英文标题：
《Density Forecasts and the Leverage Effect: Some Evidence from
Observation and Parameter-Driven Volatility Models》
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作者：
Leopoldo Catania and Nima Nonejad
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最新提交年份：
2016
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英文摘要：
The leverage effect refers to the well-established relationship between returns and volatility. When returns fall, volatility increases. We examine the role of the leverage effect with regards to generating density forecasts of equity returns using well-known observation and parameter-driven volatility models. These models differ in their assumptions regarding: The parametric specification, the evolution of the conditional volatility process and how the leverage effect is accounted for. The ability of a model to generate accurate density forecasts when the leverage effect is incorporated or not as well as a comparison between different model-types is carried out using a large number of financial time-series. We find that, models with the leverage effect generally generate more accurate density forecasts compared to their no-leverage counterparts. Moreover, we also find that our choice with regards to how to model the leverage effect and the conditional log-volatility process is important in generating accurate density forecasts
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中文摘要：
杠杆效应指的是回报率和波动率之间的既定关系。当回报率下降时，波动性增加。我们使用著名的观察和参数驱动的波动率模型，研究杠杆效应在生成股票收益密度预测方面的作用。这些模型在以下方面的假设有所不同：参数规格、条件波动过程的演变以及杠杆效应的解释方式。利用大量金融时间序列，对模型在是否考虑杠杆效应时生成准确密度预测的能力以及不同模型类型之间的比较进行了研究。我们发现，与没有杠杆效应的模型相比，具有杠杆效应的模型通常能生成更准确的密度预测。此外，我们还发现，我们在杠杆效应和条件对数波动过程建模方面的选择对于生成准确的密度预测非常重要
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分类信息：

一级分类：Statistics 统计学
二级分类：Applications 应用程序
分类描述：Biology, Education, Epidemiology, Engineering, Environmental Sciences, Medical, Physical Sciences, Quality Control, Social Sciences
生物学，教育学，流行病学，工程学，环境科学，医学，物理科学，质量控制，社会科学
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一级分类：Quantitative Finance 数量金融学
二级分类：Risk Management 风险管理
分类描述：Measurement and management of financial risks in trading, banking, insurance, corporate and other applications
衡量和管理贸易、银行、保险、企业和其他应用中的金融风险
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一级分类：Statistics 统计学
二级分类：Computation 计算
分类描述：Algorithms, Simulation, Visualization
算法、模拟、可视化
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