asset pricing theory using fresh data from China's stock market, which is largely segmented from the rest of the global financial market. Using formal variable selection methods and a comprehensive set of predictor variables, we identify conditional market variance, scaled market prices, and inflation as crucial determinants of equity premiums. The estimated simple risk-return relationship exhibits downward omitted variable bias, which underlines the importance of considering multiple factors to explain the variation in equity premiums. We cannot wholly attribute the three-factor conditional equity premium model to data mining, as Guo, Sanni, and Yu (2022) select the same model for the U.S. stock market. These findings challenge existing asset pricing models and provide valuable guidance for future theoretical research.

Secular declines in global sovereign yields are concentrated in short event windows around U.S. monetary policy announcement dates. Cumulative changes in sovereign yields during FOMC announcement dates contain critical information for explaining the persistent variations in the yields, predicting future yields and excess bond returns, and determining interest rate expectations and term premia. We build a dynamic term structure model with shifting endpoints to study the effects of U.S. monetary policy on world yield curves. Our findings highlight that U.S. monetary policy drives the secular declines in global interest rates by reducing expected interest rates.