Ikigai Consulting
Understanding NIFTY100 Movements using Machine learning / Data science models
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Stock Market Analysis Project
The stock market serves as a crucial indicator of economic health, influencing investment decisions, corporate strategies, and overall financial stability. Accurate prediction of stock market indices is essential for investors, policymakers, and financial analysts alike. In this project, we aim to analyze the impact of various independent variables on the Nifty100 index.
Objectives
- Investigate the individual and collective impact of the chosen variables on the Nifty100 index over the last 10 years.
- Examine the long-run and short-run relationships between these parameters and the NIFTY 100 index.
- Provide insights and recommendations for investors and policymakers.
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Methodology
- Data Collection: Collected monthly data for FII, DII, Exchange Rate, CPI, IIP, Inflation, SP500 and NIFTY100 for the last 10 years.
- Preprocessing: Performed data cleaning to handle missing values in the dataset.
- EDA: Performed exploratory data analysis to understand the relationship between the independent variables and the target.
- Modelling: Fitted an OLS model to predict NIFTY100 movements using our independent variables.
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Results
EDA
- Exchange Rate was converted to log scale before analysis.
- Strong positive relationship between SP500, Exchange Rate, Consumer Price Index, Index of Industrial Production and the NIFTY 100 index.
- Weak positive relationship between DII Net, Inflation and NIFTY100.
- Weak negative relationship between FII Net and the NIFTY 100 index.
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