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Consumption-portfolio choice and asset pricing with preferences for social status

Consumption-portfolio choice and asset pricing with preferences for social status
社会地位偏好下的消费组合选择和资产定价
批准号:
420492791
负责人:
Professor Dr. Holger Kraft
金额:
$0.0万
依托单位:
依托单位国家:
德国
项目类别:
Research Grants
财政年份:
2019
资助国家:
德国
项目状态:
已结题
起止时间:
2018-12-31 至 2022-12-31

项目摘要

项目成果

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中文摘要
翻译
衡量自己的成就是当今社会固有的一个过程。例如,成年人用收入来与同事或邻居进行比较。根据这些想法,我们的项目研究社会互动对个人财务决策和资产价格的影响。我们项目中提出的效用规范抓住了我们生活的一些基本方面,即超越同龄人或嫉妒的感觉。特别是,这些对社会地位的偏好抓住了经验证据,即代理人将自己的消费和/或财富与同龄人进行比较。这导致了相互关联的决策问题,可以正式描述为随机微分对策。我们的项目对金融学的两个领域有贡献,即消费组合选择和均衡资产定价。在第一种情况下,我们分析了当代理人与同行进行基准比较时,他们的财务决策是如何变化的。我们的公式产生了标准模型中不存在的额外对冲动机。一个潜在的应用是对基金经理决策的影响。主动管理基金的表现可以从两个方面进行评估:首先,人们可以衡量相对于被动基准(如标准普尔500指数)的相对表现,这是外部给定的。第二,可以将基金的业绩与同类基金的业绩进行比较。自上世纪90年代中期以来,后者变得越来越重要,当时晨星公司(Morningstar Inc.)推出了基于同行群体的基金排名。我们想分析一下,如果基金经理以同行为基准,他们的决策倾向于哪个方向。特别是,了解基于同行群体的排名如何在金融危机中影响投资组合策略是至关重要的。这是因为对某些资产需求的系统性扭曲会严重放大危机的影响。在均衡资产定价的情况下,我们将对社会偏好的分析扩展到另一个方向:我们没有考虑同期基准对个人资产需求的影响,而是研究了施加市场出清条件的一般均衡设置。在这种情况下,我们可以求解均衡股票收益、股票波动率、无风险利率和市场风险价格。因此,我们可以解决这样一个问题:对社会地位的偏好是否有助于解释一个经济体中处于资产定价核心的各种资产定价现象,比如著名的股权溢价之谜或过度波动之谜。此外,我们可以推导出与一般均衡设置一致的整个经济基准的动态。最后,我们的模型产生了资产定价时刻的内生可预测性,通过模型的灵活性,可以校准为数据中观察到的可预测性模式。
英文摘要
Benchmarking own achievements is a process that is inherent in today’s society. For instance, adults use income to benchmark themselves against colleagues or neighbors. Following these ideas, our project studies the effects of social interaction on financial decisions of individuals and asset prices. The utility specification proposed in our project captures some essential aspects of our lives, namely getting ahead of our peers or feelings of envy. In particular, these preferences for social status capture the empirical evidence that agents benchmark their consumption and/or wealth against their peers. This leads to involved interlinked decision problems that can be formally described as stochastic differential games. Our project contributes to two fields of Finance, namely, consumption-portfolio choice and equilibrium asset pricing. In the first case, we analyze how financial decisions of agents change when they are benchmarked against peers. Our formulation gives rise to additional hedging motives that are not present in standard models. A potential application is the effect on the decisions of fund managers. The performance of actively managed funds can be evaluated in two dimensions: First, one can measure the relative performance with respect to a passive benchmark such as the S&P 500 that is exogenously given. Second, one can compare the fund performance with the performance of funds in the same category. The latter has become increasingly important since the mid of the 90s when, among others, Morningstar Inc. introduced peer-group based fund rankings. We would like to analyze in which direction the decisions of fund managers are tilted if they are benchmarked against their peers. In particular, it is crucial to understand how peer-group based rankings influence the portfolio strategies in a financial crisis. This is because systematic distortions of the demands for certain assets can severely amplify the effects of a crisis.In the case of equilibrium asset pricing, we extend our analysis of social preferences into another direction: Instead of considering the effect of contemporaneous benchmarking on the asset demands of individuals, we study a general equilibrium setting where market clearing conditions are imposed. In such a setting, we can solve for the equilibrium stock return, stock volatility, risk-free rate, and market price of risk. We can thus address the question of whether preferences for social status can contribute to explaining various asset pricing phenomena in an economy that are at the heart of asset pricing such as the famous equity premium puzzle or the excess volatility puzzle. Furthermore, we can derive the dynamics of an economy-wide benchmark that is consistent with a general equilibrium setting. Finally, our model generates endogenous predictability of asset pricing moments that, by the flexibility of the model, can be calibrated to predictability patterns as observed in the data.
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