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市场方向判断中的模仿与赢则留、输则换

文章 arXiv papers · 作者: Mario Gutiérrez-Roig et al.
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总结

本研究通过实地实验室实验，考察人们如何判断金融市场会上涨还是下跌。志愿者收到基于全球指数真实数据的受控金融信息，并多次预测市场方向。研究者分析这些决策中的行为模式，并报告了两种反复出现的策略：模仿市场和赢则留、输则换；其中模仿更为普遍。

报告的模式会随决策环境而变化。专家建议、信息不足和信息过载都与更多使用这些直觉策略有关，而花更多时间思考则与较低的使用概率相关。群组分析报告称，女性和儿童更多使用这些策略，但预测表现并未降低。这些发现来自所述实验环境；提供的文本未给出样本量、效应大小，也没有证据表明这种行为会直接延伸到真实交易。研究指出，这些发现可能与界面设计和价格动态的行为模型有关。

核心观点

  • 实验利用基于真实指数数据的受控信息，研究人们对市场方向的判断。
  • 研究发现，市场模仿和赢则留、输则换是反复出现的决策模式。
  • 据报告，市场模仿是两种模式中更普遍的一种。
  • 建议以及信息不足或过载，都与更多使用直觉策略有关。
  • 决策时间越长，使用这些模式的概率越低。
  • 报告的群组差异并不意味着女性或儿童的预测表现较差。

标签

股票多资产市场情绪统计学市场微观结构
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# Market Imitation and Win-Stay Lose-Shift strategies emerge as unintended patterns in market direction guesses


# Market Imitation and Win-Stay Lose-Shift strategies emerge as unintended patterns in market direction guesses









Decisions taken in our everyday lives are based on a wide variety of information so it is generally very difficult to assess what are the strategies that guide us. Stock market therefore provides a rich environment to study how people take decision since responding to market uncertainty needs a constant update of these strategies. For this purpose, we run a lab-in-the-field experiment where volunteers are given a controlled set of financial information -based on real data from worldwide financial indices- and they are required to guess whether the market price would go up or down in each situation. From the data collected we explore basic statistical traits, behavioural biases and emerging strategies. In particular, we detect unintended patterns of behavior through consistent actions which can be interpreted as {\it Market Imitation} and {\it Win-Stay Lose-Shift} emerging strategies, being {\it Market Imitation} the most dominant one. We also observe that these strategies are affected by external factors: the expert advice, the lack of information or an information overload reinforce the use of these intuitive strategies, while the probability to follow them significantly decreases when subjects spends more time to take a decision. The cohort analysis shows that women and children are more prone to use such strategies although their performance is not undermined. Our results are of interest for better handling clients expectations of trading companies, avoiding behavioural anomalies in financial analysts decisions and improving not only the design of markets but also the trading digital interfaces where information is set down. Strategies and behavioural biases observed can also be translated into new agent based modelling or stochastic price dynamics to better understand financial bubbles or the effects of asymmetric risk perception to price drops.

在遵守原作品许可的前提下，附作者信息全文展示。 许可协议: abstract CC0

此摘要由 Stratmill 研究智能体根据原文撰写，并非原文副本。