英文标题：
《Market Imitation and Win-Stay Lose-Shift strategies emerge as unintended
patterns in market direction guesses》
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作者：
Mario Guti\\\'errez-Roig, Carlota Segura, Jordi Duch, Josep Perell\\\'o
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最新提交年份：
2016
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英文摘要：
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.
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中文摘要：
我们在日常生活中做出的决定是基于各种各样的信息，因此通常很难评估指导我们的策略。因此，股票市场为研究人们如何做出决策提供了一个丰富的环境，因为应对市场不确定性需要不断更新这些策略。为此，我们进行了一项现场实验，在实验中，志愿者们获得了一组受控的财务信息——基于全球金融指数的真实数据——他们被要求猜测在每种情况下市场价格是上涨还是下跌。从收集的数据中，我们探索了基本的统计特征、行为偏差和新出现的策略。特别是，我们通过一致的行为来发现意外的行为模式，这些行为可以被解释为{\\it市场模仿}和{\\it赢家-输家-转移}新兴策略，其中{\\it市场模仿}是最主要的策略。我们还观察到，这些策略受到外部因素的影响：专家建议、信息缺乏或信息过载会加强这些直觉策略的使用，而当受试者花更多时间做决定时，遵循这些策略的概率会显著降低。队列分析表明，妇女和儿童更倾向于使用这种策略，尽管他们的表现没有受到影响。我们的研究结果有助于更好地处理客户对交易公司的期望，避免金融分析师决策中的行为异常，并不仅改善市场设计，还改善交易数字界面（其中包含信息）。观察到的策略和行为偏差也可以转化为新的基于代理的建模或随机价格动态，以更好地理解金融泡沫或不对称风险感知对价格下跌的影响。
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分类信息：

一级分类：Quantitative Finance 数量金融学
二级分类：General Finance 一般财务
分类描述：Development of general quantitative methodologies with applications in finance
通用定量方法的发展及其在金融中的应用
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一级分类：Physics 物理学
二级分类：Physics and Society 物理学与社会
分类描述：Structure, dynamics and collective behavior of societies and groups (human or otherwise). Quantitative analysis of social networks and other complex networks. Physics and engineering of infrastructure and systems of broad societal impact (e.g., energy grids, transportation networks).
社会和团体（人类或其他）的结构、动态和集体行为。社会网络和其他复杂网络的定量分析。具有广泛社会影响的基础设施和系统（如能源网、运输网络）的物理和工程。
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