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Information Journal Paper

Title

Automatic Portfolio Rebalancing System Design Using Volatility Prediction Models and Technical Analysis Combination

Pages

  145-164

Abstract

 The management of financial portfolios or funds constitutes a widely known problematic in financial markets which normally requires a rigorous analysis in order to select the most profitable assets. In this field designing profitable automated trading systems, which could trade dynamically and make appropriate decisions is significantly important. Technical analysis is a popular method to predict future price movement. One of the deficiencies of Technical analysis is the lack of attention to risk of investing and portfolio management. This study has developed Automated Portfolio Management systems using Technical analysis indicators to find uptrend price movements and used GARCH and FIGHARCH models to consider the risk in the decisions. The developed model has assayed in one year time scope. The results illustrate that using FIGARCH models has made superior return to risk ratio. Also the ratio shows that the developed models are significantly better, comparing the other investing methods such as Markowitz model and buy and hold strategy.

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  • Cite

    APA: Copy

    Vakili, Seyyed Hojjat, Emadi, Seyyed Morteza, & Ebrahimi, seyyed Babak. (2019). Automatic Portfolio Rebalancing System Design Using Volatility Prediction Models and Technical Analysis Combination. JOURNAL OF FINANCIAL MANAGEMENT STRATEGY, 7(1 (24) ), 145-164. SID. https://sid.ir/paper/261673/en

    Vancouver: Copy

    Vakili Seyyed Hojjat, Emadi Seyyed Morteza, Ebrahimi seyyed Babak. Automatic Portfolio Rebalancing System Design Using Volatility Prediction Models and Technical Analysis Combination. JOURNAL OF FINANCIAL MANAGEMENT STRATEGY[Internet]. 2019;7(1 (24) ):145-164. Available from: https://sid.ir/paper/261673/en

    IEEE: Copy

    Seyyed Hojjat Vakili, Seyyed Morteza Emadi, and seyyed Babak Ebrahimi, “Automatic Portfolio Rebalancing System Design Using Volatility Prediction Models and Technical Analysis Combination,” JOURNAL OF FINANCIAL MANAGEMENT STRATEGY, vol. 7, no. 1 (24) , pp. 145–164, 2019, [Online]. Available: https://sid.ir/paper/261673/en

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