论文标题

风险管理和回报预测

Risk Management and Return Prediction

论文作者

Ge, Qingyin, Ma, Yunuo, Liao, Yuezhi, Li, Rongyu, Zhu, Tianle

论文摘要

随着金融业的良好发展,市场开始吸引人们的眼睛,不仅是由于从债券和股票到期货和期货的多样化的投资选择,而且还源于一般的“高风险,高级奖励”的心态,促使人们将钱投入金融市场。人们有兴趣在给定的回报水平下降低风险,因为没有办法具有高回报和低风险。许多研究人员一直在研究这个问题,最开创性的是哈里·马克维茨(Harry Markowitz)于1952年开发的现代投资组合理论,该理论是投资组合管理的基石,旨在“以给定风险的风险最高回报”。与此相比,五十年后,E。Robert Fernholz的随机投资组合理论与作为早期现代投资组合理论的基础相反,与实际投资组合和市场的可观察到的特征是一致的。在本文中,在引入了Markowitz的MPT和Fernholz的SPT的一些基本理论之后,我们跨越了应用程序,试图在基于Markowitz有效边界的四个基本模型下弄清楚,包括Markowitz模型,恒定相关模型,单个索引模型和单因素模型以及多因素模型,哪些竞赛组和这些竞争者在这些portforlios中都可以在Portforlios中表现出来。在这里,我们还涉及通用投资组合算法Thomas M.覆盖以选择投资组合作为比较。此外,将评估每个投资组合价值处于风险,预期的不足和风险管理的相应的自举置信区间。最后,通过利用因子分析和时间序列模型,我们可以预测四个模型的未来性能。

With the good development in the financial industry, the market starts to catch people's eyes, not only by the diversified investing choices ranging from bonds and stocks to futures and options but also by the general "high-risk, high-reward" mindset prompting people to put money in the financial market. People are interested in reducing risk at a given level of return since there is no way of having both high returns and low risk. Many researchers have been studying this issue, and the most pioneering one is Harry Markowitz's Modern Portfolio Theory developed in 1952, which is the cornerstone of investment portfolio management and aims at "maximum the return at the given risk". In contrast to that, fifty years later, E. Robert Fernholz's Stochastic Portfolio Theory, as opposed to the normative assumption served as the basis of earlier modern portfolio theory, is consistent with the observable characteristics of actual portfolios and markets. In this paper, after introducing some basic theories of Markowitz's MPT and Fernholz's SPT, then we step across to the application side, trying to figure out under four basic models based on Markowitz Efficient Frontier, including Markowitz Model, Constant Correlation Model, Single Index Model, and Multi-Factor Model, which portfolios will be selected and how do these portfolios perform in the real world. Here we also involve universal Portfolio Algorithmby Thomas M. Cover to select portfolios as a comparison. Besides, each portfolio value at Risk, Expected Shortfall, and corresponding bootstrap confidence interval for risk management will be evaluated. Finally, by utilizing factor analysis and time series models, we could predict the future performance of our four models.

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