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The forward premium anomaly (exchange rate changes are negatively related to interest rate differentials) is one of the most robust puzzles in financial economics. We recast the underlying parity relation in terms of lagged forward interest rate differentials, documenting a reversal of the anomalous sign on the coefficient in the traditional specification. We show that this novel evidence is consistent with recent empirical models of exchange rates that imply exchange rate changes depend on two key variables: the interest rate differential and the magnitude of the deviation of the current exchange rate from that implied by purchasing power parity.

What moves stock prices? Prior literature concludes that the revelation of private information through trading, and not public news, is the primary driver. We revisit the question by using textual analysis to identify fundamental information in news. We find that this information accounts for 49.6% of overnight idiosyncratic volatility (vs. 12.4% during trading hours), with a considerable fraction due to days with multiple news types. We use our measure of public information arrival to reinvestigate two important contributions in the literature related to individual R² s of stock returns on aggregate factors.

The prevailing view in finance is that the evidence for long-horizon stock return predictability is significantly stronger than that for short horizons. We show that for persistent regressors, a characteristic of most of the predictive variables used in the literature, the estimators are almost perfectly correlated across horizons under the null hypothesis of no predictability. For the persistence levels of dividend yields, the analytical correlation is 99% between the 1- and 2-year horizon estimators and 94% between the 1- and 5-year horizons. Common sampling error across equations leads to ordinary least squares coefficient estimates and R²s that are roughly proportional to the horizon under the null hypothesis. This is the precise pattern found in the data. We perform joint tests across horizons for a variety of explanatory variables and provide an alternative view of the existing evidence.

We investigate the empirical implications of using various measures of payout yield rather than dividend yield for asset pricing models. We find statistically and economically significant predictability in the time series when payout (dividends plus repurchases) and net payout (dividends plus repurchases minus issuances) yields are used instead of the dividend yield. Similarly, we find that payout (net payout) yields contains information about the cross section of expected stock returns exceeding that of dividend yields, and that the high minus low payout yield portfolio is a priced factor.

This study explores optimal currency exposures in international equity portfolios through the lens of a modified mean-variance optimization framework. We decomposed the optimal currency portfolio into a \"hedge portfolio\" that uses a dynamic risk model to minimize equity volatility and an \"alpha-seeking portfolio\" based on the well-documented currency styles of value, momentum, fundamental momentum, and carry. This method is an integrated and economically intuitive approach to currency management that simultaneously provides lower risk and higher returns than either hedged or unhedged benchmarks. Crucially, the solution is practical, with realistic and implementable leverage, turnover, and tail-risk characteristics. Disclaimer: AQR Capital Management is a global investment management firm that may or may not apply similar investment techniques or methods of analysis as described herein. The views expressed here are those of the authors and not necessarily those of AQR. Editor's note Submitted 3 October 2018 Accepted 20 May 2019 by Stephen J. Brown. This article was externally reviewed using our double-blind peer-review process. When the article was accepted for publication, the authors thanked the reviewers in their acknowledgments. David Gallagher was one of the reviewers for this article.

Long-horizon return regressions effectively have small sample sizes. Using overlapping long-horizon returns provides only marginal benefit. Adjustments for overlapping observations have greatly overstated t-statistics. The evidence from regressions at multiple horizons is often misinterpreted. As a result, much less statistical evidence of long-horizon return predictability exists than is implied by research, which casts doubt on claims about forecasts based on stock market valuations and factor timing. Disclosure: AQR Capital Management is a global investment management firm that may or may not apply investment techniques or methods of analysis similar to those described herein. The views expressed here are those of the authors and not necessarily those of AQR. Editor's Note Submitted 2 April 2018 Accepted 1 August 2018 by Stephen J. Brown

This article provides an analytical solution to the problem of an institution optimally managing the market risk of a given exposure by minimizing its Value-at-Risk using options. The optimal hedge consists of a position in a single option whose strike price is independent of the level of expense the institution is willing to incur for its hedging program. This optimal strike price depends on the distribution of the asset exposure, the horizon of the hedge, and the level of protection desired by the institution. Moreover, the costs associated with a suboptimal choice of exercise price are economically significant.

We investigate the cross-sectional relation between industry-sorted stock returns and expected inflation, and we find that this relation is linked to cyclical movements in industry output. Stock returns of noncyclical industries tend to covary positively with expected inflation, while the reverse holds for cyclical industries. From a theoretical perspective, we describe a model that captures both (i) the cross-sectional variation in these relations across industries, and (ii) the negative and positive relation between stock returns and inflation at short and long horizons, respectively. The model is developed in an economic environment in which the spirit of the Fisher model is preserved.

The relation between stock returns and inflation at long horizons is examined. In approaching this issue, several problems arise which must be addressed. The first difficulty is the necessity for a long data sample in order to capture long-term movements in the time series of returns. To fulfill this requirement, 2 centuries of data on stocks, short-term and long-term bonds, and inflation in both the US and the UK are accumulated. The 2nd difficulty results from the inability to model ex ante long-term inflation accurately. The absence of any long-horizon inflation model is circumvented by using an instrumental-variable approach. Instruments are chosen that have theoretical support as measures of ex ante inflation. Using ex post inflation as a proxy for ex ante inflation rates, along with these instruments, consistent estimates are provided of the ex ante relation between stocks and inflation. In contrast to existing evidence at short horizons, evidence is found to suggest that long-horizon nominal stock returns are positively related to both ex ante and ex post long-term inflation.

We investigate the relation between returns on stock indices and their corresponding futures contracts to evaluate potential explanations for the pervasive yet anomalous evidence of positive, short-horizon portfolio autocorrelations. Using a simple theoretical framework, we generate empirical implications for both microstructure and partial adjustment models. The major findings are (i) return autocorrelations of indices are generally positive even though futures contracts have autocorrelations close to zero, and (ii) these autocorrelation differences are maintained under conditions favorable for spot-futures arbitrage and are most prevalent during low-volume periods. These results point toward microstructure-based explanations and away from explanations based on behavioral models.