Research Question: This paper explores the pre-market auction price behaviour. The pre-market auction is a short duration auction, where the orders are executed with too little time for revision by the makers. The literature paid attention to application of random walk hypothesis (RWH) and its variants in efficient market (EMH) tests. Motivation: The pre-opening auction is an extremely short duration auction where traders are interested in a limited number of large cap stocks and the orders are not transparent. The interest lies on efficiency tests of discrete prices during the pre-market auction for the benefit of investors. Idea: The mechanism of price discovery in call auctions is important since they could impact normal markets. We aim to test major relevant hypotheses for pre-opening equilibrium prices. The rejection of the randomness would mean that it is possible to use historical stock prices alone. Data: The sample comprises all 50 NSE 50 Index constituent stocks sampled during the year 2019. The NSE constituent stocks maintain the highest market capitalization and have a long history of trading. Method/Tools: It summarizes the source literature on objectively driven synthesis on simulation-based decision making since the early period of 1973. Multivariate lognormal distribution is a challenging method than ordinary univariate Monte Carlo. By generating a 50 X 50 covariance matrix of prices and solving for Cholesky roots, the results were compared against lognormal multivariate Monte Carlo simulation to explore the estimates of volatility. Findings: The results demonstrate a good case for the tests of RWH and objectively arriving at the pre-opening equilibrium prices. The co-efficient of variation (COV) remained at 3.33%. We found that the stock prices were correlated among themselves, which infers the weak form of efficiency. Previous results had mentioned that MC generated higher sample variances and unsuitable, however, we found lower variances in using multi-variate Monte Carlo. Contributions: The contribution lies in the attempts using multi-variate log normal distribution to deduce prices with lower estimated variance. The results have implications to making trade decisions and portfolio construction during the Covid period, where high degree of persisting decline happened to indices.