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本文在回顾过往各类经典量化模型的基础上另辟蹊径,着重探讨了“同一股票在不同时间的时变波动率与时变收益率的关系”这一问题。在经过实证检验后,发现同一标的波动率与收益率呈负相关,即“高风险≠高收益”!在构建基于波动率调控仓位的模型时,本文并不像一些经典模型那样复杂,而是力求简洁明了,采取单变量模型策略。在实证检验的过程中,模型选取上证综指为标的,经过模型优化,在六年的模拟操作中共取得了320%的绝对收益,相对指数的累计超额收益率近100%,模型的收益率分布与夏普指数也远远好于同期的上证综指。因此,对于厌恶风险的投资者来说,就可以利用这种现象构造出方差小但收益也不低的组合。本文第二部分回顾了过往各类经典量化模型并作了相应的评价,第三部分重点论述了我们提出的理论与模型,第四部分则总结了我们的结论。
Based on the review of various classic quantitative models, this paper explores the relationship between the time-varying volatility and the time-varying rate of return of the same stock at different times. After the empirical test, we found that the volatility of the same index is negatively correlated with the yield, that is, “high risk ≠ high yield”! This article is not as complex as some classical models when building a model based on volatility positions, Instead, it strives to be concise and clear and adopts a univariate model strategy. In the empirical test, the model selected the Shanghai Composite Index as the benchmark, after the model optimization, in the six-year simulation made a total of 320% of the absolute return, the relative index of the cumulative excess return rate of nearly 100%, the model of the distribution of returns And the Sharp index is also much better than the same period of the Shanghai Composite Index. Therefore, investors who are risk averse can use this phenomenon to construct a combination of small variance and low returns. The second part of this article reviews the past classical quantitative models and makes corresponding evaluations. The third part focuses on the theories and models that we propose. The fourth part summarizes our conclusions.