Curriculum Overview
The Finance program at Prayaga Institute of Management Studies is structured over 8 semesters, with each semester comprising core courses, departmental electives, science electives, and laboratory sessions. This structured approach ensures that students develop a solid foundation in finance principles while gaining specialized knowledge through elective choices.
Semester-wise Course Structure
Year | Semester | Course Code | Course Title | Credits (L-T-P-C) | Prerequisites |
---|---|---|---|---|---|
Year 1 | Semester I | FN-101 | Principles of Economics | 3-1-0-4 | - |
FN-102 | Calculus and Linear Algebra | 3-1-0-4 | - | ||
Semester II | FN-103 | Probability and Statistics | 3-1-0-4 | FN-102 | |
FN-104 | Introduction to Financial Accounting | 3-1-0-4 | - | ||
Semester III | FN-105 | Business Communication | 2-0-0-2 | - | |
FN-106 | Financial Mathematics | 3-1-0-4 | FN-102 | ||
Semester IV | FN-107 | Corporate Finance Fundamentals | 3-1-0-4 | FN-104, FN-106 | |
FN-108 | Introduction to Financial Markets | 3-1-0-4 | FN-101 | ||
Year 2 | Semester V | FN-201 | Investment Analysis and Portfolio Theory | 3-1-0-4 | FN-107, FN-103 |
FN-202 | Risk Management Concepts | 3-1-0-4 | FN-103 | ||
Semester VI | FN-203 | Financial Econometrics | 3-1-0-4 | FN-103, FN-106 | |
FN-204 | International Finance | 3-1-0-4 | FN-107 | ||
Semester VII | FN-205 | Derivatives and Risk Modeling | 3-1-0-4 | FN-201, FN-202 | |
FN-206 | Fixed Income Securities | 3-1-0-4 | FN-201 | ||
Semester VIII | FN-207 | Advanced Financial Analysis | 3-1-0-4 | FN-201, FN-205 | |
FN-208 | Capstone Project in Finance | 2-0-0-2 | All previous courses |
Advanced Departmental Electives
Departmental electives offer students the opportunity to explore specialized areas within Finance. Below are descriptions of some advanced courses:
- Advanced Derivatives Pricing: This course explores complex derivative instruments including exotic options, structured products, and interest rate derivatives. Students learn to price these instruments using advanced mathematical models and numerical methods.
- Quantitative Methods in Finance: Focused on applying statistical techniques and algorithms to financial data, this course covers regression analysis, time series forecasting, and Monte Carlo simulations.
- Behavioral Economics in Finance: This course investigates how psychological factors influence financial decision-making. Topics include cognitive biases, heuristics, prospect theory, and market anomalies.
- Private Equity and Venture Capital: Students examine the structure and functioning of private equity firms and venture capital funds. The course covers deal structuring, due diligence, valuation techniques, and exit strategies.
- Credit Risk Modeling: This course provides an in-depth look at credit risk assessment models used by banks and financial institutions. It includes historical default data analysis, scoring models, and regulatory compliance frameworks.
- Fixed Income Securities: Students study the pricing, risk management, and trading of fixed income securities such as bonds, mortgage-backed securities, and asset-backed securities.
- Financial Statement Analysis: This course teaches students to analyze financial statements using ratios, trend analysis, and industry comparisons. It emphasizes identifying red flags and assessing company performance.
- Algorithmic Trading Strategies: Students learn how to design, implement, and backtest algorithmic trading strategies using Python, R, or MATLAB. The course includes market microstructure concepts and execution costs.
- Regulatory Compliance in Financial Services: This course covers regulatory frameworks affecting financial institutions, including Basel III, Dodd-Frank Act, MiFID II, and other international standards.
- Global Financial Markets: An overview of global financial markets including forex, commodities, equity markets, and emerging economies. The course includes currency risk management and cross-border investment strategies.
- Climate Finance and Green Bonds: Focuses on the intersection of environmental sustainability and finance. Students study green bonds, carbon markets, ESG investing, and climate risk assessment tools.
- Banking and Financial Institutions: This course examines the structure and operations of commercial banks, central banks, and other financial institutions, including their role in monetary policy and economic stability.
- Financial Data Analytics with Python: Students learn to extract insights from large datasets using Python libraries like pandas, numpy, and matplotlib. The course covers data cleaning, visualization, and predictive modeling techniques.
- Entrepreneurial Finance: Designed for aspiring entrepreneurs, this course explores funding mechanisms, valuation methods, business planning, and financial strategy for startups.
- Islamic Wealth Management: Covers Sharia-compliant investment products and wealth management strategies. Students study sukuk issuance, Islamic equity valuation, and asset allocation models compliant with Islamic principles.
Project-Based Learning Philosophy
The Finance department at Prayaga Institute of Management Studies believes in experiential learning through project-based assignments. Our philosophy centers on fostering innovation, analytical thinking, and practical application of theoretical concepts.
Mini-Projects: During the first three years, students undertake mini-projects that allow them to apply classroom knowledge to real-world scenarios. These projects are typically completed in groups and involve case studies, market research, or financial modeling exercises. Mini-projects are assessed based on clarity of approach, analytical depth, presentation quality, and peer feedback.
Final-Year Thesis/Capstone Project: In the final year, students select a capstone project that integrates all knowledge acquired during their studies. Projects may involve developing an investment strategy, conducting empirical research on financial markets, designing a fintech product, or analyzing risk profiles of financial institutions. Students work closely with faculty mentors who guide them through the research process and help refine their methodologies.
The selection process for capstone projects is collaborative. Students propose project ideas aligned with their interests and career aspirations. Faculty members evaluate proposals based on feasibility, relevance, and academic rigor. Once selected, students receive ongoing mentorship throughout the project lifecycle, including regular progress meetings, feedback sessions, and final presentations.