VAR and VECM models were used to investigate the factors that influence of Indian securities market performance, including the period of Covid 19's financial crises
DOI:
https://doi.org/10.31181/10025112023sKeywords:
VECM, VAR model, cointegration, BSE (Sensex), Covid 19Abstract
Using a dummy variable, we evaluate commodities in addition to macroeconomic considerations of the Indian securities market from 2010 to 2021, which includes the era of the Covid 19 crises. We used the Bombay Stock Exchange (BSE) (Sensex) for securities market performance and developed a Vector Auto regressive models that combines the short- and long-run model of economics. On stock price indexes, we discovered that the Indian securities market reflects both macroeconomic indicators and prices of commodity. Growth in the economy, inflation, interest, rates, currency rates, crude oil prices, and gold prices are all factors to consider were all used in this study to see how they affected BSE (Sensex) prices during the Covid 19 crises. In their first difference, all series were judged to be stationary. We discovered that shocks to all eight factors had both positive and negative effects on BSE (Sensex) prices in the short and long term, including Covid 19 crises. Each securities market index’s most significant impulse is its own shock, decreasing from short to long-term. We also used the Joint Co-Integration Test to detect and confirm the lack of a long-term equilibrium link (cointegration) between all eight variables, resulting in four cointegration equations with an estimated error correction term at the 0.05 level (speed of adjustment towards equilibrium) of 0.007362. Vector Error Correction Mode (VECM), on the other hand, suggests that the BSE (Sensex) has a significant value with its lagged values of.007362 and 0.517952. We created Vector Auto regressive (VAR) models for the BSE (Sensex) using eight independent variables, including Dummy variables, but their statistics were not significant, despite the fact that the lagged value of crude oil, gold prices, the rupee, and the BSE (Sensex) lagged value were all significant. We proceed to estimate VECM. We proved the short and long-term effects of lagged BSE(Sensex) prices, crude oil prices, gold prices, and the currency on the BSE (SENSEX) using several robustness tests. Dummy factors have also been included to see how the Covid 19 crisis affected the BSE (Sensex) prices. We discovered that crude oil prices followed value, gold prices lagged value, and rupees based on the dollar had a significant impact on BSE(Sensex) pricing over the study period, including the Covid 19 crises from March 2020 to June 2021.
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