论文标题
使用Hawkes模型探测的左边和右尾极端事件的不对称激发：适用财务回报
Asymmetric excitation of left- and right-tail extreme events probed using a Hawkes model: application to financial returns
论文作者
论文摘要
我们构建了一个两尾峰值阈值霍克斯模型，该模型在时间序列中捕获不对称的自我和交叉兴趣。我们通过调查标准普尔500股票指数的每日日志返回中的极端收益和损失来证明其适用性。我们发现，极端损失和收益的到达是通过共同的条件强度描述的，损失的贡献是收益的两倍。但是，前者的贡献比后者的贡献差不多近五倍。我们将这些不对称性归因于市场交易者的不同反应，这是资产价格的极端上下移动：消极偏见的一个例子，其中创伤比欣快感更为显着。
We construct a two-tailed peak-over-threshold Hawkes model that captures asymmetric self- and cross-excitation in and between left- and right-tail extreme values within a time series. We demonstrate its applicability by investigating extreme gains and losses within the daily log-returns of the S&P 500 equity index. We find that the arrivals of extreme losses and gains are described by a common conditional intensity to which losses contribute twice as much as gains. However, the contribution of the former decays almost five times more quickly than that of the latter. We attribute these asymmetries to the different reactions of market traders to extreme upward and downward movements of asset prices: an example of negativity bias, wherein trauma is more salient than euphoria.
