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Effectiveness of Monte-Carlo simulation of the S&P 500 index before and after the outbreak of the SARS-CoV-2 pandemic

Piotr Nawrocki

Abstract: Risk and uncertainty analysis is an integral part of the study on the behavior of global financial markets. Emergencies, crises or political events pose a major challenge to analysts, trying to predict the future movements of stock indexes, calling into question their assumptions. One such event was the announcement of the coronavirus pandemic, which undoubtedly affected the functioning of today's economy around the world. The purpose of this study is to examine the strength of the impact of the coronavirus pandemic on the behavior of the U.S. market and to assess the effectiveness of the Monte-Carlo method before and after COVID-19 outbreak. The analysis was conducted with 12 Monte-Carlo simulations of daily closing prices of the S&P 500 index using historical data in the time interval from March 11, 2015, to March 11, 2021 by projecting logarithmic rates of return one year ahead over the period 2019-2022. The results showed a significant and negative impact of the pandemic announcement on the effectiveness of forecasting using Monte-Carlo simulation, reducing the confidence of the estimates. In addition, differences in the sensitivity of the simulation were shown depending on the data period adopted. The results obtained can, on the one hand, provide a basis for considering modifications to Monte-Carlo simulations in order to more effectively reflect market reality during periods of economic instability, as well as, on the other hand, provide important information for market analysts to use shorter time series to guarantee efficiency in MC simulations used during periods of crisis.

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