Financial Risk Management – Level 2

Explore credit risk fundamentals, including settlement risk and financial obligation, and learn credit analysis across individuals and various entities, using PD, LGD, and EAD to compute expected loss.

Explore the credit risk process by examining four components—willingness and capacity, external environment, instrument characteristics, and risk mitigants—and the qualitative and quantitative methods across consumers and corporates.

Estimate PD, LGD, and EAD to compute expected loss (PD × LGD × EAD) and relate rating from triple A to D, time horizon, and collateral recovery to credit risk.

Compute expected loss from PD, LGD, and EAD using practical examples, including recovery rate and exposure at default, and explore how the PD and LGD correlation affects loan pricing.

Explore how bank insolvency stems from illiquidity caused by a liquidity mismatch in a specific maturity bucket, where liabilities exceed assets; regulators provide liquidity, and credit analysis rates insolvency severity.

Discover the roles and tasks of a credit analyst, mastery of quantitative and qualitative skills, and key information sources for robust credit analysis, including a camel rating model for banks.

Explore the universe of credit risk by examining corporate, small business, consumer, financial institution, sovereign, and structured finance analyses, focusing on external and internal risks, and rating models.

Explore the varied roles of credit analysts across consumer, corporate, and counterparty analysis, and how buy-side, sell-side, and rating models shape lending decisions.

Assess counterparty credit risk through reviews and recommend credit limits; present to credit committee with Basel norms and risk mitigants. Analyze fixed income and equity for buy, sell, or hold.

Explain bank credit risk analysis by dividing into quantitative and qualitative skills, covering statement analysis, ratios, macro factors, and collateral evaluation. Assess capacity, willingness, and default implications through these skills.

Identify key sources for credit analysis: annual reports (income statement, balance sheet, cash flow), md&a, investor presentations, press releases, rating agency and third-party research, and credit modeling tools.

Learn how audit reports provide independent opinions on the bank's financial statements, including unqualified, qualified, and adverse, and how analysts read between the lines to detect fraud or misrepresentation.

Explore the Camel framework for bank credit risk, evaluating capital adequacy, asset quality, management, earnings, and liquidity to assess risk and guide valuation.

Explore the concept of economic capital, examining credit risk from borrower default or rating migration and how expected and unexpected losses guide capital requirements via confidence intervals and asset risk.

Explore capital calculation by detailing probability of default, loss given default, and exposure at default, and show how expected loss (PD×LGD×EAD) and unexpected loss (standard deviation around EL) are estimated.

Explore how banks determine capital structure by assessing economic capital against credit risk, and learn to calculate expected and unexpected losses and translate them into economic capital.

Calculate expected loss and unexpected loss for a loan, deriving pd and lgd variance and estimating ead to compare ul with el.

Compute the portfolio's expected loss from PD, LGD, and EAD for assets A and B, then determine the unexpected loss and risk contribution using the asset correlation.

Explore how unexpected loss translates into economic capital by decomposing standalone UL, portfolio UL, and diversification effects, including the role of correlation and risk contributions.

Explore counterparty credit risk, its differences from lending risk, and key terminologies. Learn Basel III concepts, CVA, bilateral netting, close-out clauses, and practical risk management techniques.

Explore counterparty risk in otc derivatives and related transactions, where either party may default, focusing on pre-settlement and settlement risks and their bilateral exposure.

Examine how counterparty risk surfaces in over-the-counter derivatives like interest rate swaps, forwards, and credit default swaps, with netting and wrong-way risk as mitigation.

Explore how counterparty risk arises in securities financing transactions, with repos and reverse repos, collateral, haircuts, and the flow of cash and securities, and the role of the repo rate.

Examine counterparty risk terminology, including exposure, mark-to-market, and notional, and how positive or negative MTM in FX contracts leads to loss at default. Assess LGD, recovery, and exposure at default.

Explore how to manage counterparty risk through high quality counterparties, cross product netting and mtm, close-out clauses, centralized clearing, collateralization, and hedging considerations.

Explore how banks manage capital structure, measure credit risk, and calculate economic capital, expected loss, and unexpected loss, while assessing portfolio risk contributions under Basel norms.

Assess the probability of default as a key credit risk factor, explaining default risk, recovery risk, exposure risk, migration risk, spread risk, and liquidity risk.

Explore exposure amount and exposure at default, using outstanding loans as examples, and relate loss rate, probability of default, and recovery rate to estimate expected and unexpected losses.

Learn to compute expected loss as exposure amount times probability of default and loss rate, and explore unexpected loss and credit migration with simple models like the Merton model.

Compute portfolio expected loss by summing individual expected losses and assess portfolio unexpected loss via risk contributions and correlations. Analyze diversifiable and undiversifiable risk, and how correlation affects concentration risk.

Explore how to compute portfolio expected loss and unexpected loss using an Excel sheet with two assets, showing how exposure, probability of default, loss rate, and correlation drive risk.

Compute economic capital as the excess over expected loss to cover unexpected credit losses. Model credit risk with beta distributions and Monte Carlo to capture tail losses and limitations.

Explore rating assignment methodologies, including default probability, and how issuers are rated using quantitative and heuristic approaches.

Explore how a rating system supports credit risk management, pricing, and capital provision by assessing default probability, using objective, homogeneous, and specific measures backed by measurable variability.

Explore three risk assessment approaches—expert-based, statistical, and numerical—using qualitative and quantitative variables to assess default risk and adapt to market changes with neural networks.

Learn how rating migration matrices quantify how often ratings move between classes, estimate default risk with probability of default and related measures, and assess matrix accuracy and limitations.

Explore rating agencies methodologies, blending judgment and model-based analysis, the eight-step rating process, and how privileged information supports assessing issuer risk and credit quality.

Explore how rating agencies determine issuer and instrument ratings through integrated methodologies, emphasizing probability of default, agency versus expert-based approaches, and the role of structural and reduced form approaches.

Compare structural and reduced form approaches, from Merton and Black-Scholes to distance-to-default and metamodels, for estimating default probability in credit risk.

Learn how linear discriminant analysis builds scoring models to separate solvent and insolvent firms, using z-scores, calibration, and cutoff thresholds to assess credit risk.

Explore logit regression models to predict default and link dependent and independent variables through a non-linear probability function, with cluster and principal component analyses for segmentation.

Explore cash flow simulation models that rate firms with minimal track records by forecasting pro forma cash flows across scenarios, assessing default probability and model risk.

Define counterparty risk and its distinction from lending risk, outline key terms, and identify market players. Learn how to manage, mitigate, and quantify credit exposure in derivatives and settlement.

Explain counterparty risk in financial transactions, highlighting minimal risk in exchange-traded derivatives, and describe repos, reverse repos, securities lending and borrowing, and short selling with practical India constraints.

Explore repo and reverse repo concepts as short-term, collateral-backed lending agreements, detailing fees, haircut, repo rate, collateral types, and counterparty risk in secured financing.

Explore securities lending and borrowing, contract termination fees, and over-the-counter derivatives—interest rate swaps, foreign exchange forwards, and credit default swaps, with focus on counterparty risk and netting.

Identify large, medium, and small counterparty risk players in OTC markets and how collateral and clearing services reduce exposure. Learn terms like credit exposure, default probability, recovery, and mark-to-market exposure.

Learn to manage, mitigate, and quantify counterparty risk by using high quality counterparties, cross product netting, collateralization, and diversification, with close-out and walkaway protections.

Explore mitigating counterparty risk through netting, collateralization, hedging, and central counterparties, and learn to quantify risk with CVA and Xva terms across trade, counterparty, and portfolio levels.

Examine netting and close-out procedures, including unilateral, bilateral, and multilateral netting; compare payment netting (set-off) with closeout netting, and explore the ISDA master agreement standardizing OTC terms and collateral.

Explore how netting offsets multiple trades to cut exposure, reduce collateral needs, and unwind positions while lowering counterparty risk, using close-out netting under ISDA master agreements.

examine multilateral netting across multiple counterparties using central counterparties or exchanges, weighing risk reduction against added costs, disclosure needs, and collateral implications.

Explore termination features in credit risk management, including reset agreements, additional termination events or break clauses, and walk-away clauses, plus how netting and trade compression reduce exposure.

Explain wrong-way risk and its contrast with right-way risk, where exposure and counterparty creditworthiness move together during macroeconomic events, with examples from bonds and instruments like options, swaps, and CDS.

Explain wrong-way risk and right-way risk, and how they influence CVA, DBA, exposure, and counterparty default probability.

Illustrates wrong-way and right-way risk in collateral agreements, exposure, and counterparty default. Demonstrates how credit value adjustment reflects exposure and counterparty default probability, using options and otc structures.

Explain credit default swaps as protection against default and illustrate wrong-way risk via the 2007–2009 crisis, concentration risk in mortgage-backed securities, and currency swaps, contrasted with right-way risk.

Explore how wrong-way risk rises with counterparty exposure in interest rate swaps and commodity hedges, and how collateral and CCP structures mitigate or amplify risk.

Explore securitization and credit risk mitigation, including the originate-to-distribute model and credit derivatives. Understand flaws in securitization that contributed to crises and how risk transfer works.

This analysis of flaws in securitization, including wrong ratings by rating agencies, the originate-to-distribute model, opaqueness of multi-layer securitized products, and SIVs rolling short-term debt, with credit risk mitigation insights.

Explore credit risk mitigation techniques, including bond insurance, collateralization, termination and reassignment, netting, marking to market, loan syndication, and their impact on bank credit functions.

Originate to distribute model transfers credit risk, improves capital efficiency, and expands access to credit, while a credit portfolio management group monitors risk concentration.

Credit derivatives unbundle and transfer credit risk from assets to other parties without selling them. Credit default swaps act as customizable insurance, enabling risk management or speculation through specified payments.

Explore credit derivatives such as credit default swaps, forced default puts, and total return swaps, illustrating counterparty risk, default correlation, and protection mechanics through a four-bond bank portfolio.

Explain asset backed credit linked notes and how they embed default swap into debt tied to underlying asset. Describe securitization via spv and cash waterfall across senior, mezzanine, and equity.

Explore credit securitization, including cash CDOs, synthetic CDOs, and asset-backed securities. Learn about collateralized loan obligations, senior and equity tranches, and risk transfer through originators and SPVs.

Learn how collateral underpins credit risk, mastering collateral types, the credit support annex, and ISDA frameworks, while examining margins, disputes, and market, operational, and liquidity risks.

Explore key risk parameters, including thresholds, initial and maintenance margins, collateral concepts, rounding, haircuts, and valuation agents to manage credit exposure in derivatives.

Understand various collateral types, from cash to equities, and how collateral agreements set eligibility, delivery, margin calls, and mark-to-market terms. Learn dispute resolution, reconciliation, and risk management across regions.

Explore collateral features in CSA agreements, including thresholds, initial margins, minimum transferable amounts, rounding, and haircuts, and learn how these terms manage credit risk and margining practices.

Analyze collateral concepts including haircut, substitution, rehypothecation, and segregation, and compare CSI agreements with two-way and one-way CSAs, linking collateral terms to credit quality.

Explain wrong-way and right-way risk in collateral agreements, linking exposure and counterparty default probability to credit value adjusted, with options and over-the-counter examples.

Understand how counterparty risk is mitigated through central counterparty structures, loss waterfall, multilateral netting, collateralization, and the role of special purpose vehicles in securitization.

Special purpose vehicles, bankruptcy-remote, isolate assets from the originator, transferring risk off balance sheet and repackaging assets into structured notes or CDOs sold to investors.

Mitigates bilateral credit risk in the over-the-counter derivative market as a central counterparty intermediary. Enhances multilateral netting, collateral management, and novation to reduce domino effects.

Explore the CCP risk management process, detailing the loss waterfall, collateral, default funds, and rights of assessment, and compare bilateral trades with centrally cleared OTC derivatives.

Analyze CCP advantages such as transparency, multilateral netting, and liquidity, alongside disadvantages like moral hazard and procyclicality, and examine central clearing's impact on CVA, FVA, KVA, and margin costs.

Explore retail banking risk and credit scoring, compare with corporate lending, examine scoring models and mortgage factors, and understand risk-based pricing for lender profitability.

Explore reputation risk, interest rate risk, and asset valuation risk in banking, compare retail and corporate credit risk, and examine regulation, qualified mortgages, and the ability to repay loans.

Learn credit risk scoring models, including credit bureau scores and custom models, that convert applicant data into scores predicting probability of default, exposure at default, and loss given default.

Examine how lenders assess creditworthiness through mortgage criteria, including FICO score, loan-to-value, debt-to-income, payment type, documentation, cut-off scores, Basel norms, and scorecard performance.

Explore how lenders balance creditworthiness with profitability using scorecards such as revenue, application, response, and behavior scores, and apply risk based pricing to optimize profitability and market share.

Explore the evolution of counterparty credit risk through stress testing, covering current exposure, peak exposure, expected exposure, expected positive exposure, CVA, DVA, and wrongway risk.

Master counterparty credit risk and stress testing by balancing credit risk with market risk, monitoring, risk mitigation, understanding collateral agreements, default handling, and current exposure scenarios.

Stress test expected loss for loan and derivative portfolios by varying probability of default, exposure at default, and loss given default, while considering macroeconomic variables.

Explore stress testing of counterparty credit risk within market risk, covering unilateral and bilateral CVA, DBA, and how expected exposure and default probabilities are stressed.

Explore credit value adjustment (CVA) to price counterparty risk, using exposure, default probability, and loss given default, including incremental and marginal CVA, bilateral contracts, netting, collateralization, and CVA spread.

Analyze how incremental and marginal CVA account for netting and collateral, quantify changes in exposure, and convert CVA to running spreads, including bilateral CVA and DBA considerations.

Analyze portfolio credit risk through default correlation, single-factor and copula models, and their impact on VaR, diversification, and the limitations of correlation-based frameworks.

Explore conditional default probabilities and credit var using single-factor models and copulas, highlighting conditional independence, distance to default, and distribution parameters.

Explore credit var with copulas, extending single-factor models to capture default correlations, using threshold, beta, and market factor, and compare loss distributions via simulation.

Explore securitization basics, including selling cash flows to an SPV and converting loans into securities. Learn about tranche structures, mortgage-backed securities, credit enhancements, and risk transfer.

Explore the securitization process, transforming illiquid assets into asset-backed or mortgage-backed securities via SPV, true sale, and credit enhancement, with roles of originator, issuer, and trustee.

Explore the cash waterfall in securitization, detailing senior, mezzanine, and equity tranches, overcollateralization, first loss piece, and SPV master trusts with amortizing and revolving structures.

Explore how a master trust SPV enables multiple asset-backed securities from a single credit card pool by using a grantor trust SPV, with excess spread to service tranches.

Explore securitization benefits for financial institutions and investors, including funding assets, balance sheet management, risk transfer through SPV-backed ABS, and enhanced diversification.

Explore credit enhancements in asset-backed securitization, including overcollateralization, pool insurance, subordinated note classes, margin setup, and excess spread, which either increase loss-absorption or control cash flows.

Explore performance measures for securitization structures, including auto loan loss curves and absolute prepayment speed, and credit card delinquency, default, and monthly prepayment rate tools.

Learn the key securitization structure ratios, including dscr, dcr, wac, wam, wal, cpr, and prepayment concepts, and how they govern cash waterfalls, risk, and investor payoffs.

Examine seven frictions in subprime mortgage securitization, including moral hazard, adverse selection, predatory lending and borrowing, across originators, arrangers, rating agencies, and investors.

Explains seven frictions in subprime mortgage securitization, from arranger and third parties to servicer and rating agencies. Shows how adverse selection and moral hazard drive risk and require due diligence.

Study credit risk and credit derivatives, price risky debt with the Merton model, and assess portfolio credit risk and credit value at risk to hedge exposure.

Explore credit spreads as the yield gap between risky and risk-free bonds, and examine subordinated debt’s role between equity and debt.

Compare native and meta credit risk models, including distance to default and Merton's framework, with credit risk portfolio approaches, var, and macroeconomic driven Moody's KMV and portfolio view.

Learn how credit derivatives hedge credit risk with over-the-counter instruments like credit default put and credit default swaps, transferring risk on events such as bankruptcy, default, or restructuring.

Explore spread conventions, hazard rates, and default models, including yield spreads, i-spread, z-spread, asset swap spread, credit default swap spread, and option-adjusted spread, and their impact on pricing.

Explore structured credit risk by examining common structured products, securitization, waterfall tranches, credit enhancements such as overcollateralization and excess spread, and the impact of default probability and correlation.

Explain how increasing correlation affects tranche values, with equity rising and mezzanine or senior shifting with default rate, and highlight convexity in securitization.

Explore credit exposure concepts like potential future exposure and credit exposure matrix, and examine how payment frequencies, exercise dates, netting, collateral attributes, and Basel II timing rules affect risk management.

Explore potential future exposure across bonds, FX, rate products, and options, noting PFE curves and how collateral, margin calls, and risk neutral vs real measures shape exposure.

Explore practical Excel techniques to value equity and debt using the metal model, calculating firm value, equity, and debt from given inputs with D value, normal distribution, and risk-free rate.

Compute credit spreads, probability of default, and cumulative probability of default using hazard rate, plus loss given default, in Excel; analyze netting and expected versus potential future exposure.

Explore liquidity risk principles, funding models, cash flow modeling, and stress testing. Differentiate solvency from liquidity, and examine cost of liquidation with liquidity-adjusted VaR.

Analyze the Northern Rock Bank case to illustrate liquidity risk, market stress, and the need for Basel III liquidity measures like LCR and NSFR, plus risk governance and reporting.

Explore how traders create liquidity stress through negative and positive feedback loops, leverage, and margin calls, illustrated by the 1987 crash and funding implications for banks.

Explore how fractional reserve banking and leverage heighten commercial bank fragility under stressed market conditions. Examine off-balance sheet funding, SPVs, collateral, haircuts, repos, and related liquidity risks.

Monitor liquidity risk with early warning indicators such as asset and liability concentration, currency mismatch, and cost of debt, guided by the merit framework from Basel and regulators.

Use forward-looking bias to assess liquidity risk with near-term to one-year projections. Dashboards flag red or orange breaches from credit, market, rates, and collateral indicators.

An investment manager links assets and liabilities to stabilize income, balance liquidity, and manage risk via long- and short-term securities while supporting regulatory requirements and diversification.

Explore money market and capital market instruments—from treasury bills and munis to corporate bonds, asset-backed securities, structured notes, and strips—and how yield, liquidity, and risk shape bank portfolios.

Explore how interest rate expectations drive investment maturity strategies: ladder, front load, back load, and barbell, to balance liquidity, risk, and returns in bank portfolios.

Learn carry trade and riding the yield curve to enhance returns, then master duration matching, cash flow matching, and immunization to hedge portfolio value and liquidity.

Examine factors shaping a bank’s net liquidity position by analyzing liquidity supply and demand, time and urgency dimensions, and approaches like asset conversion, borrowed liquidity, and balanced strategies.

Estimate liquidity needs by analyzing sources and uses of funds, including loan changes, money supply, deposits, inflation, and trend, seasonal, and cyclical components shaping net liquidity.

Learn the structure of funds approach to liquidity management, splitting funds into hot money, vulnerable, and stable deposits, and using scenario-based, probability-weighted liquidity estimates.

Apply liquidity indicator approach to assess bank liquidity using ratios such as cash position, liquid securities, net federal funds and repo position, capacity, core deposits, loan commitments, with tailored thresholds.

Analyze marketplace signals to assess bank liquidity, including stock price trends, public confidence, risk premiums, asset sales, central bank borrowings, and lagged reserve accounting.

Explore intraday liquidity and how banks borrow from the central bank to cover day-end payable or receivable positions. Understand its impact on opportunity cost, overdrafts, nostro accounts, and settlements.

Navigate intraday liquidity governance by forecasting cash balances, client inflows, and intraday credit, and apply Basel stress scenarios to manage day-of funding risk.

Monitor intraday liquidity by tracking inflows and outflows across 1–14, 15–28, 29–90, and 90–180 day buckets to assess liquidity risk and funding costs.

Dealer banks act as intermediaries in securities and derivatives, providing liquidity, underwriting, prime brokerage, asset custody, and repo-based financing, with risks from liquidity crunches and perceived counterparty risk.

Learn how dealer banks mitigate counterparty risk through hedging, immunization, and central clearing while examining the right to offset, insurance limits, and the lender of last resort during crises.

Learn Basel's four liquidity stress scenarios and classify funding into operational, contingent, restricted, and strategic funds, then apply a 12-month stress testing framework using cash flow at risk methods.

Learn liquidity stress testing techniques across baseline, historical, and hypothetical scenarios to determine buffers, funding optimization, and governance reporting for banks.

Align a customized contingency funding plan with the bank's risk profile to support liquidity under stress. Integrate this CFP with liquidity stress testing, governance, scenarios, and stakeholder escalation.

The session introduces risk management and investment management for the frm part 2 exam. It covers book structure, theory and Excel practice with topics like factor theory, Capm, and alpha.

Study illiquid assets, the imperfections that encourage illiquidity, biases that inflate returns, and four ways to harvest the illiquidity premium, plus how to evaluate inclusion and risk in portfolio construction.

Explore risk monitoring and performance measurement, defining VaR and tracking error, risk budgeting, liquidity considerations, and the tools for evaluating portfolio performance using Sharpe, Jensen, Treynor, information ratio, and attribution.

Explore hedge funds, examine performance, compare with mutual funds, and analyze alpha and beta across strategies and institutional growth.

Explain mutual funds and hedge funds: mutual funds welcome all investors, avoid long/short strategies; hedge funds target investors, use leverage, and charge 2% plus 20% with high watermark.

Compare hedge funds to mutual funds as private, leveraged investments with a 2% management fee and 20% performance payout, and examine selection bias, self-reporting bias, and data challenges shaping performance.

Examine how hedge funds grew from 190 billion to 1.3 trillion (1999–2007) and how alpha-beta separation guides managers to pursue alpha while controlling beta with risk tools, benchmarks, and derivatives.

Explore hedge fund performance, uncovering persistent alpha, low exposure to stocks and bonds, and the creation of hedge fund indices; analyze diversification risks during crises like Covid-19 and 2008.

Explore risk sharing asymmetry in hedge funds, examining how compensation, incentives, and reputation shape managers' risk-taking during crises and the impact of institutional capital.

Analyze hedge fund strategies, including managed futures and global macro, merger arbitrage, distressed, fixed income arbitrage, volatility trading, and convertible arbitrage, with lookback options and trend-following bets.

Understand long–short equity funds that balance long and short positions with futures and options to capture market directions. Explore emerging markets and zero beta equity market neutral strategies.

Explain illiquid assets and illiquid asset markets, outlining four characteristics: illiquidity in most asset classes, large markets for illiquid assets, widespread illiquid holdings, and liquidity drying up in crises.

Explore market imperfections that drive illiquidity, including participation costs, transaction costs, search friction, asymmetric information, price impacts, and funding constraints, with real estate as a key example.

Examine how illiquid asset returns can be distorted by survivorship, selection bias, and infrequent trading, with reporting bias inflating observed performance.

Examine liquidity effects across treasury, corporate bond, and equity markets, showing illiquid assets often yield higher returns, but illiquidity premiums are not guaranteed and may reflect biases and hidden risks.

Perform due diligence on fund managers and funds to assess risk and evaluate risk management, drawing lessons from past failures—poor investments, fraud, extreme events, leverage, liquidity, and controls.

Assess a potential investment manager and fund via due diligence elements, including investment background, risk controls, valuation practices, and a balanced risk-return profile with clear fees.

Perform due diligence on manager evaluation, examining strategy, ownership, track record, and investment management, plus risk management and fund operations for sound returns.

Assess risk management due diligence across systematic and unsystematic risk, risk committee and culture, valuation independence, leverage and liquidity, tail risk, risk reporting, and alignment with the investment strategy.

Assess fund operations through internal controls, staff qualifications, and background checks, while reviewing derivatives documents, disclosures, and service provider evaluations for counterparty risk and governance.

Explore how to assess operational risk, business model risk, and fraud risk in funds using a thorough due diligence questionnaire, coverage from governance to controls, and regulatory checks.

Explore alpha and the low risk anomaly, examining how active returns, tracking error, and information ratio measure performance against benchmarks using beta and Sharpe ratio.

Compare CAPM with the Fama-French three-factor model and explain momentum, size, and value-growth effects. Assess time-varying factors, style analysis, and nonlinear alpha issues in tradable versus nontradable factors.

Examine volatility and beta anomalies, showing higher volatility and beta relate to lower risk-adjusted returns via the Sharpe ratio, with tracking error, information ratio, and benchmark choice guiding active management.

Explore factor theory and the CAPM, comparing its assumptions to real-world limits, and contrast with multi-factor models, stochastic discount factors, and efficient market hypotheses for risk pricing and active management.

Explore how the CAPM links market portfolio, beta, and systematic risk to a mean-variance efficient framework, guiding optimal diversification, capital market line choices, and risk premium.

Examine the theoretical shortcomings of the CAPM, including market frictions, taxes, transaction costs, and heterogeneous expectations, with Excel-based demonstrations of momentum, size, value, and growth strategies.

Explore multifactor models, including factor risk premia and pricing kernel concepts, comparing them to CAPM and arbitrage pricing theory, with insights on diversification and market efficiency.

Master portfolio construction by analyzing current portfolios, alphas, covariances, and transaction costs; apply scaling, trimming, and various neutralizations for improved active risk and alpha.

explore portfolio revisions and rebalancing, incorporating marginal contribution and transaction costs. review construction techniques: screens, stratification, linear and quadratic programming—and how alpha, risk, and client cash flows drive dispersion.

Explore diversified and undiversified VAR, marginal VAR, incremental VAR, and component VAR, with formulas and explanations of portfolio risk and diversification benefits.

Master risk planning, budgeting, and monitoring to set return and volatility goals, allocate risk capital, and evaluate performance with VaR, tracking error, mean-variance optimization, and sensitivity analysis.

Explore portfolio performance evaluation using dollar-weighted and time-weighted returns, and compare risk-adjusted metrics like Sharpe ratio, Treynor measure, Jensen's alpha, information ratio, and mean squared measure.

Explore blockchain technology and its impact on finance within current issues in financial markets, including fintech, artificial intelligence, machine learning, climate risk, and how risk and finance managers adapt.

Explore bitcoin and the blockchain basics, including mining, digital signatures, and distributed consensus. Examine tokens, Ethereum, and smart contracts that reduce counterparty risk and costs of trust in digital currencies.

Explore how digital wallets lower intermediaries and economic rent, accelerate settlements with smart contracts, enable micro and faceless transactions, and assess scalability, privacy, and governance challenges.

Understand how cryptocurrency value depends on user trust and collective belief. Discover how smart contracts enable lower counterparty risk and faster settlements through blockchain.

Explore how fintech, big tech, and open banking reshape financial market structure, focusing on concentration, contestability, and competition, with APIs, cloud computing, and third-party providers.

Regulators license third-party services and new technologies, shaping supervision of p2p lending and cloud computing. Banks monitor operational risk and compete with fintechs to meet demand for real-time digital services.

Big tech firms offer financial services, including payments, cross-border transfers, microloans, wallets, asset management, and insurance, via front-end networks and partnerships, expanding access and lowering costs.

Explore how fintech credit expands access by online platforms, highlighting peer-to-peer lending, crowdfunding, and marketplace lending across global markets, while managing operational risk and regulatory protections.

Explore how a three‑party p2p lending platform connects lenders, borrowers, and the intermediary, boosting access to credit and faster funding, with Asia Pacific-led growth and varied consumer versus business lending.

Explore how GDP per capita and regulatory stringency shape fintech credit across countries, analyze risk and returns in peer-to-peer lending, and compare policy frameworks.

Trace fintech credit growth and regulation by Basel and FSB, and map five scenarios from better bank models to new digital banks and robo-advisors with digital KYC.

Distributed, relegated, and disintermediated bank models emerge as incumbents and fintechs partner to deliver cloud services and platform offerings, with regulators addressing operational risk and data privacy in rag tech.

Analyze data safety, cyber security, and consumer protection in digital finance, including fraud risk and unauthorized transactions. Evaluate opportunities and regulatory challenges for banks, fintechs, and big tech.

Explore the digital money spectrum from central bank money to cryptocurrency, including electronic and investment money, and assess centralized versus decentralized models with regulatory implications.

Examine the distinctions between be money backed by governments and various forms of e-money, including private, wallet-based, and investment monies, and explore adoption drivers like convenience, low costs, and trust.

Explore the liquidity, market, and foreign exchange risks of e-money, the role of private backers like Alibaba, Google, and WeChat, and the regulatory framework for fintech licenses and reserves.

Bringing e-money and B-money providers under central bank purview protects customers with depository insurance and central bank backing, while enabling oversight of transactions and alignment with monetary policy.

Explore how digital evolution shapes finance and business, from cryptocurrencies and fintech to non-banking institutions and digital wallets, with computers recording every online transaction.

Explore how big data exceeds Excel and SQL limits, driving cloud-based, distributed analysis of terabytes of transactions; learn tools like Hadoop, MapReduce, and BigQuery for advanced modeling.

Explore how prediction and non-linear relationships drive data analysis with classification and regression trees (cart), including regularization, train-test splits, and out-of-sample forecasting.

Explore how a CART model uses age and travel class to predict Titanic survival, forming partitions, pruning to avoid overfitting, and improving accuracy via bootstrapping, bagging, and boosting.

Learn how random forest ensembles many decision trees to handle nonlinear data, using bootstrap samples and random predictors, with majority voting for final predictions.

Explore how GDP growth is modeled as a time series, selecting predictors with Bayesian structural time series, including trend and seasonality, and assessing causality behind advertising impact on sales.

Use Bayesian structural time series to quantify the causal impact of advertising on sales, via actual versus predicted visits, showing cumulative effects during and after campaigns with big data insights.

Explore how machine learning analyzes unstructured financial data, improves regulatory reporting, enhances fraud detection, and models credit risk via supervised and unsupervised learning.

Explore supervised and unsupervised learning, from linear and nonlinear regression to deep learning. Learn how multi-layer networks extract features from unstructured data, with predictive power and financial world use cases.

Explore how financial institutions use machine learning for regulatory reporting, credit risk modeling, fraud detection, and stress testing, balancing accuracy and interpretability.

Machine learning analyzes large market data to flag money laundering and market abuse, using text and email traffic, audio phone calls, calendar items to detect insider trading and fraudulent trades.

Explain how banks use deposits as liabilities to fund loans and earn net interest margin. Describe fractional reserve system, reserve requirements, and two deposit types: transaction based and non-transaction deposits.

Analyze how banks price deposits based on transaction and non-transaction account fluctuations, using long-term and seasonal averages, with cost plus margin and marginal cost approaches.

Explore how banks price depository accounts through conditional pricing, overhead allocation, and relationship value, and how deposit services fund bank operations.

Explore non-deposit liabilities as a funding source beyond deposits, including federal funds market, FHLB advances, negotiable CDs, and eurocurrency deposits, and how cost of funds shapes banks’ funding mix.

Examine non-deposit liabilities, focusing on the federal funds market and repo agreements, showing how banks borrow short-term reserves via fed wire, meet reserve requirements, and manage funding costs.

Discover how banks borrow from the federal reserve, distinguish federal funds from the discount window, and analyze primary, secondary, and seasonal credits, plus FHLB advances and negotiable CDs.

Examine non-deposit liabilities like commercial papers and eurodollar deposits, their short-term nature, fixed or zero-coupon features, and related funding choices and risks.

Compare historical average cost and pooled funds approaches to determine a bank's cost of funds, comparing sources like savings, time deposits, CDs, and federal borrowing, with risk factors.

Utilize repo financing as a major, secured funding source by posting government securities as collateral, applying haircuts, and aligning buyback terms with asset liquidity and credit quality.

Understand long-term repo financing, including collateral maturity, liquidity, and haircut effects; differentiate general vs special reverse repo transactions and their rate implications.

Analyze a reverse repo transaction that balances demand and supply in the short-term funding market, calculating accrued interest, haircut, and cash flows across both legs and the buyback.

Analyze repo financing, calculate net cash flow and accrued interest, and examine Bear Stearns, JP Morgan, and Lehman Brothers case studies to understand counterparty risk and liquidity.

Explore liquidity transfer pricing (LTV) and governance practices that price the cost of liquidity, credit providers of funds, and strengthen resilience after the global financial crisis.

Explore how banks manage cost of liquidity through the liquidity management information system, transfer pricing, and centralized or decentralized funding structures amid stress scenarios and Basel guidelines.

Explains liquidity transfer pricing concepts: pricing liquidity as a costed good with incentives. Compares four liquidity pricing approaches: zero cost, pooled average, marginal, and pooled funds.

Examine how banks manage liquidity across units, including core deposits, interbank funding, and liquidity transfer pricing. Assess funding sources, costs, and Basel guidelines for a liquidity cushion.

Explore how liquidity cost of funds drives liquidity transfer pricing, as part of cost of doing business, using base rates plus liquidity and term premiums for users and providers.

Examine how European and Japanese banks’ growing US dollar assets and cross-border funding created liquidity and foreign currency funding risk during the global financial crisis.

Quantify banks' international positions by funding foreign currency assets via spot foreign exchange transactions, foreign exchange swaps, or direct foreign currency borrowing, and assess associated funding risk and hedging needs.

Global banks' four perspectives on balance sheets highlight cross-border funding and currency maturity mismatches managed across consolidated entities, with most foreign claims booked outside home offices.

the lecture explains the global us dollar shortage, the funding pressures on banks, and three responses: large write downs, swap lines, and the Fed as lender of last resort.

Analyze banks' foreign currency assets exposure through derivatives and off balance sheet transactions, with international offices booking up to 60% of assets, creating a foreign exchange funding gap.

Investigate illiquid assets and liquidity risk via the Harvard endowment’s 2008 stress, showing funding reliance on illiquid investments and the challenges of liquidation amid market stress, including entry barriers.

Examine the costs, barriers, and information asymmetry in illiquid assets, including high ticket sizes, limited transactions, and funding constraints that shape price discovery.

Most asset classes are illiquid with long periods between trades and low turnover. Retail and high-net-worth investors hold most illiquid assets like housing, human capital, and private real estate.

Explore how illiquidity creates a liquidity premium and distorts returns in long-term debt, real estate, and private markets, while survivorship bias, infrequent trading, and price smoothing bias distort reported performance.

Explore illiquid assets and the illiquidity premium, noting the lack of benchmarks and how market makers, private equity, and dynamic strategies influence returns.

Explore the persistent violation of covered interest rate parity since the 2007–08 crisis and its arbitrage implications, and how balance of payments and purchasing power parity shape exchange rates.

Explore how interest rate parity determines exchange rates by comparing domestic and foreign rates, inflation, and monetary policy, with examples of arbitrage via forward contracts.

Explain covered interest rate parity, the basis b, and how forward hedging ties foreign and domestic interest rates; discuss banks, institutional hedging, and policy-driven factors.

Learn how the covered interest rate parity basis opens and stays non-zero as risk controls, liquidity costs, and regulation limit arbitrage in foreign currency markets.

Trace the evolution of ALM strategies from asset-focused to liability- and funds-focused approaches. Connect interest rate risk management to yield curve, maturity gap, and net interest margin.

Analyze the yield curve’s liquidity and credit risk across short and long durations, including inverted curves as recession indicators and how banks manage interest rate sensitivity gaps by maturity.

Explore how duration gap informs interest rate sensitive gap management to align asset and liability portfolios while assessing interest rate, credit, and inflation risks.

Analyze how duration and convexity shape net worth and how banks manage positive and negative duration gaps. Include a Fannie Mae example of duration gap and basis points scenario analysis.

Explore the principles of sound operational risk management, three lines of defense, and corporate operational risk function, covering risk governance, enterprise risk management, regulatory compliance, and stress testing.

Explore operational risk management from board governance to risk appetite and controls, using tools like rsa and csa, kpis, scenario analysis, audits, and outsourcing and technology risk.

Explore how enterprise risk management integrates risks in a cohesive framework to optimize macro and micro level risk-return, hedge diversifiable risk, and align economic value with accounting value.

Analyze how capital allocation among products, lines of business, and practices creates economic value within an ERM framework by balancing risk and risk-return trade-offs.

Integrate market, credit, and operational risk at the enterprise level, highlighting interdependencies beyond silos and prioritizing top ten risks, real-time reporting, and risk-adjusted performance.

Discover how the enterprise risk management framework treats the organization as an integrated whole, capturing interdependencies among market, credit, and operational risk with real-time, risk-adjusted performance reporting.

Explore enterprise risk management as it interplays across business lines and portfolios, including risk transfer, liquidity, geography, risk analytics, and stakeholder management.

Explore how risk appetite defines the aggregate level and capacity for risk across an organization, from top-level to lower-level risk, and drives governance and regulatory alignment.

Unpack the challenges of implementing a risk appetite framework from top-down strategy to bottom-up execution, including planning cycle alignment, stakeholder buy-in, and ongoing supervisory expectations.

Risk appetite framework combines qualitative and quantitative factors to set risk limits across credit, market, liquidity, and operational risks, cascading from strategy to business units with governance and monitoring.

Foster a diverse senior leadership and board to improve risk management, and measure culture through ethics, behavior, and performance to restore public trust in finance, noting regulators can't create culture.

Link risk culture in banking to the broader organizational ethics and quantify it using staff and customer feedback, whistleblower policy usage, and risk-adjusted performance measures.

Explore how risk culture in banking blends organizational values and ethics into decision making, with top-level leadership driving consistent messages across geographies, including developing and developed contexts, and regulators' principles.

Explore the rating model validation process for credit ratings, covering qualitative and quantitative validation, calibration, ex-post versus ex-ante comparisons, and Basle guidelines on governance and independence.

Assess calibration by comparing forecasted default rates with actual outcomes and note how quickly the model adapts, incorporating Basel guidance on discriminatory power and validation.

Assess model risk by examining errors in models and the quality of var estimates. Validate market, security master, and position data to ensure accurate var measures and informed trading decisions.

Explore how variability in var estimates stems from calculation approaches and risk-factor mapping. See how liquidity, horizon choices, and model risk in mortgage-backed securities fuel underestimation during crises.

Explore a 1.5 billion commercial loan portfolio to compute risk-adjusted returns using the ROC formula, detailing expected revenue, operating costs, expected losses, taxes, and economic capital.

Explore risk-adjusted return on capital (RAROC) for performance measurement, using VAR, default probability, confidence level, and hurdle rate to guide capital budgeting and internal risk assessment.

Explore how risk-adjusted return on capital drives diversification, guides capital budgeting, and ranks projects by their risk-adjusted return and impact on firm diversification.

Explore coherent risk measures for economic capital, compare standard deviation, value at risk, expected shortfall, and spectral/distorted metrics, and learn aggregation methods such as covariance matrices, copulas, and full modeling.

Explore qualitative and quantitative validation within the economic capital framework, including use tests, reviews, system implementation, and sensitivity analysis; examine challenges from market, credit, and operational risks.

Explore the capital adequacy process for large US banks, detailing risk management foundation, stress testing, scenario analysis, and loss estimation methods, with emphasis on internal controls, governance, and capital policy.

Forecast pre-provision net revenue to estimate reserves and provisions for economic losses, allocate capital at the bcc level, and back-test to assess capital adequacy against actual outcomes.

Explore how post-crisis stress testing evolved from single shocks to macroeconomic, scenario-based frameworks, emphasizing capital requirements, SCAP, and the role of globally systemically important banks.

Explore how stress testing evolved from scap to CCR, focusing on capital adequacy, baselines, tailored supervision, and scenario planning for non global systemically important banks.

CCR and DFAST compare stress testing approaches, showing how CCR emphasizes future capital actions and CCAR scenarios beyond supervisory benchmarks to address severe shocks like COVID-19.

Explore how supervisors and regulators guide outsourcing risk management for banks and financial institutions, detailing compliance, concentration, reputational risks, country risk, operational risk, and legal risk from third-party providers.

Define contract provisions for the TPRM program, detailing scope, terms, compensation, performance standards, and risk accountability between the owner and the third party, including data privacy and bank oversight.

This lecture explains money laundering in three stages—placement, layering, integration—and its link to financing terrorism, and outlines risk management principles, due diligence, governance, and the three lines of defense.

Identify and evaluate money laundering and financial terrorism risks through comprehensive customer due diligence, robust kyc policies, governance, sar reporting, and a three-line defense with continuous monitoring.

Explain how banks use straight-through processing with AML, sanctions, and KYC checks, including third-party due diligence, to prevent cross-border money laundering while balancing privacy and false positives for customers.

Explore how over-the-counter derivatives markets differ from exchange-traded contracts, focusing on margins, mark-to-market, and counterparty risk, and examine post-crisis central clearing reforms from Pittsburgh 2009.

Regulatory changes push standardised otc derivatives to be cleared by a centralised counterparty, standardise contracts, and trade on electronic platforms, improving price discovery, transparency, and settlement.

Analyze the shift toward clearing and central counterparty risk reduction in OTC and exchange markets, balancing systemic, credit, liquidity, and operational risks with regulatory oversight.

Trace the global regulatory evolution from Basel I to Basel 2.5 and the trading book reforms, highlighting stress testing, CCAR, Dodd-Frank, and DFAST shaping modern banking supervision.

Trace the Basel framework shift from one-size-fits-all to customized supervision, as risk-weighted assets and capital ratios drive bank resilience under Basel I to Basel III and beyond.

Basel II builds on Basel I with a three-pillar framework: minimum capital requirements, supervisory review, and market discipline, to strengthen banking regulation and global financial markets.

Learn Basel III capital rules, covering tier one and tier two components, risk weighted assets, and asset risk weights from zero to 100%, plus cocos and other hybrids.

Understand how banks compute risk weighted assets using asset weights 0% to 100% and how this drives tier one capital under Basel II to Basel 2.5, including stressed var.

Explore Basel 2.5 and Frtb concepts, including stressed VAR, market capital charge, and minimum capital requirements, with model validation and backtesting at trading desk and bank-wide level.

Explore Basel III capital requirements, including tier one and tier two capital, capital conservation and countercyclical buffers, leverage and liquidity ratios, and 99.9% VAR stress measure.

The lecture explains how Basel guidelines and the Reserve Bank of India build regulatory capital, detailing CET1 minimums, capital conservation buffers, and India's total minimum of 11.5%.

Explore cocos (contingent convertible bonds) as tier two capital that convert to common equity on trigger events, impacting capital adequacy and strengthening banks' capital during stress.

Examine Basel III's standardized approach for credit risk as a minimum floor, compare it with the IRB framework, and review counterparty risk, CVA, securitization, and operational risk frameworks.

Examine Basel III reforms on operational risk capital, leverage ratio and buffers, and the flows for calculating risk parameters under standardized and IRB approaches across credit, market, and operational risk.

Learn to calculate operational risk capital using the standardized framework by combining the business indicator (BIC) with the internal loss multiplier (ILM), based on LDC, SC, and FC components.

Record operational loss data within a robust risk framework, noting occurrence and discovery dates, period, reserves, and PNL impact, with transparent BIC components and internal loss multiplier calculations.

Explore cyber risk as a rising operational risk in banking, and apply a cyclical risk framework, identifying, detecting, responding, assessing impact, recovering, and protecting, emphasizing crisis management and staff awareness.

Build cyber resilience through a top-down business continuity plan and RCC exercise, guided by ISO 27001, emphasizing detection, containment, and crisis management; anticipate, withstand, and learn from data breach.

Quantify reputational, legal, and regulatory risks in dollar terms with a cyber value at risk framework; perform regular, event-driven assessments to build resilient organizations.

Develop a robust cyber governance framework by aligning strategy, culture, and governance with proactive controls testing, crisis response, and staff training for sustained resilience, plus supervisors and third-party coordination.

Identify the UK's financial market infrastructures and their supervising authorities—the Bank of England, PRA, and FCA—and outline key objectives for operational resilience, financial stability, market integrity, and consumer protection.

Identify and manage risks to operational resilience in financial services, implement crisis management and business continuity plans, and strengthen cyber security controls to withstand disruptions.

Test baseline operational resilience and cyber threat responses across banks, payment services, insurance services, and investment management, under UK regulators' six-step framework of identify, map, assess, test, invest, communicate.

Enhance operational resilience by communicating risk to internal and external stakeholders and applying six steps—identify, map, assess, test, invest, communicate—via scenario analysis for disruption tolerance in the UK financial sector.

Identify the drivers of disruption across the supply chain by examining the scale of innovations, digitisation, legacy infrastructure, and the sophistication of malicious actors to test the organisation's operational resilience.

Explore the characteristics of an operationally resilient organization, including governance, organizational focus, integration, risk measurement, and preparedness to build enterprise-wide resilience.

This FRM part 2 course introduces an 80-question practice paper aligned to the updated 2020 syllabus, covering six sections and strategies like elimination to navigate tricky questions.

Explore market risk measurement and management through var and var mapping, detailing lognormal var for long option portfolios and normal var for forward positions, with daily conversions and 95% confidence.

Compute May and June correlations for a Rwanda market index using mean reversion toward a long-term average, and examine copula functions for default risk and hedging with Dv01 and tips.

Analyze dv01 hedging with tips, swap payments, and binomial bond valuation. Explore drift and mean-reverting interest rate models, including Vicsek.

Analyze the Cox-Ingersoll-Ross model with a positive drift and zero lower bound, highlighting QE impacts and rate behavior, then discuss volatility, options, and Basel IV market var.

Explore credit risk concepts, including the Kamil rating system, expected and unexpected losses, internal rating models vs regulators, Willcocks cash flow model for startup liquidity, and CDO tranche risk.

Practice solving FRM Part 2 exam questions on equity tranche IRR, break and close-out clauses, margin risk timing, CCP advantages, and BCVA calculations.

Explore counterparty credit risk and wrong-way risk, master CVA calculations, and analyze lending criteria along with a Tokyo–Singapore total return swap settlement.

Explore operational and integrated risk management with rcsa as a key tool for cross-unit impact analysis, and examine risk appetite, governance, and risk culture concepts.

Evaluate mismatches in model risk descriptions, distinguish statistical, calibration, and parameter risks, and analyze data errors, suspicious activity reporting, risk-weighted assets, and Basel buffers.

Calculate the stable funding ratio using ASF and SF to determine net stable funding, and explore cyber resilience attributes, best practices, ISO standards, and cyber value at risk metrics.

Analyze liquidity and treasury risk, calculating cost of liquidation in normal and stress markets using bid-ask spread and mid-market value, with 99% confidence.

Explore liquidity risk concepts, from identifying early warning indicators and appropriate contingent funding buffers to key liquidity ratios, and calculate bank funding costs using the pooled funds approach.

Explore why banks adopt the average cost of funds approach to align income and funding amid liquidity stress, and how post-crisis rate parity shifts drive hedging via swaps.

Examine risk management and investment management through CAPM assumptions, portfolio analysis, and risk-adjusted metrics like alpha, beta, and benchmark neutral alpha.

Analyze portfolio rebalancing methods including screens, stratification, linear programming, and quadratic programming and their effect on benchmark similarity. Learn to compute diversified var and both dollar-weighted and time-weighted returns.

Explore tech firms entering finance with quick transactions, APIs, and mobile apps, and review China NPIs’ regulation of money market funds, Ireland fintech growth drivers, and related risk dynamics.

Explore how central banks regulate e-money, licensing, reserves, and KYC to manage systemic risk, and study benchmark changes, LIBOR history, and ideal benchmark features for FRM Part 2.