Log Periodic Power Law Fitting on Indian Stock Market

Abstract

Stock price prediction is one of the challenging tasks for researchers and academics due to frequent changes in stock prices. The stock prices are speculation, and it purely depends on the demand and supply of the market during the trading session. Most of the existing work approach is foresting stock prices using machine learning methods. There has been a limited number of studies on stock crisis identification. Log periodic power law (LPPL) is one of the approaches to identify bubbles in the stock market before crises happened. By looking at existing work, we found that LPPL has not applied in the Indian stock market. In this paper, we have considered LPPL to identify a bubble in the Indian stock market. Due to fluctuation in the market, stock price follows the nonlinearity behavior, hence LPPL is considered to fit the equations. The experiment is carried out R Studio platform. © 2020, Springer Nature Singapore Pte Ltd.