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Bond peer momentum (PM), the average return of economically linked bonds, strongly predicts one-month-ahead excess returns. Across firm linkages, the shared-analyst network is most informative and subsumes alternative PMs. A long–short strategy based on this signal earns 0.45% per month, with alphas unexplained by standard bond and stock factor models and robust across samples, characteristics, and return measures. The predictability is concentrated among co-held bonds and is stronger when trading frictions are high, supporting a flow-based limits-to-arbitrage channel rather than limited attention. Compared with stocks, bond PM delivers comparable Sharpe ratios, lower crash risk, and shorter persistence.

We find strong evidence of peer momentum in delta-hedged option returns. Our main peer momentum measure, in which firms are linked if they share common sell-side analysts, is highly profitable, with a pre-cost Sharpe ratio of 3. It is distinct from standard momentum, and there is little impact from controlling for standard momentum or other well-know option return predictors. It is robust to the length of the formation periods, the method of return computation, and realistic assumptions about transactions costs. Alternative methods for linking peer firms usually result in weaker performance, though it in most cases remains highly significant. We show that peer momentum is consistent with underreaction of implied volatilities to volatility shocks of peer firms. Using several different approaches, we also show that factor momentum only partially explains peer momentum, and vice versa. Our final results demonstrate the new finding of peer reversal, which is present in a smaller number of firm pairs but is nevertheless highly significant.

This paper documents a strong media coverage effect in the options market. Firms receiving higher media coverage earn significantly lower straddle returns in the subsequent month, which remains unexplained by existing option return predictors. We provide evidence for a volatility overreaction channel in the options market: while realized variance spikes during periods of intense media coverage and mean-reverts thereafter, implied variance fails to fully anticipate this decline. Consequently, implied variance substantially exceeds future realized variance during high-coverage periods, leading to overpriced straddles and predictably lower future returns. Alternative explanations, including investor recognition, investor attention, earnings announcement, and abnormal realized variance, fail to explain the media coverage effect. Furthermore, this effect is primarily concentrated in news regarding five key topics: earnings, revenues, equity actions, mergers and acquisitions, and stock prices.

We estimate the short-term discount rate from the options written on the S&P 500 index via the put-call parity. This estimated discount rate predicts average stock returns significantly both in-sample and out-of-sample. Cross-sectionally, stocks with higher exposure to the short discount rate earn higher average returns; they significantly outperform the low exposure stocks by 0.49% (0.72%) per month under equal (value) weights. Using the demand system approach, we find that long-term investors tend to hold stocks with low (negative) exposure to the short discount rate. In contrast, short-term investors outweigh this risk relative to the household and mid-term investors.

This paper introduces a new approach to infer the individual stock return during market crashes from the options market, which relies on the correlation between the VIX and the prices of butterflies at different strikes. Applying it to the cross-section of S&P 500 stocks yields a strategy that hedges the market downturn while earning an annualized alpha of approximately 4%. The value-weighted aggregation produces a measure for the severity of market crashes, which is shown to be an important determinant of both the equity risk premium and the survey-based expectation of return.

Using contemporaneous beta approach, we try to explore the prediction performance of variance risk premium (VRP) and skewness risk premium (SRP) for Chinese stock market return. In response to the shortcoming of Pyun (2019)'s model and its poor performance in China, we incorporate skewness risk to variance risk and derive a model to theoretically link expected market return with VRP and SRP. Empirical results show that under the framework of contemporaneous beta approach, incorporating both variance and skewness risk can greatly improve the prediction performance on market return, compared with incorporating only one of them.

This paper proposes the concept of bull market risk, i.e., the time variation in the probability of a future bull market state, and explores whether it is priced. Since a bull spread option portfolio reflects investors' ex-ante expectations about future bull market risk-neutral probability, its short-term return is used to measure bull market risk. This measurement, which belongs to the implied information method, aligns more closely with the ex-ante attributes of risk and can avoid the Peso problem by using historical data. Based on China's stock and option market data, the paper finds that bull market risk cannot be explained by traditional factor models. What's more, an individual stock's exposure to bull market risk, which is defined as bull beta, has a significantly robustly positive relation with its future return, indicating that bull market risk is priced in the cross-section.