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Fees
₹8,00,000
Placement
94.0%
Avg Package
₹5,20,000
Highest Package
₹9,50,000
Fees
₹8,00,000
Placement
94.0%
Avg Package
₹5,20,000
Highest Package
₹9,50,000
Seats
240
Students
1,200
Seats
240
Students
1,200
The Finance program at The Institute Of Chartered Financial Analysts Of India University Ranchi is structured over 8 semesters, providing a comprehensive educational experience that builds upon foundational knowledge while introducing advanced concepts and practical applications. This carefully designed curriculum ensures students develop both theoretical understanding and practical skills essential for success in the financial industry.
| Course Code | Course Title | Credit Structure (L-T-P-C) | Pre-requisites |
|---|---|---|---|
| FN-101 | Introduction to Financial Concepts | 3-0-0-3 | None |
| FN-102 | Financial Accounting Principles | 3-0-0-3 | None |
| FN-103 | Principles of Economics | 3-0-0-3 | None |
| FN-104 | Mathematics for Finance I | 3-0-0-3 | None |
| FN-105 | Introduction to Financial Markets | 3-0-0-3 | None |
| FN-106 | Financial Communication Skills | 2-0-0-2 | None |
| FN-107 | Computer Applications in Finance | 2-0-0-2 | None |
| FN-108 | Financial Ethics and Professionalism | 2-0-0-2 | None |
| Course Code | Course Title | Credit Structure (L-T-P-C) | Pre-requisites |
|---|---|---|---|
| FN-201 | Financial Statement Analysis | 3-0-0-3 | FN-102, FN-103 |
| FN-202 | Corporate Valuation and Investment Analysis | 3-0-0-3 | FN-104 |
| FN-203 | Risk Management Principles | 3-0-0-3 | FN-104 |
| FN-204 | Financial Markets and Institutions | 3-0-0-3 | FN-105 |
| FN-205 | Mathematics for Finance II | 3-0-0-3 | FN-104 |
| FN-206 | Quantitative Methods in Finance | 3-0-0-3 | FN-104 |
| FN-207 | Financial Modeling and Forecasting | 2-0-0-2 | FN-205 |
| FN-208 | Introduction to Derivatives | 3-0-0-3 | FN-201, FN-204 |
| Course Code | Course Title | Credit Structure (L-T-P-C) | Pre-requisites |
|---|---|---|---|
| FN-301 | Advanced Financial Statement Analysis | 3-0-0-3 | FN-201 |
| FN-302 | Investment Banking and M&A | 3-0-0-3 | FN-202, FN-204 |
| FN-303 | Corporate Finance and Capital Structure | 3-0-0-3 | FN-202 |
| FN-304 | Financial Engineering and Derivatives | 3-0-0-3 | FN-208, FN-205 |
| FN-305 | International Finance and Currency Markets | 3-0-0-3 | FN-204 |
| FN-306 | Behavioral Finance and Decision Making | 3-0-0-3 | FN-201 |
| FN-307 | Sustainable Finance and ESG Investing | 3-0-0-3 | FN-202 |
| FN-308 | Financial Regulation and Compliance | 3-0-0-3 | FN-204 |
| Course Code | Course Title | Credit Structure (L-T-P-C) | Pre-requisites |
|---|---|---|---|
| FN-401 | Advanced Financial Modeling | 3-0-0-3 | FN-301, FN-304 |
| FN-402 | Quantitative Risk Management | 3-0-0-3 | FN-304 |
| FN-403 | Portfolio Theory and Asset Pricing | 3-0-0-3 | FN-301, FN-304 |
| FN-404 | Financial Market Analysis | 3-0-0-3 | FN-301 |
| FN-405 | Capstone Project in Finance | 4-0-0-4 | FN-301, FN-302, FN-303, FN-304 |
| FN-406 | Research Methodology in Finance | 2-0-0-2 | FN-301 |
| FN-407 | Advanced Topics in Financial Economics | 3-0-0-3 | FN-301 |
| FN-408 | Financial Policy and Governance | 3-0-0-3 | FN-303 |
Departmental electives in the Finance program offer students opportunities to explore specialized areas of interest and develop expertise in emerging fields. These courses are designed to complement core curriculum requirements while providing advanced knowledge in specific financial domains.
This course provides comprehensive coverage of derivative instruments including forwards, futures, options, and swaps. Students learn about pricing models, risk management techniques, and practical applications in financial markets. The course emphasizes both theoretical foundations and real-world implementation strategies for managing financial risks.
Learning objectives include understanding the mechanics of various derivatives, applying pricing models such as Black-Scholes and binomial trees, and developing risk management frameworks for portfolio optimization. Students also gain experience with industry-standard software for derivative valuation and risk analysis.
This advanced course focuses on sophisticated quantitative techniques used in modern financial analysis. Students learn about statistical modeling, time series analysis, regression methods, and machine learning applications in finance. The course emphasizes practical implementation of analytical tools for financial decision-making.
Learning objectives include mastering advanced statistical methods, understanding data mining techniques, applying econometric models, and developing programming skills using R and Python for financial analysis. Students also explore predictive modeling approaches for forecasting financial outcomes.
This course examines the psychological factors that influence financial decision-making and market behavior. Students study cognitive biases, heuristics, and behavioral anomalies that affect investment choices and market efficiency. The course integrates insights from psychology and economics to understand irrational behaviors in financial markets.
Learning objectives include identifying common cognitive biases, analyzing market anomalies, understanding prospect theory, and developing frameworks for incorporating behavioral insights into investment strategies. Students also examine case studies of market bubbles and crashes through a behavioral lens.
This course provides in-depth analysis of international financial systems, currency markets, and cross-border capital flows. Students study exchange rate determination, international portfolio diversification, and global financial integration. The course addresses regulatory frameworks governing international financial transactions and emerging market risks.
Learning objectives include understanding international financial theories, analyzing currency markets, evaluating cross-border investment opportunities, and assessing geopolitical risks in global finance. Students also gain insights into international banking regulations and foreign exchange hedging strategies.
This emerging field course focuses on environmental, social, and governance (ESG) factors in financial decision-making. Students learn about sustainable investing approaches, impact measurement, and ESG integration in portfolio management. The course addresses the growing demand for responsible investment strategies that consider long-term sustainability alongside financial returns.
Learning objectives include understanding ESG frameworks, evaluating impact investing opportunities, applying sustainable finance principles, and developing tools for ESG risk assessment. Students also explore regulatory developments in sustainable finance and corporate reporting requirements.
This course combines mathematical modeling with financial theory to develop innovative solutions for complex financial problems. Students learn about algorithmic trading strategies, quantitative risk management, and financial engineering applications. The course emphasizes practical implementation of sophisticated financial models using computational tools.
Learning objectives include developing algorithmic trading systems, applying quantitative methods to derivative pricing, understanding financial engineering principles, and implementing automated trading strategies. Students also gain experience with high-frequency trading concepts and market microstructure analysis.
This course examines the regulatory frameworks governing financial markets and corporate behavior. Students study banking law, securities regulation, and financial supervision mechanisms. The course addresses compliance requirements, ethical considerations, and regulatory impact on business operations.
Learning objectives include understanding financial regulatory structures, analyzing compliance frameworks, evaluating regulatory impact on business decisions, and developing knowledge of corporate governance principles. Students also examine case studies of regulatory failures and successful compliance strategies.
This course focuses on sophisticated financial modeling techniques and data analytics applications in modern finance. Students learn about advanced statistical methods, machine learning algorithms, and big data analytics for financial decision-making. The course emphasizes practical implementation of complex models using industry-standard software.
Learning objectives include mastering advanced financial modeling techniques, applying data analytics to financial problems, understanding predictive modeling approaches, and developing skills in financial data visualization. Students also gain experience with cloud computing platforms and distributed computing methods in finance.
This course provides comprehensive coverage of investment banking activities including underwriting, mergers and acquisitions, and capital structure decisions. Students learn about valuation techniques, financial modeling for corporate transactions, and regulatory aspects of investment banking. The course emphasizes practical applications in real-world financial scenarios.
Learning objectives include understanding investment banking processes, applying valuation methods, developing financial models for corporate transactions, and analyzing regulatory requirements. Students also gain insights into deal structuring, due diligence processes, and industry best practices in investment banking.
This course examines comprehensive risk management frameworks including market, credit, operational, and liquidity risks. Students learn about enterprise risk management concepts, risk measurement techniques, and regulatory compliance requirements. The course emphasizes practical implementation of risk management strategies in financial institutions.
Learning objectives include understanding risk identification and assessment methods, applying risk measurement models, developing risk management frameworks, and evaluating regulatory compliance requirements. Students also explore case studies of risk management failures and successful risk mitigation strategies.
The Finance program at The Institute Of Chartered Financial Analysts Of India University Ranchi embraces a robust project-based learning approach that bridges theoretical knowledge with practical application. This pedagogical philosophy recognizes that effective financial education requires students to engage with real-world problems and develop solutions through hands-on experience.
Mini-projects are introduced in the second year, allowing students to apply concepts learned in core courses to specific financial scenarios. These projects typically focus on financial statement analysis, market research, or basic valuation exercises. Students work individually or in small teams to complete these assignments, developing analytical skills and attention to detail.
The capstone project, undertaken in the final year, represents a comprehensive application of all learned concepts. Students select from a range of industry-relevant topics or propose their own research questions. These projects often involve collaboration with external organizations, providing students with exposure to real-world financial challenges.
Project selection process involves faculty mentorship and student preferences. Students participate in project proposal presentations and receive guidance on topic development and methodology. The evaluation criteria emphasize both technical quality and practical relevance of the work produced.
Faculty mentors play a crucial role in guiding students through their projects, providing expertise, resources, and feedback throughout the process. The program ensures that each student receives adequate supervision and support to successfully complete their project requirements.
