Asset Allocation and Private Market Investing

Shen, Junying; Li, Ding; Qiu, Grace; Jeet, Vishv; Teng, Michelle; Wong, Ki Cheong

doi:10.3905/jpm.2021.1.211

Cited by 9 publications

(1 citation statement)

References 11 publications

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“…By far, economists and other professionals did diversified investigations derived from the portfolio construction process. For instance, Shen [4] did the portfolio construction for the private market; the Russell company [5] focused on the assets allocation of the Emerging Market (EM) fixed income asset class, and Chattopadhyay [6] did the portfolio construction based on art and science-related assets. However, apart from these papers, the research combining the portfolio construction process with extra aspects, such as the financial indicators of assets and the time series prediction with back tests of the portfolio return, is relatively rare.…”

Section: Introductionmentioning

confidence: 99%

Portfolio Construction Based on Financial Indicators

Qiao¹,

Yuan²,

Wang³

2023

Proceedings of the 4th International Conference on Economic Management and Model Engineering, ICEMME 2022, November 18-20, 2022

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This paper focuses on the portfolio construction that determines the assets arranged in the portfolio based on some relatively novel and unique financial indicators. After that, the Monte Carlo simulation is used to find the efficient frontier and the allocation distribution of each asset. Subsequently, the ARIMA model is used to predict the overall trend of the price performance of the portfolio. Finally, there is a back test of the newly established asset portfolio to check the performance of our portfolio. In this paper, the historical data of 20 chosen blue-chip stocks is extracted from NYSE and NASDAQ. Each stock is assigned with an appropriate weight to achieve a smoother and more stable price trend by modeling. In the prediction section, there is a reasonable time prediction of the portfolio. The final back test also showed that the portfolio performs better than average market performance. In addition, the maximum sharp ratio proves that the research of this paper has made achievements on receiving extra returns under relatively stable risk and volatility. Altogether, the findings in this paper benefit certain investors in the related markets. It offers a brand-new quantitative investing strategy, which selects stocks scientifically and weighing them properly, decreasing the risk and receiving an acceptable return.

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Section: Introductionmentioning

confidence: 99%