A predictive analysis on ASPI, Bank Industry and Consumer Services Industry indices based on macro-economic variables during the COVID environment of Colombo Stock Exchange

Abstract

"This study intends to identify the pre-specified macro-economic variables that affect the All Share Price Index (ASPI) and selected sectorial indices {i.e. Banks Industry Group Index and Consumer Services Industry Group Index} using daily data for the period starting from April 2020 to March 2022 (Post pandemic era), analyze the identified macroeconomic variables’ impact on the overall market and on the identified sector indices and build a machine learning model that is capable of predicting the sector indices given a set of macro-economic variables. After a thorough literature review, six macro-economic factors namely overnight liquidity, exchange rate, interest rate, gold prices, oil prices and freight charges were identified for which the data was collected mainly from secondary sources such as CSE, Central Bank of Sri Lanka (CBSL). The researcher has then built 6 predictive models in order to identify the significant macro-economic variables and has chosen the optimum machine learning algorithm at the end of the research which can be utilized by investors to take informed decisions. The study will be conducted as a regression analysis and can be categorized as quantitative research."