Technical analysis is widely spread in practice and can be defined as the study of asset prices and volumes with the intention of forecasting future trends. Followers and adaptors of technical analysis apply indicators based on mathematical principles to identify regularities by extracting non-linear patterns from noisy data. A variety of different indicators exist but the concepts used mostly are moving averages. However, technical analysis still is anathema to the academic world as it challenges the veracity of the efficient market hypothesis directly. The current paper implements the concept of moving average strategies to portfolios sorted by volatility portfolios, attempting to outperform a buy-and-hold strategy. Using stocks from the Swiss Performance Index, the investment timing portfolios show some ability to outperform the underlying benchmark but lack to do so in every case. Abnormal returns, relative to the CAPM, the FAMA-FRENCH three-factor and the CARHART four-factor models, demonstrate statistical and economic significance even though the alphas are lower than the returns from corresponding buy-and-hold portfolios. To check the received results, a variety of robustness tests are conducted. The results show that an anomaly in the cross-section of returns can neither be confirmed nor neglected but that the implementation of technical analysis can be potentially profitable under certain circumstances and assumptions.Technical analysis is widely spread in practice and can be defined as the study of asset prices and volumes with the intention of forecasting future trends.
|Title||:||On the Cross-Sectional Profitability of Technical Analysis|
|Author||:||Stephan Schafroth, David Oesch|