Knowledge that Transforms

In this work, we study statistical arbitrage strategies in international crude oil futures markets. We analyse strategies that extend classical pairs trading strategies, considering the two benchmark crude oil futures (Brent and WTI) together with the newly introduced Shanghai crude oil futures. We document that the time series of these three futures prices are cointegrated and we model the resulting cointegration spread by a mean-reverting regime-switching process modulated by a hidden Markov chain. By relying on our stochastic model and applying online filter-based parameter estimators, we implement and test a number of statistical arbitrage strategies. Our analysis reveals that statistical arbitrage strategies involving the Shanghai crude oil futures are profitable even under conservative levels of transaction costs and over different time periods. On the contrary, statistical arbitrage strategies involving the three traditional crude oil futures (Brent, WTI, Dubai) do not yield profitable investment opportunities. Our findings suggest that the Shanghai futures, which has already become the benchmark for the Chinese domestic crude oil market, can be a valuable asset for international investors.

Our study evaluates the return sensitivity of cryptocurrencies to various measures of uncertainty (uncertainty beta). We identify that crypto returns react primarily to financial uncertainty, which is the unforecastable component of multiple financial indicators. However, crypto returns are not sensitive to other forms of uncertainty such as macro, real, or policy uncertainty, as well as VIX, and inflation. The portfolio analysis yields a significant financial uncertainty premium of around 21% per month, which is driven by the outperformance (underperformance) of cryptocurrencies with a negative (positive) uncertainty beta. The portfolio returns are more potent in coins with speculative, rather than transactional, features such as proof-of-work, non-token, and mineable. Our findings suggest that large investors exhibit a willingness to pay higher premiums for cryptocurrencies with positive uncertainty betas, as these assets can be used as a hedging tool within a larger financial portfolio.

We evaluate the relation between 133 anomalies/factors and market states using a sample of 57 countries from 1980 to 2019. The vast majority (96 of 133; 50 significant at the 5% level) performs better in bad times; 9 anomalies perform significantly better in good times, including market, size, value, and momentum. The value-weighted four-factor alpha amounts to 47.7 (31.8) bps in bad (good) times. 92.9% of the performance gain in bad times is driven by the anomaly short side. Findings are robust to controlling for sentiment or recession indicators and highlight the importance of mispricing in explaining anomaly returns.

Conventionally, it is very difficult to differentiate factor risk premium from mispricing. Motivated by the fact that short-sellers take advantage of observable mispricing, this paper highlights the different effects of short selling activity on the profitability and investment premia. We find that the profitability premium disappears among the stocks with high short selling activity whereas short selling has no impact on the investment premium. We also show that the profitability premium is more likely than the investment premium to be associated with the sentiment-driven mispricing, which is eliminated among heavily shorted stocks. Collectively, our results suggest that the two new premia have different underlying attributions. While the profitability premium is more consistent with the mispricing interpretation, the investment premium is not.

This paper develops and tests an equilibrium model of active fund management with ESG considerations. Heterogeneous sustainability preferences lead fund managers to intensify information acquisition on assets across the ESG spectrum, broadening the scope of active management. This information channel enhances price informativeness, lowers discount rates, and increases portfolio deviation from benchmarks. The model predicts a negative and concave ESG-expected return relation, stronger for green assets and weaker for brown assets. Using data on U.S. mutual funds and stocks from 2007–2021, we find supporting evidence based on price informativeness and the implied cost of equity capital.

Our primary contribution to the finance literature is the introduction of folklore narratives as a major factor in influencing corporate outcomes. Using the initial public offering (IPO) underpricing as the main focus, we demonstrate that folklore narratives depicting lower tolerance toward antisocial behavior are associated with lower IPO underpricing. The relation between folklore narratives and IPO pricing is independent of indicators of trust, religion, culture, societal preferences, or institutional democracy. This relation is weaker in countries with a more transparent information environment and following reforms that improve disclosure and corporate governance. Folklore narratives on punishment for antisocial behavior are also related to enhanced information disclosure, lower agency problems, better long-term performance for IPO firms, higher proceeds raised and free float, and overall IPO activity in the market. Collectively, we show that informal institutions, such as folklore narratives, exert a strong influence on IPO outcomes globally.