Market Risk Management (MRM) Strategies for Success

From Fundamentals to Advanced Practices, Market Risk Analytics, Governance, Tools, Models, and Applications in MRM.

Description

This is Unofficial Course.

This course is a comprehensive journey into the world of market risk management, designed to equip learners with both the theoretical foundations and practical tools used by risk professionals in banks, investment firms, and regulatory environments. It begins with the core question of what market risk is, exploring its various types such as interest rate risk, foreign exchange risk, equity risk, commodity risk, and volatility risk, along with the instruments and trading activities that generate these exposures.

From there, it builds a solid foundation in statistical and mathematical concepts such as returns, distributions, variance, volatility, covariance, and correlation, explaining how risks aggregate across instruments and why diversification is both a strength and a limitation when correlations break down.

The course then dives deeply into the central methodologies of risk measurement, with a detailed exploration of Value at Risk (VaR) and its different calculation approaches including parametric, historical simulation, and Monte Carlo methods. It also covers the important concept of Expected Shortfall, highlighting its advantages as a coherent risk measure and its growing role in regulatory frameworks.

Alongside this, learners will gain a strong grasp of volatility estimation techniques, time-series modeling with ARCH and GARCH families, and the implications of heavy-tailed return distributions on tail risk.

Building on this quantitative foundation, the course introduces derivatives and options as key sources of market risk, explaining option payoffs and moneyness before moving to the Greeks—delta, gamma, vega, theta, and rho—as essential tools for measuring sensitivities and managing nonlinear risk exposures.

Learners will understand how to apply linear and quadratic approximations to portfolio risk, as well as the limitations of such methods under stress.

A full module is dedicated to stress testing and scenario analysis, showing how firms design, implement, and interpret both historical and hypothetical scenarios, as well as how reverse stress tests uncover vulnerabilities that traditional models may miss.

The course then addresses backtesting, model validation, and model risk management, ensuring learners understand how to evaluate model performance, govern their use, and mitigate inherent limitations.

Governance and regulatory perspectives are emphasized throughout, with dedicated attention to how firms establish risk appetite, policies, limits, and escalation frameworks. The course also examines the role of Basel regulations, regulatory capital requirements, and the distinction between regulatory and economic capital in decision-making and risk-adjusted performance measurement.

Finally, the course focuses on reporting and practical applications, including how effective risk reports and KPIs are structured, how daily P&L explain processes reveal risk drivers, and how market risk interacts with liquidity risk during stressed conditions.

It concludes by addressing emerging issues such as valuation adjustments (XVA), margining requirements, and counterparty exposures that are becoming increasingly central to risk management practice.

By the end of the course, learners will have mastered the language, tools, and frameworks of market risk management, gaining the confidence to interpret risk metrics, challenge assumptions, communicate effectively with senior stakeholders, and apply best practices in both day-to-day risk oversight and strategic decision-making.

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