Course Schedule Overview

Semester	Course Code	Course Title	Credits (L-T-P-C)	Prerequisites
1st	FN101	Introduction to Financial Markets	3-0-0-3	-
1st	FN102	Principles of Economics	3-0-0-3	-
1st	FN103	Calculus for Business	4-0-0-4	-
1st	FN104	Statistics for Finance	3-0-0-3	-
1st	FN105	Financial Accounting Fundamentals	3-0-0-3	-
1st	FN106	Financial Literacy and Ethics	2-0-0-2	-
2nd	FN201	Corporate Finance	3-0-0-3	FN101, FN105
2nd	FN202	Investment Analysis and Portfolio Theory	3-0-0-3	FN101, FN104
2nd	FN203	Risk Management	3-0-0-3	FN104
2nd	FN204	Financial Statement Analysis	3-0-0-3	FN105
2nd	FN205	Financial Modeling and Valuation	3-0-0-3	FN103, FN104
2nd	FN206	Introduction to Python for Finance	2-0-0-2	FN103
3rd	FN301	Derivatives and Structured Products	3-0-0-3	FN202, FN203
3rd	FN302	Behavioral Finance and Decision Making	3-0-0-3	FN201, FN204
3rd	FN303	Quantitative Methods in Finance	3-0-0-3	FN205, FN206
3rd	FN304	International Finance and Global Markets	3-0-0-3	FN201, FN202
3rd	FN305	Financial Markets and Institutions	3-0-0-3	FN201, FN202
3rd	FN306	Fintech Innovation and Digital Banking	3-0-0-3	FN206
4th	FN401	Advanced Corporate Finance	3-0-0-3	FN301, FN302
4th	FN402	Research and Thesis Writing in Finance	3-0-0-3	All previous courses
4th	FN403	Capstone Project in Finance	3-0-0-3	All previous courses
4th	FN404	Sustainable Finance and ESG Investing	3-0-0-3	FN302, FN304
4th	FN405	Regulatory Frameworks in Finance	3-0-0-3	FN201, FN301
4th	FN406	Financial Engineering and Algorithmic Trading	3-0-0-3	FN303, FN305

Advanced Departmental Electives

Departmental electives offer students the opportunity to deepen their knowledge in specialized areas of finance. These courses are designed to provide advanced insights into current trends and emerging practices in the field:

• Derivatives and Structured Products: This course explores complex financial instruments used for hedging, speculation, and arbitrage. Students learn about options, futures, swaps, and other derivatives, including their valuation models and risk implications.
• Behavioral Finance and Decision Making: This elective examines how psychological factors influence investment decisions and market behavior. It integrates theories from psychology, neuroscience, and economics to understand investor biases and irrational behaviors in financial markets.
• Quantitative Methods in Finance: Designed for students interested in data-driven finance, this course introduces statistical modeling, econometrics, and machine learning techniques applied to financial analysis and forecasting.
• International Finance and Global Markets: This course covers exchange rate dynamics, international capital flows, foreign direct investment, and the role of global institutions in shaping financial policies across countries.
• Financial Markets and Institutions: An exploration of how financial markets operate, including the roles of banks, insurance companies, mutual funds, pension funds, and central banks in facilitating economic activity.
• Fintech Innovation and Digital Banking: This elective focuses on emerging technologies in finance such as blockchain, digital currencies, robo-advisors, mobile payments, and AI-driven financial services.
• Advanced Corporate Finance: Students study advanced topics in corporate finance including capital structure decisions, dividend policies, mergers and acquisitions, and international corporate finance strategies.
• Sustainable Finance and ESG Investing: This course addresses environmental, social, and governance factors in investment decisions, exploring sustainable investment strategies, green bonds, carbon pricing, and impact investing models.
• Regulatory Frameworks in Finance: A comprehensive look at financial regulations, including Basel III, Dodd-Frank Act, and global regulatory reforms aimed at enhancing financial stability and reducing systemic risk.
• Financial Engineering and Algorithmic Trading: This course introduces algorithmic trading strategies using Python and R, focusing on high-frequency trading, market microstructure analysis, and automated portfolio optimization techniques.

Project-Based Learning Philosophy

The department strongly believes in project-based learning as a cornerstone of education. This approach encourages students to engage with real-world challenges and apply theoretical knowledge to practical situations.

The mini-project component begins in the second year, where students work in teams on small-scale research or consulting assignments related to current financial issues. These projects help develop analytical thinking, teamwork, and communication skills essential for future careers.

The final-year thesis or capstone project is a significant milestone that allows students to explore an area of personal interest within finance under the supervision of a faculty mentor. The project must demonstrate originality, depth, and relevance to current industry needs.

Project selection involves collaboration between students and faculty members. Students propose topics based on their interests and career aspirations, while mentors guide them through research methodologies, data collection, analysis, and presentation techniques.

Evaluation criteria include the clarity of objectives, methodology rigor, quality of results, and overall contribution to knowledge or practice in finance. Students are assessed not only on technical competence but also on their ability to articulate findings effectively in both written and oral formats.