Market expectation shifts in option-implied volatilities in the US and UK stock markets during the Brexit vote

This paper investigates the effect of the Brexit vote on the connection between UK stock market expectations and US stock market returns. To gauge UK stock market expectations, the option-implied volatilities of the FTSE 100 index are calculated in the period starting five months before and ending four months after the Brexit referendum. To keep the analysis “clean”, it stops right before the 2016 US presidential elections. It uses an OLS regression to estimate the change in the relationship between US and UK stock market expectations.The main findings show that the US and UK stock markets became somewhat less integrated four months after the Brexit referendum compared to the five months before it. The S&P 500 Index returns have a statistically significant impact on implied volatilities of the FTSE 100 only before the Brexit referendum. However, the British risk-free rate (LIBOR) became a statistically significant factor affecting FTSE 100 implied volatilities only after Brexit. This analysis may be used by decision-makers in the money management industry to act appropriately during Black Swan events. When UK citizens unexpectedly voted in favor of Brexit, the risk-free rate dropped, making it cheaper to invest, increasing the Sharpe ratios of equity portfolios. Coupled with increased uncertainty, this caused portfolio reallocations. In turn, expected volatility measured by options-implied volatility increased. AcknowledgmentThe authors would like to thank Olesia Verchenko for critique, a KSE M.A., external defense reviewer for helpful comments.

Rationalizing forecast inefficiency

We show analysts’ own earnings forecasts predict error in their own forecasts of earnings at other horizons, which we argue provides a measure of the extent to which analysts inefficiently use information. We construct our measure by exploiting two sources of variation in analysts’ incentives: (i) more recent forecasts have greater salience at the time of the earnings release so accuracy incentives are higher (lower) at shorter (longer) forecast horizons and (ii) analysts have greater incentives for optimism (pessimism) at longer (shorter) horizons. Consistent with these incentives affecting the incorporation of information into forecasts, we document (i) current year forecasts underweight (overweight) information in shorter (longer) horizon forecasts and (ii) the mis-weighting is more pronounced when recent news is negative—when analysts have greater (weaker) incentives to incorporate the news into shorter (longer) horizon forecasts. Finally, returns tests suggest that forecasts adjusted for the inefficiency we document better represent market expectations of earnings.

Promoting Platform Takeoff and Self-Fulfilling Expectations: Field Experimental Evidence

A platform might have the potential to bring enormous value to its users. However, without a well-orchestrated launch strategy that coordinates a sufficient number of users onto the platform, this potential will not be realized. The theoretical literature predicts that one approach to coordinating platform take-off is to influence the market’s subjective focal expectations of the future installed base of users. This paper reports on a field experiment investigating the causal role of subjective expectations in the launch of a new platform venture, in which invitations to join a newly launched platform were sent to 16,349 individuals. The invitations included randomized statements regarding the size of the future expected installed base (along with disclosures of the current installed base). I find that simple, subjective, uncommitted, and relatively costless statements broadcasted by the platform with the goal of influencing market expectations were indeed able to influence platform takeoff and overcome an initial chicken-and-egg problem. These broadcasted subjective statements regarding future installed base had a larger influence on adoption rates than did disclosures of the true current installed base during early adoption. However, these subjective statements of expected future installed base ceased to have any effect once the true current installed base grew large. I discuss implication for the promotion, marketing, and evangelism of new platform ventures. This paper was accepted by Duncan Simester, marketing.

Ownership, Learning, and Beliefs

We examine how owning a good affects learning and beliefs about its quality. We show that people have more extreme reactions to information about a good that they own compared to the same information about a nonowned good: ownership causes more optimistic beliefs after receiving a positive signal and more pessimistic beliefs after receiving a negative signal. Comparing learning to normative benchmarks reveals that people overextrapolate from signals about goods that they own, which leads to an overreaction to information; in contrast, learning is close to Bayesian for nonowned goods. We provide direct evidence that this effect is driven by ownership channeling greater attention towards associated information, which leads people to overweight recent signals when forming beliefs. The relationship between ownership and beliefs has testable implications for trade and market expectations. In line with these predictions, we show that the endowment effect doubles in response to positive information and disappears with negative information, and demonstrate a significant relationship between ownership and overextrapolation in survey data about stock market expectations.