Economics & Finance

Investment Strategies 2.0
A Guide to Combining Behavioral Finance and Artificial Intelligence for Better Investment Outcomes

Editors: Anju Singla, PhD
Garima Saini, PhD
Poonam Saini, PhD

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Investment Strategies 2.0

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Artificial intelligence (AI) and behavioral finance are two fields that have the potential to complement each other in various ways. Behavioral finance is the study of how human psychology and behavior affect financial decision-making. It is concerned with understanding how emotions, biases, and heuristics impact investment choices and financial outcomes. Conversely, AI refers to the development of computer algorithms and systems that can perform tasks that typically require human intelligence, such as learning, problem-solving, and decision-making. It is based on the idea that investors are not always rational, and their decisions can be influenced by biases, heuristics, and emotions.

Largely, people tend to be overconfident about their investment abilities and often engage in herd mentality, following the crowd instead of making independent decisions. AI can be applied to behavioral finance using machine learning algorithms to analyze and predict patterns of human behaviour in financial markets. It identifies patterns in trading behavior by analyzing sentiment in financial news articles, social media, and other sources of data that can influence financial decision-making. AI algorithms can process vast amounts of data, recognize patterns and relationships, and make predictions based on statistical models.

In the financial industry, AI is used in various applications, including investment research, trading, and risk management. The combination of behavioral finance and AI has the potential to revolutionize the financial industry by providing more accurate and personalized investment advice, reducing the impact of behavioral biases, and improving overall investment performance. One way AI can be applied in behavioral finance is through the analysis of investor behaviour such as their buying and selling patterns, AI algorithms can identify common biases and heuristics that may be influencing their decision-making. Based on this analysis, the AI can then provide personalized recommendations to help investors overcome these biases and make more informed decisions.

Sub Themes:

  • Behavioral Finance
  • Artificial Intelligence (AI) in Investing
  • Combining Behavioral Finance and AI
  • Investor Psychology
  • Risk Management
  • Market Analysis and Prediction
  • Investor Behavior and Market Efficiency
  • Practical Investment Strategies
  • Ethics and Responsible Investing
  • Case Studies and Examples
Important Deadlines:

Submission Guidelines:


Chapter proposal submission due (750 words): 30th September, 2023
Primary notification to authors: 5th October, 2023
Full chapter submission: 20th November, 2023
Chapter acceptance notification: 20th December, 2023
Submission of final chapters: 10th January,2023


Send your chapter proposal to:
email: istaylorfrancis@gmail.com

The book is scheduled to be published by Apple Academic Press. Exclusive co-publishing with CRC Press, Taylor and Francis Group.


NO PUBLICATION/PROCESSING FEE INVOLVED AT ANY STAGE


About the Authors / Editors:
Editors: Anju Singla, PhD
Associate Professor, Centre of Management and Humanities (CMH), Punjab Engineering College, India
E-mail: anjusingla@pec.edu.in


Garima Saini, PhD
Faculty, Centre of Management and Humanities (CMH), Punjab Engineering College, India
E-mail: garimasaini@pec.edu.in


Poonam Saini, PhD
Associate Professor, CSE, Punjab Engineering College, India
E-mail: poonamsaini@pec.edu.in





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