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Fees
₹3,50,000
Placement
92.0%
Avg Package
₹65,00,000
Highest Package
₹1,20,00,000
Fees
₹3,50,000
Placement
92.0%
Avg Package
₹65,00,000
Highest Package
₹1,20,00,000
Seats
200
Students
200
Seats
200
Students
200
| Semester | Course Code | Course Title | Credit Structure (L-T-P-C) | Prerequisites |
|---|---|---|---|---|
| 1 | FN-101 | Mathematics for Finance I | 3-0-0-3 | - |
| 1 | FN-102 | Introduction to Financial Markets | 3-0-0-3 | - |
| 1 | FN-103 | Financial Accounting Fundamentals | 3-0-0-3 | - |
| 1 | FN-104 | Statistics for Finance | 3-0-0-3 | - |
| 1 | FN-105 | Business Communication | 2-0-0-2 | - |
| 1 | FN-106 | Computer Programming for Finance | 3-0-0-3 | - |
| 2 | FN-201 | Financial Accounting II | 3-0-0-3 | FN-103 |
| 2 | FN-202 | Corporate Finance Principles | 3-0-0-3 | FN-101 |
| 2 | FN-203 | Financial Markets and Institutions | 3-0-0-3 | FN-102 |
| 2 | FN-204 | Economics for Finance | 3-0-0-3 | FN-101 |
| 2 | FN-205 | Financial Statement Analysis | 3-0-0-3 | FN-201 |
| 2 | FN-206 | Data Analytics for Finance | 3-0-0-3 | FN-104 |
| 3 | FN-301 | Investment Analysis | 3-0-0-3 | FN-202 |
| 3 | FN-302 | Risk Management | 3-0-0-3 | FN-204 |
| 3 | FN-303 | Derivatives and Financial Engineering | 3-0-0-3 | FN-201 |
| 3 | FN-304 | Behavioral Finance | 3-0-0-3 | FN-204 |
| 3 | FN-305 | Quantitative Methods in Finance | 3-0-0-3 | FN-206 |
| 3 | FN-306 | International Finance | 3-0-0-3 | FN-203 |
| 4 | FN-401 | Advanced Corporate Finance | 3-0-0-3 | FN-301 |
| 4 | FN-402 | Financial Modeling and Valuation | 3-0-0-3 | FN-301 |
| 4 | FN-403 | Algorithmic Trading | 3-0-0-3 | FN-305 |
| 4 | FN-404 | Financial Markets and Portfolio Theory | 3-0-0-3 | FN-301 |
| 4 | FN-405 | Sustainable Finance and ESG Investing | 3-0-0-3 | FN-302 |
| 4 | FN-406 | Financial Ethics and Regulation | 3-0-0-3 | FN-202 |
Advanced departmental electives play a crucial role in shaping students' specialized knowledge and research capabilities. These courses are designed to provide deep insights into specific areas of finance while encouraging critical thinking and innovation.
Investment Banking Techniques: This course explores the intricacies of investment banking, including mergers and acquisitions (M&A), initial public offerings (IPOs), and capital markets operations. Students learn about valuation techniques, due diligence processes, and deal structuring methodologies through real-world case studies and simulations.
Risk Management in Financial Institutions: Focusing on enterprise risk management frameworks, this course covers operational risk, credit risk, market risk, and liquidity risk. It includes hands-on exercises using industry-standard software such as RiskMetrics and CreditRisk+ to assess and mitigate financial risks effectively.
Quantitative Finance and Derivatives: Designed for students interested in mathematical modeling, this course introduces stochastic calculus, option pricing models, and Monte Carlo simulations. Students gain practical experience in developing and implementing quantitative models for derivatives valuation and risk analysis.
Sustainable Finance and ESG Investing: This course integrates environmental, social, and governance (ESG) factors into financial decision-making. Students explore sustainable investment strategies, green bonds, carbon credit markets, and the impact of ESG criteria on portfolio performance.
Fintech Innovation and Digital Banking: With rapid advancements in technology transforming traditional banking, this course examines digital payment systems, blockchain applications, robo-advisors, and decentralized finance (DeFi). Students work on projects involving fintech startups and collaborate with industry partners to understand emerging trends.
Behavioral Finance and Behavioral Economics: This course explores how psychological biases influence financial decision-making. Through experiments and case studies, students analyze investor behavior, market anomalies, and the role of emotions in trading strategies.
International Capital Markets: Covering global capital flows, exchange rate dynamics, and international banking systems, this course helps students understand cross-border financing mechanisms, foreign direct investment (FDI), and the impact of geopolitical events on financial markets.
Financial Statement Analysis and Valuation: Students learn advanced techniques for analyzing financial statements, forecasting cash flows, and valuing companies using various methods such as discounted cash flow (DCF), comparable company analysis, and precedent transaction analysis.
Advanced Derivatives Pricing: This course delves into complex derivatives instruments including exotic options, credit derivatives, and structured products. It covers pricing models like Black-Scholes, binomial trees, and finite difference methods for solving derivative pricing problems.
Algorithmic Trading Strategies: Students explore the design and implementation of algorithmic trading systems using Python, R, and other programming languages. The course includes backtesting strategies, market microstructure analysis, and high-frequency trading concepts.
Corporate Governance and Ethics in Finance: This course emphasizes ethical considerations in financial decision-making, corporate governance frameworks, and regulatory compliance. Students engage in discussions about fiduciary responsibilities, insider trading laws, and corporate transparency.
Financial Engineering and Risk Modeling: Combining mathematical finance with practical applications, this course teaches students how to model financial instruments, simulate scenarios, and develop risk management strategies using advanced computational tools.
Quantitative Methods in Financial Markets: Focusing on statistical analysis and econometric modeling, this course equips students with skills in time series forecasting, regression analysis, and portfolio optimization techniques used in modern financial markets.
Fixed Income Securities and Interest Rate Models: This course covers bond valuation, yield curve construction, and interest rate derivatives. Students learn about fixed income strategies, duration matching, convexity adjustment, and the impact of central bank policies on market rates.
The department believes that project-based learning is essential for developing practical skills and deepening understanding of financial concepts. Projects are assigned at different stages of the program to ensure continuous engagement with real-world applications.
Mini-Projects: In the third year, students undertake mini-projects under faculty supervision. These projects typically last 3-4 months and involve applying theoretical knowledge to solve specific financial problems or conduct research in a chosen area. Students present their findings at departmental symposiums and receive feedback from peers and experts.
Final-Year Thesis/Capstone Project: The capstone project is a significant component of the program, requiring students to complete an independent research study or industry-related initiative over a period of 6-8 months. Projects are selected in consultation with faculty mentors based on student interests and career goals.
Students have access to a wide range of resources including databases, software tools, financial data providers, and mentorship programs. The evaluation criteria include project proposal quality, research methodology, presentation skills, and final deliverables. Successful projects may lead to publications in academic journals or collaborations with industry partners.
