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Last date of admission: 26th Sep
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Semester 1
Microeconomics
Learners examine consumer behaviour, production and cost analysis, market structures, factor pricing, and welfare economics, with a focus on their applications in the digital economy and financial decision-making.
Programming with R and Python
This subject introduces programming fundamentals in R and Python while developing skills in data manipulation, visualisation, statistical computing, financial data analysis, forecasting, and introductory machine learning for finance.
Business Statistics
This subject introduces statistical concepts and methods used in business and financial analysis. Learners develop skills to analyse data, identify trends, interpret results, and support informed business and economic decisions.
Corporate Finance
The subject covers key areas of corporate finance, including the time value of money, cost of capital, leverage, capital budgeting, working capital management, and dividend decisions, with an emphasis on value maximisation strategies.
Financial Reporting & Statement Analysis
Learners gain knowledge of accounting processes and financial statement preparation while developing the ability to analyse assets, liabilities, cash flows, financial ratios, performance, and financial risk.
Semester 2
Macroeconomics
This subject examines national income, inflation, unemployment, monetary and fiscal policies, exchange rates, and business cycles, while considering contemporary macroeconomic factors influencing financial markets.
Business Econometrics
Learners apply regression analysis, model diagnostics, hypothesis testing, and forecasting techniques to analyse business and financial data and support informed decision-making.
International Financial Management
The subject develops an understanding of foreign exchange markets, exchange rate determination, currency exposure, country risk, and financial management strategies for multinational organisations.
Investment Analysis and Portfolio Management
Learners explore security analysis, portfolio theory, CAPM, market efficiency, mutual funds, bond analysis, and techniques for evaluating portfolio performance
Research Methodology
This subject develops research capabilities through research design, sampling, data collection, statistical analysis, literature review, academic writing, research ethics, and proposal development
Skill Lab I
Learners gain hands-on experience with spreadsheets, dashboards, financial databases, visualisation tools, presentations, and industry-oriented analytical assignments.
Semester 3
Banking and Financial Services
Learners explore banking operations, credit appraisal, financial services, Basel regulations, digital banking, UPI, artificial intelligence applications in banking, and financial inclusion
Financial Econometrics
This subject introduces econometric methods for analysing financial and economic data. Learners explore statistical models and techniques to understand financial relationships, analyse market trends, and support data-driven financial decisions.
Fixed Income Securities
Learners develop an understanding of bond valuation, yield analysis, duration, convexity, credit risk, fixed-income derivatives, and debt portfolio management
Behavioral Finance
The subject examines the influence of cognitive and emotional biases on financial decisions, alongside investor psychology, behavioural portfolio management, market anomalies, and digital investing behaviour
Financial Risk Management
Learners study market, credit, liquidity, and operational risks while exploring VaR, stress testing, hedging, enterprise risk management, and AI-driven approaches to risk analytics.
Skill Lab II
Practical sessions enable learners to apply financial modelling, dashboard development, business intelligence, analytical reporting, teamwork, and professional communication skills.
Semester 4
Time Series Analysis
Learners study trends, seasonal patterns, exponential smoothing, ARIMA, and forecasting accuracy to develop the skills required for analysing and forecasting financial time series
FinTech - Emerging Technologies in Finance
This subject explores emerging technologies transforming the financial sector, including blockchain, AI, open banking, embedded finance, digital lending, WealthTech, InsurTech, CBDCs, DeFi, and FinTech regulation
Financial Analytics
Learners apply financial analytics techniques to accounting, securities, volatility, portfolios, forecasting, scenario analysis, and credit risk to generate meaningful financial insights
Financial Derivatives
The subject introduces futures, options, swaps, hedging strategies, the Black-Scholes model, and Greeks, with emphasis on the application of derivatives in financial risk management
Financial Modeling
Learners develop practical financial modelling skills through Excel-based valuation, three-statement modelling, DCF, project finance, portfolio optimisation, VaR, and R-based financial modelling
Capstone Project
The capstone enables learners to undertake a faculty-guided research or industry project that integrates finance, economics, analytics, technology, reporting, and professional presentation skills
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