Micro-Foundation of ARCH Model

T. Mizuta
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引用次数: 1

Abstract

The Japanese version of this paper can be found at http://ssrn.com/abstract=2710516.Many macroeconomic study argued macroeconomic models should be aggregated by micro processes models ("micro-foundation") and many micro-founded macroeconomic models were built. On the other hand, there are many models for price variation of a risk asset, which is macro phenomena, however, there are few studies for micro-foundation of such models. In this study we tried micro-foundation of an ARCH model using intelligence of artificial market simulation studies. That is we tried to clarify which micro processes determine each coefficient of an ARCH model. Then, we showed that the dispersion of investors' estimated prices is larger or the orders by the buy-sell imbalance taking liquidity are more, the volatility is larger. And we showed that the ration of the normal investors taking liquidity to the noise traders providing liquidity is higher or the measure of risk aversion of the normal investors is lower, the magnitude of volatility clustering is larger.
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ARCH模型的微观基础
本文的日文版本可以在http://ssrn.com/abstract=2710516.Many宏观经济研究中找到,该研究认为宏观经济模型应该通过微观过程模型(“微观基础”)进行汇总,并建立了许多微观基础的宏观经济模型。另一方面,风险资产价格变动的宏观现象模型较多,但对模型微观基础的研究较少。在本研究中,我们尝试用人工市场模拟研究智能ARCH模型的微观基础。也就是说,我们试图澄清哪些微过程决定了ARCH模型的每个系数。然后,我们证明了投资者估计价格的分散性越大,或者买入卖出不平衡的订单越多,波动性越大。结果表明,正常投资者采取流动性的比例高于提供流动性的噪音交易者,或者正常投资者的风险厌恶度量较低,波动性聚类的幅度较大。
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