Excel and Python-Based Risk Management Program
Quant Market Risk Management
The Quant Market Risk Management (QMRM) Program is an advanced training program designed to equip professionals with in-depth knowledge, hands-on expertise, and quantitative techniques essential for managing financial market risks effectively. Offered by one of the most trusted platforms in financial education, this program bridges the gap between theoretical risk frameworks and real-world risk measurement, modeling, and automation techniques.​ Ideal for: Financial Risk Managers, Traders and Portfolio Managers, Financial Engineers, Quant Risk Analysts, Post-Grad Students, and Professionals preparing for roles in: Banks, Investment Firms, Asset Management Companies, Consulting Firms, Mutual Funds and Hedge Funds, and Other Financial Institutions
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HOURS ON-DEMAND
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QUANT RISK MODELS
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REAL-TIME PROJECTS
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4.9
BLOGS PUBLISHED
RATING ACHIEVED
What You'll Learn
Equities, Interest Rates, Modeling Systematic Risk, and Monitoring Yield Spreads: Market Data for Equities, Equity Shocks, Measuring Equity Risk, and Extreme Risk Analysis. Fixed-Income Markers, Yield Curve Interpretation, Interest Rate Shocks, Market Monitoring, and Reporting.​
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Market Data Management and Automation: Multi-Asset Market Data – Equities, Interest Rates, Currencies, Commodities, Cryptocurrencies, Including Derivatives, Understanding Derivative Instruments – Options, Futures, Forwards, and Swaps, and Python Automation for Market Data.​​​ Descriptive and Inferential Statistics, and Probability Distributions: Normal and Log-Normal Distributions.
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Modeling Term-Structure of Interest Rates: Yield Curve Construction, Basic and Advanced Interpolation Methods: Vandermonde Matrix, Newton's Divided Difference, Lagrange, Cubic Spline, Modeling Yield Curve using Nelson-Seigel (NS) and Nelson-Seigel-Svensson (NSS) Models, and Model Validation.
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Modeling Short-Rate and Interest Rate Factors: Stochastic Interest Rate Models – Vesicek Model, Cox-Ingersoll-Ross (CIR) Model, Hull-White Model, Backtesting Models, Introduction to Principal Component Analysis (PCA) for Interest Rate Modeling, PCA Modeling, and Reduced Model in Perspective.
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Modeling Volatilities, Volatility Skew, and Surfaces: Time-Series Modeling, Standard and Downside Standard Deviation, Exponential Weighted Moving Average (EWMA) Model, Maximum Likelihood Estimation (MLE) for Parameter Estimation, Generalized Autoregressive Conditional Heteroskedasticity (GARCH) Model. Volatility Skew and Surface Construction, Call-Put Implied Volatility Arbitrage.
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Stochastic Processes and Simulations: Introduction to Stochastic Processes and Simulations, Historical Simulation (HS) Method – Point and Path Estimation Techniques, Monte-Carlo Simulation (MCS) Method for Equities, and MCS Method Integrated with Vasicek and Cox-Ingersoll-Ross (CIR) Models.
Pricing and Valuation of Fixed-Income Securities:
Full Valuation DCF Model for US Treasury Securities, Corporate Bonds, IRS, FRAs, Swaptions, Mark-to-Market PnL Computation, Interest Rate Scenario Analysis and Sensitivities. Partial Revaluation Sensitivity-Based Model – Duration Approach (DV01), Duration-Convexity (DC) Approach, and Residual PnL, Bond Cashflow Mapping Procedure – Nearest Tenor Matching and Variance Matching Approach.​
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Pricing and Valuation of Derivative Instruments: Introduction to Pricing Equity Futures and Options, Cost of Carry Model, Binomial and Trinomial Models, BSM Model, Partial Revaluation Sensitivity-Based Model – DGV Approach, MCS for European, American, Asian, and Barrier Options. Valuation Models for IR Swaps, Swaptions, and Cross-Currency Rate Swaps.
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Sensitivity Analysis and Hedging Strategies:
Interest Rate Sensitivities – Duration, DV01, Convexity. DV01-Neutral Curve Spread Strategy. Option Greeks – Delta and Gamma, Vega, Volga, and Vanna, Theta, and Rho. Impact of Moneyness, Volatility, and Time-Decay on Option Greeks. Managing Directional and Volatility Risk with Delta-Gamma-Vega Hedging and Rebalancing. Delta-Gamma-Vega Risk Profiles for Long-Short Straddle and Strangle, Bull and Bear Spreads.
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Scenario Analysis and Stress Testing: Introduction, Equity Scenarios, Interest Rate Scenarios – Parallel, Non-Parallel Shifts – Bull-Bear Steepener and Flattener, and Regulatory Scenarios, Vol Scenarios. Scenario Creation Methodologies – Ladder-Based, Historical, Event-Specific, Hypothetical, and Antithetic, PCA Model Calibration and Scenario Generation. Scenario Revaluation and PnL Computation.
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Value-at-Risk, Stress Value-at-Risk, Expected Shortfall, and Advancements: Introduction, VaR, SVaR, IVaR, MVaR for Equities, Fixed-Income Securities (Bonds, IR Swaps), Option Derivatives with Historical, Variance-Covariance, Monte-Carlo Method, PCA Model for VaR. Stress Period Selection for Stressed VaR. Model Development and Validation through Backtesting & Stress Testing. Basel Regulations, FRTB.
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Premium Subscription
Quant Market Risk Management
reach out to us at contact@thefinanalytics.com
INR 20,000
USD 250
Subscription Info.:
Prerequisites: Python Basics
160+ hrs Duration (12 Months Access)
Live Sessions (Instructor-led Interactive) + Recordings
Recorded Sessions (Self-Paced)
25+ Hands-On Projects (Team Collaboration)
Supported Devices: Desktop, Laptop, iPad (Not Supported on
Mobile Devices)
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Program Coverage Curated By Experienced Mentors
We're focused on delivering practical skills to data science, data analytics, and finance professionals with an in-depth understanding & implementation using python. We never stop adding more content to it.
Introduction to Market Risk Management
→ Introduction to Market Risk Framework
→ Financial Products & Derivative Instruments - Underlying Risk Factors
→ Market Risk Model Performance Monitoring & Risk Monitoring Tactics - Standard Error | RMSE | Traffic Light | Limits | Flags | Thresholds → Market Risk Measurement Models & Management Tactics
→ Historical Time-Series of Equities & Equity Shocks - Absolute | Discrete Proportional | Continuous Proportional → Modeling - Equity Risk | Extreme Value Theory | Equity Return Distribution
→ Projects: Distributional Assumption for Equity Returns – Normality vs. Standardization | Applied Time-Series Models for Equity Risk – Simple vs. Exponential | Market Report: Monitor USD10Y3M Spread and S&P500
Introduction to Python Programming [7 Sessions]
Value-at-Risk Measurement Models
→ Value-at-Risk (VaR) Models - Historical Simulation Method | Monte-Carlo Simulation Method → Value-at-Risk (VaR) Models - Parametric Method → Downside Risk | Tail Risk | Conditional Value-at-Risk (CVaR | Expected Shortfall) → Stressed Value-at-Risk (SVaR), Incremental & Marginal Value-at-Risk (IVaR & MVaR)
→ Revaluation Approaches for VaR - Full Reval | Partial Reval - Taylor Approx. → Market Risk Model Validation through Backtesting VaR & ES Models → Exceptions/Breaches in VaR Limits/Flags/Thresholds → Overall Impact on Bank's Capital Adequacy Requirement
→ Model Validation through Backtesting | Traffic Light Approach
→ Projects: Equity Risk Assessment – Historical Simulation and Parametric Method
Sensitivity Analysis & Hedging Techniques
→ Market Risk Asset Classes - Equity | Interest Rate | Currency/FX | Commodity
→ Risk Sensitivities - Beta | Duration | DV01 | Convexity | Delta | Gamma | Vega | Theta | Rho | Vanna | Volga & Impact due to - Moneyness | Volatility | Time
→ Sensitivity-Based Models - Taylor Approximation | Ladder-Based Interpolation
→ Static/Dynamic Hedging & Rebalancing Techniques to remain Risk-Neutral - Delta | Gamma | Delta-Gamma | Vega | Delta-Vega → Multiple Risk Sensitivity Trades
→ Exceptions/Breaches in Sensi-Limits/Flags/Thresholds
Scenario Analysis & Stress Testing
→ Risks involved in Equities | Bonds | Options | Swaps → Identification of Risk Factors & Computation of Shocks - Absolute | Proportional → Scenario Generation & Expansion - Spot | Vol | SpotVol | Ladder → Scenario Types - Historical/Hypothetical | Event Specific
→ Scenario Analysis | Stress Testing - Scenario Creation for Identified Shocks - Spot Shocks [Positive | Negative | Antithetic] - Equity, Rates, FX, Commodity | Volatility Shocks - Normal/Local | Log-Normal/ATM Implied | Full Revaluation Model | Scenario Profit & Loss | Risk - EQ, IR, FX, COM | Cross Risk
→ Exceptions/Breaches in Scenario Limits/Flags/Thresholds
→ Management Action & Recommendations
Pricing & Valuation of Financial Instruments
→ Interest-Rate Bonds, IR Swaps - Discounting Cash Flow Model → Equity Futures, Forwards, FRAs - Cost of Carry Model → Equity, Rates, FX Option Derivatives - Binomial Model (Single-Period | Two-Period | Multi-Period) - Risk-Neutralization Approach | Delta-Hedging Approach | Replicating Portfolio Approach | Black-Scholes-Merton Option Pricing Model | Monte-Carlo Simulation - Point Estimation | Path Estimation
→ Full Revaluation vs. Partial Revaluation - Taylor Series Expansion/Approximation | Ladder-Based Interpolation Technique → Testing Option's Price under Put-Call Parity Theorem
→ Model Validation - Challenging Assumptions - Distributional, Constant Volatility, Interest Rate | Model Inputs & Model Formula
Modeling Volatilities & Interest Rates | Stochastic Processes & Simulation
→ Volatility Engines - Implied Volatility Smile & Smirk | Exponentially Weighted Moving Average (EWMA) | Generalized AutoRegressive Conditional Heteroskedasticity (GARCH 1,1) Model → Interest Rate Theories - IRR | Spot Rate | Forward Rate | Par Rate | Yield/IRCurve | Mechanics of Interest Rates - IRP | Cost of Carrying Model → Historical Time-Series of Interest Rates & Interest Rate Shocks - Absolute | Discrete Proportional | Continuous Proportional → Rates - Treasury | Agency | Municipals | Corporate → Stochastic Models - Historical Simulation | Monte-Carlo Simulation - Point & Path Estimation using Differential Equation → Yield Curve Construction - Linear Interpolation & Extrapolation | Bootstrapping | OLS Method for Interest Rates Modeling - Linear | Polynomial - Quadratic | Cubic Spline Piecewise | Quartic | Nelson-Siegel | Nelson-Siegel-Svensson
Market Risk Regulations
→ Minimum Capital Requirement for Market Risk
→ Risk Weighted Assets (RWA) & Components - Value at Risk (VaR) | Stressed VaR | Risk Not in VaR (RNIV) | Incremental Risk Charge (IRC)
→ Tier I & II Capital & Elimination of Tier III Capital in Basel Norms
→ Sensitivity-Based Approaches - Linear Risk | Volatility Risk | Curvature Risk
→ Standardised Approach (SA) for Market Risk → Internal Models Approach (IMA) for Market Risk
→ Understanding of Fundamental Review of Trading Book (FRTB) Standards and Modeling
→ Understanding of Basel Regulations - Accord I, II, III and Modeling