Author(s)

Xiaoyu Su ¹, Jingyao Huang ¹

Affiliation(s)

¹ School of Economics, Jinan University, Guangzhou, Guangdong, 511443, China

Corresponding Author

Xiaoyu Su

ABSTRACT

Investors often pursue two objectives in the process of frequent trading of some assets with high price volatility: maximizing investment return and minimizing investment risk. In this paper, we use principal component analysis to capture the up and down signals that the market implies to investors from various aspects, while establishing a random forest model to realize the prediction of market prices, using the Sharpe ratio to compare the return with the risk, and finally getting the quantitative buying signal indicator; we also use the knowledge of statistics and finance to analyze the influencing factors of trading decisions. The study of this problem can provide investors with guiding advice to help them better gain returns and avoid risks.

KEYWORDS

Sharpe Ratio, Random Forest, Principal Component Analysis, Dynamic Programming

CITE THIS PAPER

Xiaoyu Su, Jingyao Huang, Strategies to Simulated Trading: Based on Sharpe Ratio and Random Forest. Information Systems and Economics (2022) Vol. 3: 35-41. DOI: http://dx.doi.org/10.23977/infse.2022.030207.

REFERENCES

[1] Nana Lin, Jiangtao Qin. Forecast of A-Share Stock Change Based on Random Forest [J]. Journal of University of Shanghai for Science and Technology, 2018, 40 (3): 267-273.
[2] Qixiang He, Yutong Ma. A Classification Study on Risk Premiums of Commodity Futures under Different Trading Strategies [J]. Journal of Industrial Engineering and Engineering Management, 2019, 33(3): 52-60.
[3] Haixiang Yao, Junwei Li, Shenghao Xia, Shumin Chen. Fuzzy Trading Decision Based on Apriori Algorithm and Neural Network [J]. Journal of Systems Science and Mathematical Sciences, 2021, 41(10): 2868-2891.
[4] Wenlan Huang. Research on Portfolio Optimization Based on Multi-objective Evolutionary Algorithm [D]. Harbin University of Commerce, 2020.

Sponsors, Associates, and Links

---

• Accounting, Auditing and Finance
  
  
• Industrial Engineering and Innovation Management
  
  
• Tourism Management and Technology Economy
  
  
• Journal of Computational and Financial Econometrics
  
  
• Financial Engineering and Risk Management
  
  
• Accounting and Corporate Management
  
  
• Social Security and Administration Management
  
  
• Population, Resources & Environmental Economics
  
  
• Statistics & Quantitative Economics
  
  
• Agricultural & Forestry Economics and Management
  
  
• Social Medicine and Health Management
  
  
• Land Resource Management
  
  
• Information, Library and Archival Science
  
  
• Journal of Human Resource Development
  
  
• Manufacturing and Service Operations Management
  
  
• Operational Research and Cybernetics