Scott W. Barnhart, Andrew C. Szakmary, Testing the Unbiased Forward Rate Hypothesis: Evidence on Unit Roots, Co- Integration, and Stochastic Coefficients, The Journal of Financial and Quantitative Analysis, Vol. 26, No. 2 (Jun., 1991), pp. 245-267

This paper examines the performance of trend-following trading strategies in commodity futures markets using a monthly dataset spanning 48years and 28 markets. We find that all parameterizations of the dual moving average crossover and channel strategies that we implement yield positive mean excess returns net of transactions costs in at least 22 of the 28 markets. When we pool our results across markets, we show that all of the trading rules earn hugely significant positive returns that prevail over most subperiods of the data as well. These results are robust with respect to the set of commodities the trading rules are implemented with, distributional assumptions, data-mining adjustments and transactions costs, and help resolve divergent evidence in the extant literature regarding the performance of momentum and pure trend-following strategies that is otherwise difficult to explain.

This paper extends previous research by considering three pricing factors for American Depository Receipts (ADRs): the price of the underlying shares in the local currency, the relevant exchange rate, and the US market index. Using both a vector autoregressive (VAR) model with a cointegration constraint and a seemingly-unrelated regression (SUR) approach, we examine the relative importance of, and the speed of adjustment of ADR prices to, these underlying factors. Our results show that while the price of the underlying shares is most important, the exchange rate and the US market also have an impact on ADR prices. While the bulk of the shocks to the pricing factors are reflected in the ADRs within the same calendar day, there are indications that the adjustments are not completed until the following day. Curiously, the ADRs appear to initially overreact to the US market index but underreact to changes in underlying share prices and exchange rates.

Unlike previous papers, which have focused on the timeliness ranks, we examine Value Line’s 3–5 year projections for stock returns, earnings, sales and related measures. We find that Value Line’s stock return and earnings forecasts exhibit large positive bias, although their sales predictions do not. For stock returns, Value Line’s projections lack predictive power; for other variables predictive power may exist to some degree. Our findings suggest the spectacular past performance of the timeliness indicator reflects either close alignment with other known anomalies or data mining, and that investors and researchers should use Value Line’s long-term projections with caution.