Estimation of Jump-Tails: Theory and Applications

跳尾估计：理论与应用

• 批准号: 0957330
• 负责人: Tim Bollerslev
• 金额: $ 27.96万
• 依托单位: National Bureau of Economic Research Inc
• 依托单位国家: 美国
• 项目类别: Continuing Grant
• 财政年份: 2010
• 资助国家: 美国
• 起止时间: 2010-06-01 至 2015-05-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=0957330&HistoricalAwards=false
• 关键词: Estimation; Jump; Tails; Theory; Applications

The recent turmoil in financial markets has highlighted the importance of obtaining a better understanding of the likely occurrence of rare disasters, or so-called "tail" events, and their transmission across different assets and markets. The main theme of the proposed research activities relates to the reliable econometric estimation of such events based high-frequency intraday financial data.Intellectual Merit: The availability of high-frequency intraday asset prices has spurred a large and rapidly growing literature concerned with the analysis of this potentially rich new data source. This project aims to further expand on our ability to extract useful information about important economic phenomena from such data through the development of new econometric procedures and empirical applications thereof. Specifically, combining the insights from traditional Extreme Value Theory (EVT), developed in the context of actuary science under the assumption of independent occurrence of rare events, with so-called realized variation measures, designed to account for empirically realistic volatility clustering in financial markets, the new econometric estimators that we seek to develop as part of the proposal hold the promise of delivering much more accurate estimates for extreme "tail" events than any currently available procedures.Broader Impact: The proposed research program has a number of important broadly defined implications for the theoretical and empirical analyzes of economic and financial data, and should be of interests to theoretically oriented econometricians, as well as applied macroeconomists and financial researchers and regulators alike with an interest in the estimation of "tail" events. In particular, the most important and difficult to manage financial market risks are invariably associated with rare events. Hence, the ability to more accurately measure and possibly forecast the "tails," holds the promise of improved risk management procedures that are better geared toward controlling large risks, leaving aside the smaller "continuous" price moves. By enhancing our understanding of the types of economic "news" that induce large price moves, or "jumps," in financial asset prices, the empirical implementations of the new procedures will also help shed new light on the fundamental linkages between asset markets and the real economy. The lack of investor confidence and fear of "tail" events are often singled out as one of the main culprits behind the massive losses in market values in the advent of the Fall 2008 financial crises, and the idea that rare disasters may help explain apparent mis-pricing has spurred a rapidly growing recent literature. The key arguments put forth in that literature typically hinge on probabilities of severe events that exceed those materialized in-sample, or probabilities calibrated to reflect an unusually broad set of assets and/or countries. Instead, our proposed econometric procedures hold the promise of reliable estimating the likely occurrence of "tail" events in a given market based on actually observed high-frequency data, without resorting to "peso" type explanations.The research results will be disseminated broadly at seminars and conferences. The project will also seek to integrate research and education by involving both graduate and undergraduate students in the proposed research activities. All of the research results, including new computer programs and databases, will be made easily available through the web.

最近金融市场的动荡突出表明，必须更好地了解可能发生的罕见灾难或所谓的“尾部”事件及其在不同资产和市场上的传播。 拟议的研究活动的主题涉及到可靠的计量经济学估计，这些事件的基础上高频日内金融data.Intellectual优点：高频率的日内资产价格的可用性，刺激了大量的和迅速增长的文献关注这个潜在的丰富的新的数据源的分析。 该项目旨在通过开发新的计量经济学程序及其实证应用，进一步扩大我们从这些数据中提取有关重要经济现象的有用信息的能力。 具体而言，结合传统极值理论（EVT）的见解，在精算科学的背景下，假设独立发生的罕见事件，与所谓的实现变化措施，旨在解释金融市场的实证现实波动集群，作为建议的一部分，我们寻求开发的新的计量经济学估计方法有望为极端“尾部”提供更准确的估计。更广泛的影响：拟议的研究计划有一些重要的广泛定义的经济和金融数据的理论和实证分析的影响，并应感兴趣的理论导向计量经济学家，以及应用宏观经济学家和金融研究人员和监管机构都有兴趣在“尾部”事件的估计。 特别是，最重要和最难管理的金融市场风险总是与罕见事件有关。 因此，能够更准确地测量和预测“尾部”，就有希望改进风险管理程序，更好地控制大风险，而不考虑较小的“连续”价格波动。 通过加强我们对导致金融资产价格大幅波动或“跳跃”的经济“新闻”类型的理解，新程序的实证实施也将有助于揭示资产市场与真实的经济之间的基本联系。 投资者信心的缺乏和对“尾部”事件的恐惧往往被挑出来作为2008年秋季金融危机来临时市场价值大规模损失背后的罪魁祸首之一，罕见的灾难可能有助于解释明显的错误定价的想法刺激了最近的文献迅速增长。 这些文献中提出的主要论点通常取决于严重事件的概率，这些概率超过了样本中的具体事件，或者经过校准以反映异常广泛的资产和/或国家的概率。 相反，我们提出的计量经济学方法有望根据实际观察到的高频数据，可靠地估计给定市场中可能发生的“尾部”事件，而不诉诸于“比索”类型的解释。研究结果将在研讨会和会议上广泛传播。 该项目还将通过让研究生和本科生参与拟议的研究活动，寻求将研究和教育结合起来。 所有的研究成果，包括新的计算机程序和数据库，将很容易通过网络提供。