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基于价格持续时间的中国股市日内风险价值预测 被引量:4
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作者 鲁万波 王卫东 《数理统计与管理》 CSSCI 北大核心 2012年第3期527-536,共10页
基于高频数据度量日内交易活动的风险是目前日内金融数据与风险管理中极具挑战性的研究课题之一。本文从实时交易的角度,使用中国股市分笔交易数据,基于价格持续时间的自回归条件持续时间(ACD)模型,研究日内不规则交易数据的风险测度,... 基于高频数据度量日内交易活动的风险是目前日内金融数据与风险管理中极具挑战性的研究课题之一。本文从实时交易的角度,使用中国股市分笔交易数据,基于价格持续时间的自回归条件持续时间(ACD)模型,研究日内不规则交易数据的风险测度,利用日内不等间隔波动模型估计了日内交易的即时条件波动率,对日内不等间隔风险价值进行了预测和检验。实证结果发现日内不等间隔风险价值模型能够比较好的刻画日内交易风险,股票投资者和市场监管者可以基于该工具对日内风险做出合理的预测,达到止损避险和控制风险的目的。 展开更多
关键词 价格持续时间 风险价值 超高频数据 ACD模型
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Dependencies between price duration, volatility, volume and return on the Warsaw Stock Exchange
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作者 Malgorzata Doman Ryszard Doman 《Journal of Modern Accounting and Auditing》 2010年第10期27-38,共12页
The successive changes of asset prices are the most visible manifestation of financial markets dynamics. There exist different views about factors generating these changes, but many researchers and practitioners agree... The successive changes of asset prices are the most visible manifestation of financial markets dynamics. There exist different views about factors generating these changes, but many researchers and practitioners agree that the most important among them is the impact of information flow. According to the market microstructure theories, it depends mainly on the behavior of informed and uniformed traders. In the paper, we investigate dependencies between the possible proxies of information process: price duration and corresponding to it volume change and return. Our main objective is to answer the question about the most important factor in the process of discovering information by uniformed traders. We apply a set of models for volatility, volume and duration data. Our analysis is performed for selected equities listed on the Warsaw Stock Exchange and uses tick-by-tick data. The obtained results show that the stock liquidity on this leading stock market in Central and Eastern Europe is the most important factor influencing the process of discovering information by uninformed traders. 展开更多
关键词 market microstructure VOLUME VOLATILITY price duration dynamics stock returns ACD models ACV models
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