In the past few decades considerable effort has been expended in characterizing and modeling financial time series. A number of stylized facts have been identified, and volatility clustering or the tendency toward persistence has emerged as the central feature. In this paper we propose an appropriately defined conditional probability as a new measure of volatility clustering. We test this measure by applying it to different stock market data, and we uncover a rich temporal structure in volatility fluctuations described very well by a scaling relation. The scale factor used in the scaling provides a direct measure of volatility clustering; such a measure may be used for developing techniques for option pricing, risk management, and economic forecasting. In addition, we present a stochastic volatility model that can display many of the salient features exhibited by volatilities of empirical financial time series, including the behavior of conditional probabilities that we have deduced.
Effects of analyst sentiment on volatility dynamics in financial market
Ningbo University of Finance & Economics（宁波财经学院）；Wenzhou University of Technology（温州理工学院）；Fuyao University of Science and Technology（福耀科技大学）；Yunnan University（云南大学）
We study the activity, i.e., the number of transactions per unit time, of financial markets. Using the diffusion entropy technique we show that the autocorrelation of the activity is caused by the presence of peaks whose time distances are distributed following an asymptotic power law which ultimately recovers the Poissonian behavior. We discuss these results in comparison with ARCH models, stochastic volatility models and multi-agent models showing that ARCH and stochastic volatility models better describe the observed experimental evidences.
What does the financial market pricing do? A simulation analysis with a view to systemic volatility, exuberance and vagary
Biondi et al.（2012）开发了一个分析模型，以研究股票市场价格形成随时间推移的新兴动态特性，能够捕捉重要的程式化事实。这些后一种性质证明是敏感的基本信息提供的监管制度，以及对市场的信心条件之间的实际和潜在的投资者。以按市价（公允价值）计量交易证券为基础的制度虽然在市场价格和基本信号之间产生较高的线性相关性，但也涉及较高的市场不稳定性和波动性。这些制度还在市场信心空间的某些区域引发更多相关的市场繁荣和反复无常的事件，在这些区域进一步出现较低的市场流动性。
Mitigating Financial Risk from Climate-Induced Agricultural Price Volatility
Chennai Mathematical Institute（金奈数学研究所）；AI 4 Water LTD（AI for Water有限公司）；Institute for Interdisciplinary Research（跨学科研究所）；University College London（伦敦大学学院）；School of Computational & Integrative Sciences, Jawaharlal Nehru University（贾瓦哈拉尔·尼赫鲁大学计算与整合科学学院）
