Market Efficiency of Euro Exchange Rates and Trading Strategies

This paper tests the hypothesis on market efficiency for returns on the euro against fifteen currencies while assuming predictability of returns, dependent on the sign and magnitude of endogenous shocks. Considering the properties of exchange rate returns, the quantile autoregression approach was selected in empirical analysis. Based on the research data sample, consisting of daily exchange rates between January first, 1999, and April thirty, 2020, the paper suggests profitable trading strategies depending on a currency pair. In the case of six out of fifteen currency pairs, exchange rate returns were found non-predictable or almost non-predictable. In the case of nine considered currency pairs, there was a significant linkage between current and past exchange rate returns, found as dependent on the sign and magnitude of endogenous shocks in exchange rate returns. Finally, the paper considered possible factors of inefficiency and suggested further research of the topic.

Long Run Returns Predictability and Volatility with Moving Averages

This paper examines how the size of the rolling window, and the frequency used in moving average (MA) trading strategies, affects financial performance when risk is measured. We use the MA rule for market timing, that is, for when to buy stocks and when to shift to the risk-free rate. The important issue regarding the predictability of returns is assessed. It is found that performance improves, on average, when the rolling window is expanded and the data frequency is low. However, when the size of the rolling window reaches three years, the frequency loses its significance and all frequencies considered produce similar financial performance. Therefore, the results support stock returns predictability in the long run. The procedure takes account of the issues of variable persistence as we use only returns in the analysis. Therefore, we use the performance of MA rules as an instrument for testing returns predictability in financial stock markets.

Time-Varying Return Predictability in the Chinese Stock Market

China’s stock market is the largest emerging market in the world. It is widely accepted that the Chinese stock market is far from efficiency and it possesses possible linear and nonlinear dependencies. We study the predictability of returns in the Chinese stock market by employing the wild bootstrap automatic variance ratio test and the generalized spectral test. We find that the return predictability vary over time and a significant return predictability is observed around market turmoils. Our findings are consistent with the Adaptive Markets Hypothesis (AMH) and have practical implications for market participants and policy makers. A predictability index can be constructed for each asset, which might help warn a crisis is in store, ease the development of the ongoing bubble, and stabilize the market.

Predicting Fama-French factors based on industry returns in Brazil

There is a vast literature on the predictability of returns based on past information, and many asset pricing models have been tested, such as the Capital Asset Price Model (CAPM) and the three-factor asset pricing model of Fama and French. The purpose of this paper is to answer the question whether Fama-French’s size and value factors (SMB and HML) can be predicted by past returns of 16 portfolios formed by companies from the same industry in Brazil. Our analysis controls for different macroeconomic variables and firm characteristics, such as corporate governance practices, size, dividend yield, book-to-market, among others. The analysis reveals that 14 of 16 industries predict SMB one month ahead. Furthermore, the returns of a few industries predict the volatility of SMB and HML up to three months ahead of time. Considering the explanatory capability of the Fama-French model, the results of this research show that Brazilian industry returns contain valuable information for the SMB and HML factors, demonstrating that investors cannot absorb all the information in a timely manner, resulting in their gradual diffusion throughout the market.

Asset pricing with flexible beliefs

We develop a present-value asset pricing model with an econometrically useful representation that accommodates a plethora of stylized assumptions about beliefs. Using 20th century S&P500 data we use our model to compare the empirical fit of belief assumptions associated with rational expectations, asymmetic information, learning, behavioral effects and evolution. Among these, asymmetric information with evolution is particularly useful both in terms of statistical criteria and in terms of ability to explain the equity premium, excess volatility and predictability of returns. Our work suggests that popular relaxations of rationality can easily lead to econometric representations that may be impossible to work with in empirical research. Furthermore, replication of stylized facts may be too weak a requirement when evaluating such models. Fortunately, there exist simple relaxations of rationality that are sufficient to drastically improve the empirical fit of models with full rationality.