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An Agent-Based Model of a Pricing Process with Power Law, Volatility Clustering, and Jumps

机译:具有权力法,波动簇聚类和跳跃的定价过程的基于代理的模型

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In this paper, we propose a new model of security price dynamics in order to explain the stylized facts of the pricing process such as power law distribution, volatility clustering, jumps, and structural changes. We assume that there are two types of agents in the financial market: speculators and fundamental investors. Speculators use past prices to predict future prices and only buy assets whose prices are expected to rise. Fundamental investors attach a certain value to each asset and buy when the asset is undervalued by the market. When the expectations of agents are exogenously driven, that is, entirely shaped by exogenous news, then they can be modeled as following a random walk. We assume that the information related to the two types of agents in the model will arrive randomly with a certain probability distribution and change the viewpoint of the agents according to a certain percentage. Our simulated results show that this model can simulate well the random walk of asset prices and explain the power-law tail distribution of returns, volatility clustering, jumps, and structural changes of asset prices.
机译:在本文中,我们提出了一种新的安全价格动态模型,以解释诸如电力法分布,波动聚类,跳跃和结构变化等定价过程的程式化事实。我们假设金融市场中有两种类型的代理商:投机者和基本投资者。投机者使用过去的价格来预测未来的价格,只购买价格预期上涨的资产。基本投资者对各种资产附加一定的价值,并在资产被市场低估时购买。当药剂的期望被外源驱动时,即完全由外源新闻进行完全成形,然后它们可以根据随机步行建模。我们假设与模型中两种类型的代理相关的信息将随机到达某种概率分布,并根据一定百分比改变代理的观点。我们的模拟结果表明,该模型可以模拟资产价格随机步行,并解释返回,波动集群,跳跃和资产价格结构变化的权力律尾部分布。

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