Optimal selection of financial risk investment portfolio based on random matrix method

Tian, Jie; Zhao, Kun

doi:10.3233/jcm-194028

Cited by 9 publications

(6 citation statements)

References 17 publications

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“…When focusing on noise, a common assumption in practice is that the mean of noise is 0, i.e., (Donoho and Johnstone, 1994 ). In this case, the optimal portfolio weight under noisy environment is It is clear that noise affects portfolio performance only through the covariance matrix, which confirms the validity of previous studies to filter the covariance matrix (Daly et al, 2008 ; Tian and Zhao, 2020 ). However, when the assumption is not satisfied, only filtering the covariance matrix is not sufficient.…”

Section: Portfolio Theory Under Noisy Environmentsupporting

confidence: 82%

Portfolio Selection Based on EMD Denoising with Correlation Coefficient Test Criterion

Yao

Zheng

et al. 2022

Comput Econ

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Noise is an important factor affecting portfolio performance, how to construct an effective denoising strategy is becoming increasingly important for investors. In this study, we theoretically explain the impact of noise on portfolio and argue the necessity of denoising. Next, the empirical mode decomposition (EMD) denoising strategy based on the correlation coefficient test criterion is proposed to improve portfolio performance. In detail, EMD is used to decompose the noisy price, then, a series of correlation coefficient tests are performed to determine which intrinsic mode functions (IMFs) are noise. In the empirical analysis, we apply the proposed method to denoise the SSE 50 index’s constituents, and further test the out-of-sample performance under the mean–variance framework. The empirical results show that the proposed denoising method outperforms four common EMD, Ensemble EMD (EEMD) and wavelet denoising methods in return-risk ratio. The proposed method is the optimal denoising strategy, which can help investors improve portfolio performance to the greatest extent.

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Section: Portfolio Theory Under Noisy Environmentsupporting

confidence: 82%

Portfolio Selection Based on EMD Denoising with Correlation Coefficient Test Criterion

Yao

Zheng

et al. 2022

Comput Econ

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“…In order to separate the non-noise information in the fnancial correlation matrix, random matrix theoretical denoising methods such as the LCPB denoising method, PG + denoising method, and KR denoising method have been proposed [27][28][29][30].…”

Section: Complexitymentioning

confidence: 99%

Research on Chinese Stock Market during COVID-19—Based on Random Matrix Theory

Fang

2023

Complexity

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This paper focuses on the three industries that are greatly impacted by COVID-19, including the consumption industry, the pharmaceutical industry, and the financial industry. The daily returns of 98 stocks in the consumption industry, the pharmaceutical industry, and the financial industry in the 100 trading days from January 2, 2020, to June 3, 2020, are selected. Based on the random matrix theory, it first analyzes whether the stock market conforms to the efficient market hypothesis during the epidemic period, and second it further studies the linkage between the three industries. The results show that (1) the correlation coefficient is approximately a normal distribution, but the mean value is greater than 0, which is greater than that of the more mature markets such as the United States. (2) There are three eigenvalues greater than the prediction value, of which the maximum eigenvalue is about 11.18 times larger than the largest eigenvalue of the RMT. (3) There is a significant positive relationship between the maximum eigenvalue and the correlation coefficient. The specific market performance is that the stock price fluctuations show a high degree of consistency. (4) In the sample interval, the financial industry has a restraining effect on the consumption industry in the short term, and the pharmaceutical industry has a promoting and then restraining effect on the consumption industry in the short term. The consumption industry has a promoting effect on the financial industry in the short term, and the pharmaceutical industry has a promoting and then restraining effect on the financial industry in the short term. The consumption industry has a promoting and then restraining effect on the pharmaceutical industry in the short term, and the financial industry has a promoting and then restraining effect on the pharmaceutical industry in the short term. (5) In the sample interval, the consumption industry is mainly affected by itself, while the role of the pharmaceutical industry and the financial industry is very small. The pharmaceutical industry is mainly affected by itself and the consumption industry, while the role of the financial industry is very small. The financial industry is mainly affected by itself and the consumption industry, while the role of the pharmaceutical industry is very small. This situation has consequences for individual investors and institutional investors, since some stock returns can be expected, creating opportunities for arbitrage and for abnormal returns, contrary to the assumptions of random walk and information efficiency. The research on the correlation between asset returns will help to accurately price assets and avoid losses caused by price fluctuations during the epidemic.

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“…Relevant scholars believe that the innovation and entrepreneurship education ecosystem has the characteristics of openness, complexity, and dynamic balance [16]. Researchers believe that an entrepreneurship education ecosystem with spontaneous coupling, collaborative interconnection, and endogenous growth between different entities must be formed in the future [17].…”

Section: Related Workmentioning

confidence: 99%

Random Matrix Model for the Ecological Model of Innovation and Entrepreneurship Education for College Students

Yang

2022

Mathematical Problems in Engineering

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The introduction of the ecological perspective into the research of entrepreneurship education is an important transformation of the way of thinking. Using the thinking forms such as integrity, diversity, and openness, it analyzes the ecological role relationship of the various elements of entrepreneurship education itself, and the relationship between the entrepreneurship education system and the external social ecology. The relationship between the system and the influence of various elements on the effect of entrepreneurship education is clarified to ensure that entrepreneurship education achieves practical results. From the perspective of ecology, based on the research on entrepreneurship education in colleges and universities, on the basis of ecological cognition of entrepreneurship education, this research attempts to solve many problems in the current implementation of entrepreneurship education in colleges and universities through the theoretical construction of an ideal college entrepreneurship education ecosystem. The problem of ecological imbalance can better serve the practice of entrepreneurship education in colleges and universities. At the same time, theoretically expand the horizons of entrepreneurship education research in colleges and universities, and further promote the “conditional” integration of ecological thinking and entrepreneurship education. This paper introduces the random matrix theory and introduces the related theory of Monte Carlo method. The weight assignment of the evaluation index system is realized, which lays the foundation for the quantitative evaluation. The weight coefficients of the indicators at all levels are determined by the analytic hierarchy process, and the importance of the indicators is judged by the weight coefficients, so as to realize the scientific quantitative evaluation of the innovation and entrepreneurship education ecosystem. At the same time, the scientificity of the evaluation index system is verified by means of the method of reliability and validity test. The conclusions of this study theoretically solve the main problems existing in the evaluation of the current innovation and entrepreneurship education ecosystem. By building a complete evaluation index system for the innovation and entrepreneurship education ecosystem in colleges and universities, it helps researchers and users to clarify the connotation and elements of the innovation and entrepreneurship education ecosystem in colleges and universities, and fully taps the “hidden” elements of evaluation indicators, making the evaluation more comprehensive.

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Optimal selection of financial risk investment portfolio based on random matrix method

Cited by 9 publications

References 17 publications

Portfolio Selection Based on EMD Denoising with Correlation Coefficient Test Criterion

Portfolio Selection Based on EMD Denoising with Correlation Coefficient Test Criterion

Research on Chinese Stock Market during COVID-19—Based on Random Matrix Theory

Random Matrix Model for the Ecological Model of Innovation and Entrepreneurship Education for College Students

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