英文标题：
《Sequential Detection of Market shocks using Risk-averse Agent Based
Models》
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作者：
Vikram Krishnamurthy and Sujay Bhatt
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最新提交年份：
2015
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英文摘要：
This paper considers a statistical signal processing problem involving agent based models of financial markets which at a micro-level are driven by socially aware and risk- averse trading agents. These agents trade (buy or sell) stocks by exploiting information about the decisions of previous agents (social learning) via an order book in addition to a private (noisy) signal they receive on the value of the stock. We are interested in the following: (1) Modelling the dynamics of these risk averse agents, (2) Sequential detection of a market shock based on the behaviour of these agents. Structural results which characterize social learning under a risk measure, CVaR (Conditional Value-at-risk), are presented and formulation of the Bayesian change point detection problem is provided. The structural results exhibit two interesting prop- erties: (i) Risk averse agents herd more often than risk neutral agents (ii) The stopping set in the sequential detection problem is non-convex. The framework is validated on data from the Yahoo! Tech Buzz game dataset.
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中文摘要：
本文考虑了一个统计信号处理问题，涉及基于代理的金融市场模型，这些模型在微观层面上由具有社会意识和风险厌恶的交易代理驱动。这些代理人通过订单簿，除了他们收到的关于股票价值的私人（嘈杂的）信号外，还利用以前代理人的决策信息（社会学习），进行股票交易（买卖）。我们对以下内容感兴趣：（1）对这些风险规避代理人的动态进行建模，（2）基于这些代理人的行为对市场冲击进行顺序检测。在风险度量CVaR（Conditional Value at risk）下，给出了表征社会学习的结构结果，并给出了贝叶斯变化点检测问题的公式。结构结果显示了两个有趣的特性：（i）风险厌恶型代理比风险中性代理更容易从众（ii）序列检测问题中的停止集是非凸的。该框架基于雅虎网站的数据进行了验证！科技巴斯游戏数据集。
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分类信息：

一级分类：Mathematics 数学
二级分类：Optimization and Control 优化与控制
分类描述：Operations research, linear programming, control theory, systems theory, optimal control, game theory
运筹学，线性规划，控制论，系统论，最优控制，博弈论
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一级分类：Quantitative Finance 数量金融学
二级分类：Trading and Market Microstructure 交易与市场微观结构
分类描述：Market microstructure, liquidity, exchange and auction design, automated trading, agent-based modeling and market-making
市场微观结构，流动性，交易和拍卖设计，自动化交易，基于代理的建模和做市
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