The European Journal of Finance ( IF 1.903 ) Pub Date : 2021-03-19 , DOI: 10.1080/1351847x.2021.1900888 Shima Amini 1 , Robert Hudson 2 , Andrew Urquhart 3 , Jian Wang 2
We show that expected returns on US stocks and all major global stock market indices have a particular form of non-linear dependence on previous returns. The expected sign of returns tends to reverse after large price movements and trends tend to continue after small movements. The observed market properties are consistent with various models of investor behaviour and can be captured by a simple polynomial model. We further discuss a number of important implications of our findings. Incorrectly fitting a simple linear model to the data leads to a substantial bias in coefficient estimates. We show through the polynomial model that well-known short-term technical trading rules may be substantially driven by the non-linear behaviour observed. The behaviour also has implications for the appropriate calculation of important risk measures such as value at risk.
中文翻译:
非线性无处不在:对经验金融、技术分析和风险价值的影响
我们表明,美国股票和所有主要全球股票市场指数的预期收益对以前的收益具有特定的非线性依赖形式。在价格大幅波动后,预期的回报迹象往往会逆转,而在小幅波动后,趋势往往会继续。观察到的市场属性与投资者行为的各种模型一致,可以通过一个简单的多项式模型来捕捉。我们进一步讨论了我们发现的一些重要意义。错误地将简单的线性模型拟合到数据会导致系数估计值出现严重偏差。我们通过多项式模型表明,众所周知的短期技术交易规则可能在很大程度上由观察到的非线性行为驱动。