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Contribution Details
| Type | Master's Thesis |
| Scope | Discipline-based scholarship |
| Title | Does Intraday Technical Analysis Profitably Outperform a Buy-and-Hold Strategy? - Evidence from the Cryptocurrency Market |
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| Institution | University of Zurich |
| Faculty | Faculty of Business, Economics and Informatics |
| Number of Pages | 81 |
| Date | 2019 |
| Zusammenfassung | Cryptocurrencies propose a shift away from sovereign government-backed currencies and gained a lot of interest from the media and academia, given their innovative features and their use as an alternative investment vehicle. Given the lack of clear fundamentals, traders acting in cryptocurrency markets majorly use historical prices to predict future shifts in de-mand and supply. The practice of forecasting the future based on its past is widely applied across all asset classes and is known under the term “technical analysis”. Price prediction based on past asset values, however, contradicts the classical (weak) Efficient Market Hypothesis, which states that in efficient markets, past information is already embedded in the assets’ current prices. Consequently, using technical trading systems which rely on historical price in-formation should not be profitable. As of yet, no consens among practicioners and academics has been reached on the usefulness of technical analysis based trading systems. In general, technical trading systems’ performances vary across developed markets, rendering most of the systems unprofitable once transaction costs are taken into account. However, empricial evidence shows, that in young and emerging markets technical trading systems are profitable even after deducting transaction costs. The majority of research analyses the predicitve suc-cess of technical trading systems, using daily price observations and exogenously fixing the investment horizon to e.g, one or ten days. However, due to the increased speed in trading, financial professionals increasingly shift from trading daily to intradaily. Consequently, more weight is given to price sequences of higher frequences, increasing the popularity of technical trading systems applied to intraday prices. This thesis analyses the capability of popular methods, such as Moving Averages, Time Series Momentum and Relative Strength Indices to profitably outperforming a buy-and-hold strategy on the cryptocurrency market, using 13,527 hourly Bitcoin, Ethereum and Ripple price observations. Investment horizons are endogenously defined by the dynamic process of the technical trading systems, in which transactions are opened and closed according to the generated signals. Robustness in results is examined using an in- and out-of sample procedure while incorporating realistic transaction costs imposed by the Kraken exchange. The empirical analysis yields different results for different cryptocurrencies. Four out of 56 technical analysis based trading systems are profitable while offering cumulative net excess returns between 83%and 233% over the Bitcoin out-of-sample investment period from April, 9 2018 to January, 16 2019 when leverage is used. The profitably outperforming technical indicators are the P-SMA(150), P-SMA(200), P-EMA(100) and the P-EMA(150) specifications implemented by a levered long-short strategy. In addition, risk is reduced according to skewness and wealth losses are reduced as reported by the maximum drawdown measure. When applied to intraday Ethereum and Ripple prices, on the other hand, none of the tested trading systems are positively outperforming out-of-sample. These findings provide empirical evidence against weak intraday Bitcoin price efficiency, while presenting the usefulness of technical analysis to institutional investors when acting in the erratic intraday Bitcoin market. |
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