Portfolio Research Based on Mean-Realized Variance-CVaR and Random Matrix Theory under High-Frequency Data

Yang, Yajie; Zhu, Yipin; Zhao, Xiaoyan

doi:10.4236/jfrm.2020.94026

Cited by 3 publications

(1 citation statement)

References 19 publications

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“…An efficient portfolio is one that presents the optimal risk/return trade-off for an investor. Optimization problems in finance using risk measures or the dynamic programming principle and the Hamiltonjacobibellman theory are studied in the works of Schied [3], Gundel [4], Barrieu and El Karoui [5], Yang and al [6] and Mbigili and al [7]. Marginal risks are important criterion in portfolio management [8] [9].…”

Section: Introductionmentioning

confidence: 99%

Management of a Complex Portfolio of Assets with Stochastic Drifts and Volatilities

Yaméogo¹,

Ouédraogo²,

Barro³

2022

OJS

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In financial analysis risk quantification is essential for efficient portfolio management in a stochastic framework. In this paper we study the value at risk, the expected shortfall, marginal expected shortfall and value at risk, incremental value at risk and expected shortfall, the marginal and discrete marginal contributions of a portfolio. Each asset in the portfolio is characterized by a trend, a volatility and a price following a three-dimensional diffusion process. The interest rate of each asset evolves according to the Hull and White model. Furthermore, we propose the optimization of this portfolio according to the value at risk model.

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Section: Introductionmentioning

confidence: 99%

Management of a Complex Portfolio of Assets with Stochastic Drifts and Volatilities

Yaméogo¹,

Ouédraogo²,

Barro³

2022

OJS

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An evaluation method of open-pit slope stability based on Poset theory

Jiang,

Sun,

Wang

et al. 2024

Geomech. Geophys. Geo-energ. Geo-resour.

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To achieve an objective and reasonable judgment on slope stability, the partially ordered set (Poset) theory is applied to the slope stability evaluation against the engineering background of an open pit slope. From the four aspects of rock mass structural characteristics, slope morphology, environment conditions and engineering conditions, 24 typical evaluation indices such as cohesion, internal friction angle, elastic modulus and Poisson’s ratio are selected. Based on the Poset theory, a Poset evaluation model is established. According to the slope stability evaluation indices and the risk grade classification criteria, the slope stability risk grade is divided into four grades: stable (Grade I), generally stable (Grade II), slightly stable (Grade III) and unstable (Grade IV). The index data are normalized and the weight ranking information is used. Implicit weighting is carried out by means of accumulation. The comparison relation matrix, the Hasse matrix and the Hasse diagram are constructed for each factor layer and comprehensive index layer, respectively. This method was utilized to evaluate the risk grade of an engineering example, determine the slope risk grade, and compare with the actual situation. The results show that the slope to be evaluated is generally stable (Grade II) under the comprehensive evaluation indices of various factors, and the assessed stability condition is consistent with the actual situation. These verify the rationality and applicability of the proposed method and provide a new insight for accurately identifying the stability condition of open-pit slopes.

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Power Load Forecasting Method Based on Random Matrix Theory and CNN-LSTM Model

Huang

Tian

et al. 2022

2022 IEEE 2nd International Conference on Digital Twins and Parallel Intelligence (DTPI)

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Portfolio Research Based on Mean-Realized Variance-CVaR and Random Matrix Theory under High-Frequency Data

Cited by 3 publications

References 19 publications

Management of a Complex Portfolio of Assets with Stochastic Drifts and Volatilities

Management of a Complex Portfolio of Assets with Stochastic Drifts and Volatilities

An evaluation method of open-pit slope stability based on Poset theory

Power Load Forecasting Method Based on Random Matrix Theory and CNN-LSTM Model

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