Data Analytics for Finance Using Python by Nitin Jaglal Untwal & Utku Kose

Author:Nitin Jaglal Untwal & Utku Kose
Language: eng
Format: epub, pdf
Publisher: CRC Press
Published: 2025-10-15T00:00:00+00:00

6.2 Decision Tree

Decision tree is a diagrammatic representation of all decisions with their possible outcomes (Li & Cheng, 2023). It is an important tool for strategic management as far as investment is considered. It also gives all possible outcomes. It can act as a regression model by classification of different outcome. It is a tool for the analysis of decisions and all possible outcomes (García & Martínez, 2023; Huang & Zhao, 2023; Kim & Park, 2023). The root node is the starting node of a decision tree and is also known as the mother node. The leaf node is the end node of a decision tree with zero Gini value.

The decision tree can be an effective tool for stock price predictive analytics (Du et al., 2023; Olorunnimbe & Viktor, 2023). The decision tree is highly accurate with stock price prediction since it can predict the volatility and risk of the stock market (Zhou et al., 2023). The efficiency of a decision tree model is enhanced by making a hybrid model with a relative machine learning model such as LSTM (Feng & Zhang, 2023; Liu et al., (2023). The decision tree is used for portfolio management and volatility assessment of the stock market (Chen & Lin, 2023; Kumar & Das, 2023; Wang & Zhang, 2023). The use of the decision tree trading algorithm in market sentiment analysis has shown the importance of decision tree in the finance field (Lee & Kim, 2023; Rodriguez & Lopez, 2023; Patel et al., 2023; Wang 2023). The combination of decision tree with other machine learning techniques and artificial intelligence has a huge impact on financial data analysis decisions (Singh & Gupta, 2023; Patel & Roy, 2023; Yang & Liu, 2023).

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