Financial performance analysis using machine learning algorithms: post-IPO of Nykaa
Authors
Singhal, Ruchi
Issue Date
2024-05
Degree
MSc in Business Analytics
Publisher
Dublin Business School
Rights holder
Rights
Abstract
The research looks at how the financial performance of Nykaa which took the IPO in 2021 through 2023 in three years with machine learning models. This work aims to provide more clarity and prediction of the financial situation by using the regression analysis, time series forecasting, and clustering algorithms represented by Python and allowing this project to uncover patterns hidden within Nykaa's financial data. The literature review goes through current studies on machine learning in financial analysis which also deals with research gaps and adds to its practical concerns. The research proposal, through addressing the deficiency and taking advantage of ML-based predictive analytics, seeks to offer result-oriented insights that will be of importance to investors, general observers, and shareholders operating in the digital commerce arena. The study thus looked into the post-IPO finance and stock analysis of Nykaa that is a well-known e-commerce venture in India applying a multidisciplinary approach including clean enrichment, machine learning, and statistical modelling. Already familiarity with Python programming language and SciPy, NumPy, Pandas, Matplotlib, Seaborn, Statsmodels, TensorFlow, and scikit-learn libraries along with ARIMA and LSTM models, the research explore to a Nykaa's stock price precisely and to gain information about its financial health. It carried out the study and received historical stock price data from Yahoo Finance. The data revealed patterns in the growth of Nykaa’s revenues, profitability measures, and cash flow movements. The study used descriptive statistical approaches and visualization methods to uncover critical information about the Nykaa share price fluctuations, capitalization movement patterns, and trading volume developments. Along with this, the trainings of ARIMA and LSTM are quite good in predicting Nykaa's stock prices in the future, where it proves the real applications of machine learning in financing. Therefore, the effect of the IPO of Nykaa in the context of its financial statements' performance provides a good background of how Nykaa's investors, financial analysts, and stakeholders can understand and react responsibly to the financial market dynamics.