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Portfolio Optimization Considering Diversified Investment Methods Using GNQTS and Trend Ratio

In the stock selection problem, the Sharpe ratio is one of the commonly used indicators, but it tends to identify the portfolio with a flat trend as the best one. This paper uses the trend ratio to access the portfolio with a stable upward trend. By the portfolio trend line with initial funds, the trend ratio can simultaneously consider the daily expected return, daily risk and fairly compare with the different portfolios and different investment periods lengths. In addition to the access indicator, this paper provides diversified investments such as time deposit, buying round lots or buying odd lots. Different situation suits different investment method. Therefore, this paper applies the 2-phase investment sliding windows to avoid the overfitting problem and chooses the best investment method by multiple training using Global-best Guided Quantum-inspired Tabu Search with Not Gate (GNQTS) to find the best portfolio effectively and efficiently. Furthermore, the experimental results show that the proposed method can find the well-performing portfolio with higher return and lower risk in both the training and testing periods.