Investors' trading behavior in boom and bust markets
Investors' trading behavior in boom and bust markets
批准号:
427318789
负责人:
Professor Dr. Martin Weber
金额:
$0.0万
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 2023-12-31
中文摘要
自最近的全球金融危机及其后果以来,金融市场的宏观经济周期日益成为主要讨论的主题。虽然危机本身引发了加强消费者保护的呼吁,但人们对宏观经济冲击如何影响投资者的信念和偏好(即他们的风险厌恶)的潜在驱动因素知之甚少,因此,宏观经济冲击如何影响个人投资者的交易行为。通过我们的研究计划,我们的目标是为这场正在进行的辩论做出贡献。更准确地说,我们试图回答两个核心问题。首先,个人投资者的交易如何受到宏观经济周期(即繁荣与萧条市场)的影响?第二,繁荣和萧条市场中交易行为的差异是由投资者风险偏好的变化(即他们固有的风险态度)还是由信念的变化(即他们对未来风险/回报的估计)驱动的?更深入地了解个人投资者在不同市场周期中的交易方式和原因具有实际意义,并可能提供重要的政策启示。特别是考虑到最近的消费者保护措施,有必要更多地了解投资行为的潜在驱动因素。一个例子是金融工具市场指令(MiFID),它要求投资公司引出客户的风险偏好。然而,没有关于如何以及多久评估一次风险概况的指导方针。从本质上讲,我们希望获得有关投资者信念和偏好的时间动态的见解。这反过来又使我们能够就如何提高消费者保护政策的有效性提出建议。为此,我们提出了一种结合实证和实验分析的三折方法。在我们的第一个工作项目(WP1)中,我们的目标是实证调查投资者的抛售行为在宏观经济周期中是否以及如何不同。特别是,我们研究了处置效应,即投资者倾向于过早卖出赢家,长期持有输家,如何在繁荣和萧条时期发生变化。在第二个工作项目(WP2)中,我们分析了不同市场条件下投资行为的驱动因素。更准确地说,我们的目标是通过实验来检验投资者在繁荣和萧条市场之间如何学习形成信念的差异是否解释了投资行为。在我们的第三个工作项目(WP3)中,我们将通过对繁荣和萧条市场中购买行为的实证和实验调查来补充之前对销售行为的分析。在分析中,我们将重点关注三种类型的再投资决策。总的来说,我们的目标是对繁荣和萧条市场的交易行为提供全面的分析。因此,我们首先分析销售和购买行为在宏观经济周期中的差异,然后测试导致观察到的行为的驱动因素(偏好与信念)。在方法上,我们结合了经验和实验分析。
英文摘要
Since the recent global financial crisis and its aftermath, macroeconomic cycles of financial markets are increasingly subject of major discussions. While the crisis itself gave rise to a call for greater consumer protection, little is known about the underlying drivers of how macroeconomic shocks affect investors’ beliefs and preferences (i.e. their risk aversion) and consequently, how macroeconomic shocks affect individual investors’ trading behavior. With our research proposal we aim to contribute to this ongoing debate. More precisely, we seek to answer two central questions. First, how is the trading of individual investors affected by macroeconomic cycles (i.e. boom and bust markets)? Second, are differences in trading behavior across boom and bust markets driven by a change in investors’ risk preferences (i.e. their inherent risk attitude) or by a change in beliefs (i.e. their estimates about future risk/returns)?A deeper understanding of how and why individual investors trade differently across market cycles is of practical relevance and may provide important policy implications. Especially in the light of recent consumer protection efforts, it is essential to learn more about the underlying drivers of investment behavior. An example is the Markets in Financial Instruments Directive (MiFID) which requires investment firms to elicit customers risk preferences. However, there are no guidelines about how and how often risk profiles should be evaluated. In essence, we expect to obtain insights about the time dynamics of investors’ beliefs and preferences. This, in turn, allows us to make suggestions about how to improve the effectiveness of consumer protection policies. To do so, we propose a three-folded approach, which combines empirical and experimental analyses. In our first working project (WP1), we aim to empirically investigate if and how investors’ selling behavior is different across macroeconomic cycles. In particular, we study how the disposition effect, i.e. investors tendency to sell winners too early and hold losers too long, changes in boom and bust periods. In the second working project (WP2), we analyze the drivers of investment behavior across market conditions. More precisely, we aim to test experimentally whether differences in how investors learn to form beliefs between boom and bust markets explain the investment behavior.In our third working project (WP3), we will complement previous analyses on selling behavior by empirical and experimental investigations on buying behavior across boom and bust markets. We will focus on three types of reinvestment decisions in the analysis.Overall, we aim to provide a holistic analysis on trading behavior in boom and bust markets. Therefore, we first analyze how selling as well as buying behavior differ across macroeconomic cycles, and then test drivers (preferences vs. beliefs) causing the observed behavior. Methodological-wise, we combine empirical and experimental analyses.
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