Designed for Finance Professionals
The Fixed-Income Investments and Risk Management (FIRM) Program is an advanced training program designed to equip professionals with in-depth knowledge, hands-on expertise, and quantitative techniques essential for managing fixed-income investments and risks. This program bridges the gap between theoretical frameworks and practical investment and risk modeling.​ Each module is carefully curated to build a deep, layered understanding, from core financial concepts to advanced performance and risk metrics and management tactics.
What You'll Learn
Equities form a core component of financial markets, and understanding their risks is fundamental for market risk management. This module introduces equity market data, return calculations, and risk modeling techniques, covering both systematic and unsystematic risk factors.
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Hands-On Application: Develop Python-based models to compute equity risk metrics, visualize return distributions, and analyze historical market shocks.
Interest rates influence financial markets, corporate financing, and investment decisions. This module covers yield curves, interest rate shocks, and the impact of changing interest rates on market risk.
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Hands-On Application: Build automated market reports that monitor yield spread and SnP 500 equity market performance, using Python to extract, process, visualize, and generate reports.
Efficient market risk management relies on high-quality market data across multiple asset classes. This module introduces financial data extraction, automation, and real-time monitoring techniques.
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Hands-On Application: Implement Python-based automation to streamline market data workflows, visualize price trends, and create dynamic dashboards for risk monitoring.
Understanding the term structure of interest rates is crucial for pricing fixed-income securities, managing interest rate risk, and constructing yield curves for scenario creation. This module introduces interpolation techniques used to construct smooth and continuous yield curves, regression models for yield curve estimation (including linear and polynomial regressions), and advanced factor-based models such as the Nelson-Seigel and Nelson-Seigel-Svensson models needed for accurate interest rate modeling and forecasting.
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Hands-On Application: Implement yield curve modeling techniques, calibrate model parameters using real-world market data, and validate their predictive accuracy.
Interest rates are the primary driver of financial portfolios, influencing bond pricing, derivatives valuation, and risk management strategies. This module introduces short-rate models and principal component analysis (PCA), key techniques for modeling interest rate dynamics (level, slope, and curvature) and understanding market risk factors.
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Implement and calibrate Vasicek and CIR models using historical interest rate data, simulate interest rate paths, and compare model accuracy in forecasting yield curve dynamics.
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Perform PCA on yield curve data, analyze historical interest rate movements, and use PCA-based shock modeling to simulate interest rate stress scenarios.
Fixed-income securities are the most traded and concentrated in the financial markets. This module provides a comprehensive framework for pricing and valuing bonds and interest rate swaps, covering discounting cash flow (DCF) modeling, interest rate sensitivities, and scenario analysis techniques.
Interest rate swaps and options (swaptions) are crucial in hedging risk, managing yield curve exposures, and structuring fixed-income portfolios. This module also covers swap pricing models and option-based valuation approaches.
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Valuation Report of US Treasury Securities and Mark-to-Market: Construct a comprehensive valuation report, summarizing bond pricing methodologies and market risk assessments, conduct interest rate risk assessments, and prepare mark-to-market valuation reports using real market data.
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Implement pricing models for interest rate swaps and swaptions, calibrate Black’s model for swaption pricing, and develop risk reports for swap exposures.
Risk sensitivity analysis is a cornerstone of market risk management, allowing traders and risk managers to quantify portfolio risk exposure, optimize hedging strategies (as option positions are influenced by multiple risk factors, including price movements, volatility shifts, and time decay), and mitigate financial risks. This module focuses on fixed-income risk sensitivities (Duration, DV01, and Convexity) and advanced hedging techniques for interest rates and spreads.
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Hedging strategies allow traders and risk managers to neutralize market exposures while optimizing capital efficiency.​ ​Understanding risk profiles across different trading strategies is essential for managing exposure effectively. This module also covers practical approaches to risk mitigation and the risk-return characteristics of complex portfolio structures.
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Scenario analysis and stress testing are essential risk management techniques that evaluate a portfolio's resilience under extreme market conditions. This module focuses on designing market stress scenarios, asset prices, interest rate, exchange rate shifts, regulatory stress test methodologies to asses the impact of adverse conditions on fixed-income portfolios.​ This module expands on scenario generation techniques and introduces advanced methodologies for stress-testing fixed-income portfolios.
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Value-at-Risk (VaR) is a fundamental risk measure used by financial institutions to quantify potential losses under adverse market conditions. This module provides a comprehensive exploration of VaR, stress VaR, Expected Shortfall (ES), and risk model validation techniques. Participants will gain hands-on experience in historical simulation, parametric VaR, Monte Carlo simulations, and PCA-based risk estimation for bonds, bond futures, interest rate options, and swaps.
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Expected Shortfall (ES) provides a more accurate measure of tail risk, capturing average losses beyond VaR estimates. Stressed VaR measures risk under extreme historical market conditions, helping financial institutions prepare for black swan events and crisis scenarios.
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Model validation is crucial for ensuring accuracy, robustness, and compliance in risk management frameworks. This module also covers backtesting, stress testing, and other model validation techniques.
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Compute duration, DV01, and convexity for bond portfolios, implement yield curve strategies, and construct hedged fixed-income positions. Construct Delta-neutral portfolios, rebalance Gamma hedging strategies, and evaluate the impact of volatility shifts on interest rate Vega risk. Model profit/loss distributions, assess risk profile shifts across different market regimes, and optimize hedging techniques for structured option positions.
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Build stress-testing models for fixed income, simulate parallel and non-parallel yield curve shifts, and evaluate portfolio resilience using regulatory stress test cases. Design custom market stress scenarios, implement PCA-based interest rate shocks, and generate scenario-driven PnL reports for risk assessment.
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Market Value-at-Risk Report for Fixed-Income Securities and Portfolio: Generate a structured risk report summarizing VaR-based risk assessments for bond portfolios. Compute VaR across asset classes, calibrate PCA models for fixed-income risk, and analyze incremental and marginal VaR for portfolio optimization. Compute CVaR for multi-asset portfolios, compare VaR vs. Expected Shortfall performance, and analyze tail risk distributions. Develop stressed VaR models, analyze historical crisis periods, and simulate black swan events for portfolio risk assessments.
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Market Risk Validation Report: Backtesting and Stress Testing Risk Methodologies – Investment Portfolio: Generate a comprehensive model validation report, summarizing key risk methodologies, backtesting results, and stress testing outcomes.
Subscription
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Professional Plan
12,000 INR
100% Refund (No Questions Asked) within 2 hours of subscription.