• Title/Summary/Keyword: Sortino ratio

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Technical Trading Rules for Bitcoin Futures (비트코인 선물의 기술적 거래 규칙)

  • Kim, Sun Woong
    • Journal of Convergence for Information Technology
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    • v.11 no.5
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    • pp.94-103
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    • 2021
  • This study aims to propose technical trading rules for Bitcoin futures and empirically analyze investment performance. Investment strategies include standard trading rules such as VMA, TRB, FR, MACD, RSI, BB, using Bitcoin futures daily data from December 18, 2017 to March 31, 2021. The trend-following rules showed higher investment performance than the comparative strategy B&H. Compared to KOSPI200 index futures, Bitcoin futures investment performance was higher. In particular, the investment performance has increased significantly in Sortino Ratio, which reflects downside risk. This study can find academic significance in that it is the first attempt to systematically analyze the investment performance of standard technical trading rules of Bitcoin futures. In future research, it is necessary to improve investment performance through the use of deep learning models or machine learning models to predict the price of Bitcoin futures.

An Empirical Study of the Trading Rules on the basis of Market Anomalies and Technical Analysis (시장이상현상과 기술적 분석을 이용한 거래전략에 관한 연구)

  • Ohk, Ki-Yool;Lee, Min-Kyu
    • Management & Information Systems Review
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    • v.37 no.1
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    • pp.41-53
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    • 2018
  • This study validates the trading rules based market anomalies and technical analysis in the Korean stock market. For the analysis, we built decile portfolios on the basis of corporate characteristics factors that clearly demonstrate specific patterns of stock returns including the firm size, book-to-market equity, and accruals. This portfolio was used to develop a portfolio based on the moving average trading strategy which was used for popular technical analysis tools, and then that was evaluated using the Sharpe ratio. We also created a zero-cost portfolio to identify the profitability and success rate of the moving average trading strategy. We lastly sought to ensure a more robust evaluation by calculating the Sortino ratio of the portfolio based on the moving average trading strategy with various lags. Key findings from this validation are as follows. First, a smaller firm size, a higher book-to-market equity, and lower accruals led to larger average returns. Second, the risk-adjusted performance of the moving average trading strategy was the highest in terms of the firm size, followed by book-to-market equity and accruals. Third, the returns of the zero-cost portfolios all had a positive value, with its overall success rate hovering over 68.8%, demonstrating the successfulness of the moving average trading strategy. Fourth, various evaluations revealed the economic usefulness of our trading strategy that used market anomalies and technical analysis.