Abstract The paper aims to address a topic of interest, namely: the influence and effect of the major disruptions from recent years on one of the largest important stock markets. The purpose of the paper is to show the influence of these disruptions on the US stock market, considering market efficiency and measuring the estimated Bid-Ask spread. Using daily and weekly data sets over a period of 13 years, based on the closing stock prices of 10 companies listed in the category of the NASDAQ and NYSE stock indexes and calculating the return at (t) and (t+1) for each stock, the covariance of the two returns at (t) and (t+1) and using at t and (t+1) a "rolling window" of 21 days, which represents the trading days, as well as using the weekly data series in the same way, we obtained the relationship between the spread measurement and its size, a strong negative cross-sectional relationship, for which we performed a series of statistical tests summarized in the paper. Later, we split the data for each year separately so that we’d be able to use for each year a cross-sectional regression of the spread over the logarithmic values of the size and we noticed that there is a strong negative relationship between the two of them. According to the results obtained, it can be observed that the strongest negative correlations are in 2019 and 2021 in the case of data with daily frequency and 2020, and 2021 in the case of data with weekly frequency, for an informationally efficient market, where transaction costs are zero and in which the market price contains all the relevant information. The strongly negative correlations recorded can be explained by the fact that strong negative influences took place during these periods, which contributed to the disruption of the stock market and not only. At the same time, these negative correlations on the stock market analyzed in the last period also show a wider spread increase which theoretically shows low liquidity.
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