商业文章代写-投资组合计算

商业文章代写-投资组合计算

根据巴厘岛和Cakici的研究，预期收益与特质波动之间存在负相关关系。然而，在以不同权重方案计算平均投资组合收益时，这种关系不够稳健。作者发现，按权重相等的特质波动率计算，构建的五分位数投资组合的回报没有显著差异。默顿指出，当投资者未能考虑到不同的摩擦成本而使投资组合完全多元化时，就有可能对特殊风险进行定价。在检验股票预期收益与股票特殊风险之间的关系时，很多时候得到了混合的结果，例如，滞后一个月的股票特殊波动率与股票每月收益之间存在负截面关系。然而，许多其他作者发现了与风险收益权衡相关的时代性，这意味着预期的特质波动率与月度股票收益之间存在正相关关系。
因此，这意味着研究隐含的假设是，随着时间的推移，可以发现恒定的特质风险溢价。傅指出，在特殊风险的情况下，随着时间的推移，显著的可变性指向现有文献的无效，同时确定了存在的积极关系。这是因为早期的研究没有将时变特性作为条件特定性波动来考虑。傅利用月度数据考虑了Nelson提出的EGARCH模型，成功地提供了与基于股票收益方差的条件特质相关的样本内估计。在研究过程中，傅发现了一个主要的正相关关系。后来，明镜周刊与王共同开发了样本外估计，同时预测了特殊波动性和流动性。他们发现，随着特质风险水平的增大，股票收益增加，导致股票流动性下降。他们的主要发现涉及到流动性的核心作用，以及决定股票回报的特质。

商业文章代写-投资组合计算

As per the research study of Bali and Cakici, there is a negative relation presented in between the expected returns and that of the idiosyncratic volatility. However, the relation is not robust enough while calculating the average portfolio returns in terms of diverse weight schemes. The authors found out that no significant difference was there among the quintile portfolio returns by the construction according to idiosyncratic volatility that had equal weight. Merton stated that whenever the investors fail to diversify the portfolios in a complete manner with the consideration of different frictional costs, pricing of idiosyncratic risk is possible. Mixed results in case of examining the relationship presented between the expected stock returns and that of idiosyncratic risk have been found many a time, for example, negative cross-sectional relation present between idiosyncratic volatility that is of one-month lagged and the monthly stock returns. However, many other authors found the contemporaneousness related to risk-return tradeoff, which means there is a positive relation between the expected idiosyncratic volatility and the monthly stock returns.
Therefore, it means the research studies implicitly presuppose the fact that constant idiosyncratic risk premium can be found over the time. Fu stated that substantial variability in case of idiosyncratic risk over time points towards the ineffectiveness of the available literature while identifying the positive relation situated there. It is because the time varying characteristic has not been captured in the earlier studies as per the conditional idiosyncratic volatility. EGARCH model proposed by Nelson was taken into account by Fu by the use of monthly data and the researcher succeeded in providing in-sample estimates related to the conditional idiosyncratic with the variance based on stock returns. During the study, Fu found a major positive relation. Later, Spiegel with Wang developed the out-of-sample estimate while predicting the idiosyncratic volatility along with liquidity. They found that with greater idiosyncratic risk level, the stock returns get increased which results into liquidity decrease of the stock. Their major discovery involves the core role of liquidity as well as idiosyncratic on determining stock returns.

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