Ben R. Marshall

Can Commodity Futures be Profitably Traded with Quantitative Market Timing Strategies

Quantitative market timing strategies are not consistently profitable when applied to 15 major commodity futures series. We conduct the most comprehensive study of quantitative trading rules in this market setting to date. We consider over 7,000 rules, apply them to 15 major commodity futures contracts, employ two alternative bootstrapping methodologies, account for data snooping bias, and consider different time periods. While we cannot rule out the possibility that technical trading rules compliment some other trading strategy, we do conclusively show that they are not profitable when used in isolation, despite their wide following.

Liquidity and stock returns in pure order-driven markets: evidence from the Australian stock market

Abstract This paper examines the relationship between liquidity and stock returns in the pure order-driven stock market of Australia. The bid–ask spread, turnover rate, and amortized spread are used as proxies for liquidity. In addition to liquidity, other factors that have been found to influence stock returns, such as beta and size, are also considered. Seemingly unrelated regressions (SUR) and the cross-sectionally correlated timewise autoregressive (CSCTA) model form the methodological basis for this research. A small liquidity premium is found in the Australian market, which persists for the entire year. There is also strong evidence of a negative size effect.

Liquidity Commonality in Commodities

We examine liquidity commonality in commodity futures markets. Using data from 16 agricultural, energy, industrial metal, precious metal, and livestock commodities, we show there is a strong systematic liquidity factor in commodities. Liquidity commonality was present in 1997–2003 when commodity prices were relatively stable and during the recent boom. There is some support for both “supply-side” and “demand-side” explanations for this commonality. We find no evidence of a consistent link between stock and commodity liquidity in general. Energy commodities appear to provide a better hedge against equity market liquidity risk than the other commodity families.

Financial Distress Prediction in China

We use four alternative prediction models to examine the usefulness of financial ratios in predicting business failure in China. China has unique legislation regarding business failure so it is an interesting laboratory for such a study. Earnings Before Interest and Tax to Total Assets (EBITTA), Earning Per Share (EPS), Total Debt to Total Assets (TDTA), Price to Book (PB), and the Current Ratio (CR), are shown to be significant predictors. Prediction accuracy achieves a range from 78% to 93%. Logit and Neural Network models are shown to be the optimal prediction models.

Is technical analysis profitable on US stocks with certain size, liquidity or industry characteristics?

We consider whether popular moving average and trading range breakout technical trading rules are profitable on a subset of the US stocks with certain size, liquidity and industry characteristics. We find these rules are rarely profitable during the period 1990 to 2004, however there is some evidence that they are more profitable for smaller, less liquid stocks. There is no evidence to any industry bias in applying these rules and when a rule does produce statistically significant profits on a stock, these profits tend to be greater for longer decision period rules.

Liquidity Measurement in Frontier Markets

Frontier markets which are countries that have not yet reached emerging market status, have been shown to provide diversification benefits for international investors. However, many stocks in these markets are thinly traded so liquidity is an important consideration. We investigate which liquidity proxies best measure the actual cost of trading in 19 frontier markets that can be accessed by foreign investors. We find the Gibbs, Amihud, and Amivest proxies have the largest correlation with liquidity benchmarks, while the FHT measure provides the best measure of the magnitude of actual transaction costs.

Frontier market transaction costs and diversification

Frontier markets, sometimes referred to as “emerging emerging markets,” have high transaction costs so investors who rebalance their portfolios monthly do not receive diversification benefits. Rebalancing every three months or longer, however, leads to diversification gains. Diversification benefits are larger in time periods with lower transaction costs and this is linked to risk aversion. Higher risk aversion results in larger transaction costs and larger return correlations between the United States and frontier markets. There is no cross-country relation between diversification benefits and transaction costs or development. Our results are based on comprehensive measures of transaction costs for 19 frontier markets.

The announcement and implementation reaction to China's margin trading and short selling pilot programme

Purpose - – The purpose of this paper is to investigate how the announcement and implementation of short sales and margin trading regulation affects Chinese stock returns and trading volume. On 31 March 2010, the Chinese regulators launched a pilot programme, allowing short sales and margin trading for 50 Shanghai Stock Exchange and 40 Shenzhen Stock Exchange stocks. Design/methodology/approach - – This paper uses an event study approach to compare market model abnormal returns (ARs) of the pilot firms with two distinct matched firm samples. A volume event study is also conducted to examine abnormal trading activity surrounding the key events in the pilot stocks. Findings - – Negative ARs follow both the announcement and implementation of short selling and margin trading. This suggests the negative impact of short sales dominates the positive impact of margin trading on an average. Volume also declines, which is consistent with uninformed investors’ seeking to avoid trading against informed traders. Originality/value - – The paper appears to be the first to address the impact of both the announcement and implementation of short selling and margin trading rule changes on returns and liquidity using individual stock data.

Return Predictability Revisited

Monthly stock market returns are predictable when we refine the observation intervals of the variables used to predict these returns. Contrary to other predictability studies we find high out-of-sample adjusted R2s of up to 7% using economically important commodity returns. Shorter intervals reveal predictability consistent with near efficient markets based on price changes in industrial metals. More historical intervals expose predictability consistent with gradual information diffusion based on energy series. This predictability is robust to data mining adjustment, the inclusion of control (including economic) variables, and unrelated to time-varying risk. Inflation explains part of this predictability, but not all.

Time series momentum and moving average trading rules

We compare and contrast time series momentum (TSMOM) and moving average (MA) trading rules so as to better understand the sources of their profitability. These rules are closely related; however, there are important differences. TSMOM signals occur at points that coincide with a MA direction change, whereas MA buy (sell) signals only require price to move above (below) a MA. Our empirical results show MA rules frequently give earlier signals leading to meaningful return gains. Both rules perform best outside of large stock series which may explain the puzzle of their popularity with investors, yet lack of supportive evidence in academic studies.