时间序列技术:估计波动性

IF 1.1 4区 经济学 Q3 BUSINESS, FINANCE
Stephen Marra
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引用次数: 0

摘要

作者考察了市场从业者广泛使用的不同波动性估计方法。这些技术从简单到复杂,包含了不同程度的向后和前瞻性数据。作者讨论了资产类别回报的特征,这些特征使波动性本质上比回报本身更具预测性。他比较了各种波动性估计模型,评估了它们在不同资产类别和市场环境中的特征和预测能力。最后,他评估了波动率估计作为资产配置工具的应用。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Time-Series Techniques: Estimating Volatility
The author examines the different methods of volatility estimation widely used among market practitioners. These techniques range from the simple to the complex and incorporate varying degrees of backward- and forward-looking data. The author discusses the characteristics of asset class returns that make volatility inherently more predictive than returns themselves. He compares a variety of volatility estimation models, assessing their characteristics and predictive abilities across different asset classes and market environments. Finally, he assesses the application of volatility estimates as an asset allocation tool.
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来源期刊
Journal of Portfolio Management
Journal of Portfolio Management Economics, Econometrics and Finance-Finance
CiteScore
2.20
自引率
28.60%
发文量
113
期刊介绍: Founded by Peter Bernstein in 1974, The Journal of Portfolio Management (JPM) is the definitive source of thought-provoking analysis and practical techniques in institutional investing. It offers cutting-edge research on asset allocation, performance measurement, market trends, risk management, portfolio optimization, and more. Each quarterly issue of JPM features articles by the most renowned researchers and practitioners—including Nobel laureates—whose works define modern portfolio theory.
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