TY - GEN
T1 - Log Periodic Power Law Fitting on Indian Stock Market
AU - Naik, Nagaraj
AU - Mohan, Biju R.
N1 - Publisher Copyright:
© 2020, Springer Nature Singapore Pte Ltd.
PY - 2020
Y1 - 2020
N2 - 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.
AB - 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.
UR - https://www.scopus.com/pages/publications/85088207833
UR - https://www.scopus.com/pages/publications/85088207833#tab=citedBy
U2 - 10.1007/978-981-15-6318-8_4
DO - 10.1007/978-981-15-6318-8_4
M3 - Conference contribution
AN - SCOPUS:85088207833
SN - 9789811563171
T3 - Communications in Computer and Information Science
SP - 38
EP - 43
BT - Machine Learning, Image Processing, Network Security and Data Sciences - 2nd International Conference, MIND 2020, Proceedings
A2 - Bhattacharjee, Arup
A2 - Borgohain, Samir Kr.
A2 - Soni, Badal
A2 - Verma, Gyanendra
A2 - Gao, Xiao-Zhi
PB - Springer
T2 - 2nd International Conference on Machine Learning, Image Processing, Network Security and Data Sciences, MIND 2020
Y2 - 30 July 2020 through 31 July 2020
ER -