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与传统资产定价模型中风险收益权衡关系相悖,我国房地产市场存在投资异象和波动长记忆性特征。文章利用泰勒规则(Taylor Rule)的利率缺口,在剔除市场预期之后测度了中国市场的货币政策冲击,并基于房地产投资回报的时序数据波动聚集性和时变性特征构建GARCH(1,1)-M模型,以此度量我国房地产市场投资收益的波动演变路径,解释了央行实施加息的货币政策后当期房价反而上涨的投资现象。文章还立足于房地产市场参与人的投资特征,从行为金融学的全新研究视角出发,建立包含行为资产定价的动态模型经济系统,研究资产价格波动与最优货币政策选择问题,求得相应闭型解,为实施关注资产价格波动的最优货币政策提供理论基础。
Contrary to the trade-off between risk and return in the traditional asset pricing model, there are investment visions and long-term volatile memory in China’s real estate market. The paper uses the Taylor Rule interest rate gap to measure the impact of monetary policy in the Chinese market after excluding market expectations and build GARCH (1,1) -M based on volatility aggregation and time-varying characteristics of the time series data of real estate investment returns Model, in order to measure the volatility of China’s real estate market return on investment path of evolution explained the central bank to implement the interest rate hike monetary policy but the current rise in the current phenomenon of investment. Based on the investment characteristics of participants in the real estate market, the article sets up a dynamic model economic system including behavioral asset pricing from the perspective of a new study of behavioral finance, studies the problem of asset price volatility and optimal monetary policy selection, Solution, to provide the theoretical basis for the implementation of the optimal monetary policy focusing on asset price fluctuations.