论文标题
预测外源风险对股票市场的影响的方法
Methods for forecasting the effect of exogenous risk on stock markets
论文作者
论文摘要
市场受到内源性和外源性风险的影响,这些风险导致全球金融和经济市场中断,最终导致股票市场迅速下降。过去,在任何经济破坏后,市场都恢复了。在此基础上,我们将重点放在Covid-19的爆发中,作为外源风险的案例研究,并分析其对标准和穷人500(S \&P500)指数的影响。我们假设S \&P500指数达到最低限度,然后在不远的将来再次上升。在这里,我们提出两种情况,以预测S \&P500索引。第一个案例估计了华盛顿大学在02/04/2020释放的预期死亡。对于第二种情况,假定死亡的峰值数量将自第一个确认案件发生以来,将发生2个月。在预测趋势的初始点之后的三个月内估计了指数的下降和恢复。预测是对由$ q $ -Gaussian扩散过程描述的随机波动进行预测的预测,并具有三个时空状态。我们的预测是基于前提,即任何市场响应都可以分解为总体确定性趋势和随机术语。该预测基于确定性部分,在此案例研究中,通过在爆发的初始阶段的S \&P500数据趋势的推断来近似。随机波动的结构与过去24年的结构相同。以85%的精度获得了合理的预测。
Markets are subjected to both endogenous and exogenous risks that have caused disruptions to financial and economic markets around the globe, leading eventually to fast stock market declines. In the past, markets have recovered after any economic disruption. On this basis, we focus on the outbreak of COVID-19 as a case study of an exogenous risk and analyze its impact on the Standard and Poor's 500 (S\&P500) index. We assumed that the S\&P500 index reaches a minimum before rising again in the not-too-distant future. Here we present two cases to forecast the S\&P500 index. The first case uses an estimation of expected deaths released on 02/04/2020 by the University of Washington. For the second case, it is assumed that the peak number of deaths will occur 2-months since the first confirmed case occurred in the USA. The decline and recovery in the index were estimated for the following three months after the initial point of the predicted trend. The forecast is a projection of a prediction with stochastic fluctuations described by $q$-gaussian diffusion process with three spatio-temporal regimes. Our forecast was made on the premise that any market response can be decomposed into an overall deterministic trend and a stochastic term. The prediction was based on the deterministic part and for this case study is approximated by the extrapolation of the S\&P500 data trend in the initial stages of the outbreak. The stochastic fluctuations have the same structure as the one derived from the past 24 years. A reasonable forecast was achieved with 85\% of accuracy.