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FRM - Level II tests a candidate’s knowledge and understanding of the modern risk management practices. There will be 80 questions in the exam, which needs to be completed in 4 hours time. There are in total 5 topics in FRM - II, the first one is Market Risk Measurement and Management which has weightage of 25%, Credit Risk Measurement and Management has 25%, Operational and Integrated Risk Management has 25%, Risk Management and Investment Management has 15%, Current Issues in Financial Markets has 10% weightage. This course will give you access to:
This is the introductory video for FRM-II which talks about the topics covered under this course.
These topics are as follows:
· Market Risk Measurement and Management
· Credit Risk Measurement and Management
· Operational and Integrated Risk Management
· Risk Management and Investment Management
· Current Issues in Financial Markets
This lecture talks about:
· Volatility smile and volatility skew
· How put-call parity indicates that the implied volatility used to price call options is the same used to price put options.
· The shape of the volatility smile (or skew) and the shape of the implied distribution of the underlying asset price and the pricing of options on the underlying asset.
· Why foreign exchange rates are not necessarily log-normally distributed and the implications this can have on option prices and implied volatility.
· Volatility smile for equity options and give possible explanations for its shape.
· Volatility term structures and volatility surfaces and how they may be used to price options.
· The impact of the volatility smile on the calculation of the “Greeks” and the impact of asset price jumps on volatility smiles.
Lectures(3-4) talks about:
· Exotic derivatives and plain vanilla derivatives
· Some of the factors that drive the development of exotic products.
· How any derivative can be converted into a zero-cost product?
· Identifying and describing how various option characteristics can transform standard American options into nonstandard American options.
· The characteristics and pay-off structure of:
o Forward start options
o Compound options
o Chooser and barrier options
o Binary options
o Lookback options
o Shout options
o Asian options
o Exchange options
o Rainbow options
o Basket options
· Describing and contrasting volatility and variance swaps.
· The basic premise of static option replication and how it can be applied to hedging exotic options.
Lectures (5-6) talks about:
· Calculating the expected discounted value of a zero-coupon security using a binomial tree.
· Constructing and applying an arbitrage argument to price a call option on a zero-coupon security using replicating portfolios.
· Why a call option on a zero-coupon security cannot be properly priced using expected discounted values.
· The role of up-state and down-state probabilities in the valuation of a call option on a zero-coupon security
· Defining risk-neutral pricing and explain how it is used in option pricing.
· The difference between true and risk-neutral probabilities, and apply this difference to interest rate drift.
· How the principles of arbitrage pricing of derivatives on fixed income securities can be extended over multiple periods.
· The rationale behind the use of non-recombining trees in option pricing.
· The value of a constant maturity Treasury swap, given an interest rate tree and the risk-neutral probabilities.
· Why the Black-Scholes-Merton model used in valuing equity derivatives is not appropriate to value derivatives on fixed income securities.
This lecture talks about:
· The role of interest rate expectations in determining the shape of the term structure.
· A risk-neutral interest rate tree to assess the effect of volatility on the shape of the term structure.
· The convexity effect using Jensen’s inequality.
· The price and return of a zero coupon bond incorporating a risk premium.
Lecture (8-9) talks about:
· The process and effectiveness of the following models, and construct a tree for a short-term rate using the following models:
· A model with normally distributed rates and no drift (Model 1)
· A model incorporating drift (Model 2)
· The short-term rate change and standard deviation of the change of the rate using a model with normally distributed rates and no drift.
· Methods for handling negative short-term rates for term structure models.
· The process of and construct a tree for a short-term rate under the Ho-Lee Model with time dependent drift.
· Describing uses and benefits of the arbitrage-free models and assess the issue of fitting models to market prices.
· The process of and construct a simple and recombining tree for a short-term rate under the Vasicek Model with mean reversion.
· The Vasicek Model rate change, standard deviation of the change of the rate, expected rate in T years, and half life.
· The effectiveness of the Vasicek Model.
This lecture talks about:
· The short-term rate process under a model with time-dependent volatility (Model 3).
· The short-term rate change and the behavior of the standard deviation of the change of the rate using a model with time dependent volatility.
· The effectiveness of time-dependent volatility models.
· The short-term rate process under the Cox-Ingersoll-Ross (CIR) and Lognormal models.
· The short-term rate change and the basis point volatility using the CIR and Lognormal models.
· The application of a lognormal model with deterministic drift and a lognormal model with mean reversion.
This lecture talks about:
· The securitization process of residential mortgage backed securities (MBS).
· The difference between agency and non-agency MBS and the major participants in the residential MBS market.
· The mortgage prepayment option and the factors that influence prepayments.
· The impact on a MBS of the weighted average maturity, the weighted average coupon, and the speed of prepayments of the mortgages underlying the MBS.
· The effective duration and effective convexity of standard MBS instruments and the factors that affect them.
· Collateralized mortgage obligations (CMOs) and contrast them with MBSs.
· Describing and working through a simple cash flow example for the following types of MBS:
o Pass-through securities
o CMOs, both sequential and planned amortization class
o Interest only and principal only strips
This lecture talks about:
· Backtesting and exceptions and the importance of backtesting VaR models.
· The significant difficulties in backtesting a VaR model.
· The framework of backtesting models with the use of exceptions or failure rates.
· Type I and type II errors.
· Why it is necessary to consider conditional coverage in the backtesting framework.
· The Basel rules for backtesting.
This lecture talks about:
· The principles underlying VaR Mapping, list and the mapping process.
· How the mapping process captures general and specific risks.
· Mapping a fixed income portfolio into positions of standard instruments.
· How mapping of risk factors can support stress testing.
· How VaR can be used as a performance benchmark.
· The method of mapping forwards, commodity forwards, forward rate agreements, and interest rate swaps.
· The method of mapping options.
This lecture talks about:
· VaR using a historical simulation approach.
· VaR using a parametric estimation approach assuming that the return distribution is either normal or lognormal.
· The expected shortfall given P/L or return data.
· Coherent risk measures.
· The method of estimating coherent risk measures by estimating quantiles.
· The method of estimating standard errors for estimators of coherent risk measures.
· The use of QQ plots for identifying the distribution of data.
Lectures (15-16) talks about:
· The bootstrap historical simulation approach to estimating coherent risk measures.
· Historical simulation using non-parametric density estimation.
· The following weighted historic simulation approaches:
o Age-weighted historic simulation
o Volatility-weighted historic simulation
o Correlation-weighted historic simulation
o Filtered historical simulation
· The advantages and disadvantages of non-parametric estimation methods.
This lecture talks about:
· The drawbacks of using correlation to measure dependence.
· How copulas provide an alternative measure of dependence.
· How tail dependence can be investigated using copulas.
Lectures (18-19) talks about:
· The importance and challenges of extreme values for risk management.
· Extreme value theory (EVT) and its use in risk management.
· The peaks-over-threshold (POT) approach.
· The parameters of a generalized Pareto (GP) distribution.
· The tradeoffs in setting the threshold level when applying the GP distribution.
· VaR and expected shortfall using the POT approach, given various parameter values.
· The importance of multivariate EVT for risk management.
This lecture talks about:
· The key attributes that define mortgages.
· The mortgage payment factor.
· Prepayment risk, reasons for prepayment, and the negative convexity of mortgages.
· Credit and default risk analysis of mortgages, including metrics for delinquencies, defaults, and loss severity.
This lecture talks about:
· The evolution of the MBS market.
· The creation of agency (fixed rate and adjustable rate) and private-label MBS pools, pass-throughs, CMOs, and mortgage strips.
· How a loan progresses from application to agency pooling.
· MBS market structure and the ways that fixed rate pass-through securities trade.
· A dollar roll transaction, how to value a dollar roll, and what factors can cause a roll to trade “special.”
· The purpose of cash flow structuring of mortgage backed securities.
This lecture talks about:
· The static cash flow yield of a MBS using bond equivalent yield (BEY) and the associated nominal spread.
· The steps in valuing a mortgage security using Monte Carlo methodology.
· Option-adjusted spread (OAS), zero-volatility OAS, and option cost.
· How to select the number of interest rate paths in Monte Carlo analysis.
· Total return analysis, total return, and factors present in more sophisticated models.
· Limitations of the nominal spread, Z-spread, OAS, and total return measures.
This lecture talks about:
· Exogenous and endogenous liquidity risk and explain how they might be integrated into VaR models including adjusting the VaR time horizon.
· VaR, Expected Shortfall, Spectral, and other identified risk measures.
· The recent state of stress testing research and practice.
· Compare unified versus compartmentalized risk measurement.
· Assess the results of research on “top-down” and “bottom-up” risk aggregation methods.
· Intermediary balance sheet management and the cyclical feedback loop from VaR constraints on leveraged investors.
Lectures (23-24) talks about:
· The subprime mortgage credit securitization process in the United States.
· Key frictions in subprime mortgage securitization and the relative contribution of each factor to the subprime mortgage problems.
· The characteristics of the subprime mortgage market, including the creditworthiness of the typical borrower and the features and performance of a subprime loan.
· The structure of the securitization process of the subprime mortgage loans.
· The credit ratings process with respect to subprime mortgage backed securities.
· The implications of credit ratings on the emergence of subprime related mortgage backed securities.
· The relationship between the credit ratings cycle and the housing cycle.
· The implications of the subprime mortgage meltdown on the management of portfolios.
· The difference between predatory lending and borrowing.
Lectures (26-27) talks about :
· Describe the mechanics of a single named credit default swap (CDS), and describe particular aspects of CDSs such as settlement methods, payments to the protection seller, reference name, ownership, recovery rights, trigger events, accrued interest and liquidity.
· Describe portfolio credit default swaps, including basket CDS, Nth to Default CDS, Senior and Subordinated Basket CDS.
· Describe the composition and use of iTraxx CDS indices.
· Explain the mechanics of asset default swaps, equity default swaps, total return swaps and credit linked notes.
This lecture talks about:
· Objectives of structured finance and explain the motivations for asset securitization.
· The process and benefits of ring-fencing assets.
· The role of structured finance in venture capital formation, risk transfer, agency cost reduction, and satisfaction of specific investor demands.
· The steps involved and the various players in a structuring process.
· The process of tranching and subordination, and the role of loss distributions and credit ratings.
This lecture talks about:
· Securitization and the process and the role the participants play.
· The differences in the mechanics of issuing securitized products using a trust vs. special purpose entity.
· The various types of internal and external credit enhancements and interpret a simple numerical example.
· The impact liquidity, interest rate and currency risk has on a securitized structure, and list securities that hedge these exposures.
· The securitization process for mortgage backed securities and asset backed commercial paper.
This lecture talks about:
· Collateralized debt obligations (CDO) and the motivations of CDO buyers and sellers.
· The types of collateral used in CDOs.
· The structure of balance sheet CDOs and arbitrage CDOs.
· The benefits of and motivations for balance sheet CDOs and arbitrage CDOs.
· Cash flow vs. market value CDOs.
· Static vs. managed portfolios of CDOs.
Lectures (31-33) talks about:
· The Merton model for corporate security pricing, including its assumptions, strengths and weaknesses:
o Security-holder payoffs based on the Merton model
o The Merton model, the value of a firm’s debt and equity and the volatility of firm value
o The results and practical implications of empirical studies that use the Merton model to value debt
· The Moody’s KMV Credit Monitor Model to estimate probability of default using equity prices, and the Moody’s KMV equity model with the Merton model.
· Credit scoring models and the requisite qualities of accuracy, parsimony, non-triviality, feasibility, transparency and interpretability.
· The difference among the following quantitative methodologies for credit analysis and scoring:
o Linear discriminant analysis
o Parametric discrimination
o K nearest neighbor approach
o Support vector machines
· The difference the following decision rules: minimum error, minimum risk, Neyman-Pearson and Minimax.
· The problems and tradeoffs between classification and prediction models of performance.
· Important factors in the choice of a particular class of model.
This lecture talks about:
· Securities with different types of credit risks, such as corporate debt, sovereign debt, credit derivatives, and structured products.
· The difference between book and market values for a firm’s capital structure.
· Different debt seniorities and their respective collateral structure.
· Common frictions that arise during the creation of credit contracts.
· The following terms related to default and recovery: default events, probability of default, credit exposure, and loss given default.
· Expected loss from recovery rates, the loss given default, and the probability of default.
· The difference between a credit risk event and a market risk event for marketable securities.
· Credit assessment techniques such as credit ratings and rating migrations, internal ratings, and risk models.
· Counterparty risk, describe its different aspects and explain how it is mitigated.
· How counterparty risk is different from credit risk.
· The Merton Model and its use to calculate the value of a firm, the values of a firm’s debt and equity, and default probabilities.
· Credit factor models and an example of a single-factor model.
· Credit VaR (Value-at-Risk).
This lecture talks about:
· The different ways of representing spreads.
· How default risk for a single company can be modeled as a Bernoulli trial.
· The relationship between exponential and Poisson distributions.
· The hazard rate and its use to define probability functions for default time and conditional default probabilities.
· Risk-neutral default rates from spreads.
· Advantages of using the CDS market to estimate hazard rates.
· How a CDS spread can be used to derive a hazard rate curve.
· A hazard rate curve from a CDS spread curve.
· A default distribution curve from a hazard rate curve.
· How the default distribution is affected by the sloping of the spread curve.
· Spread risk and its measurement using the mark-to-market and spread volatility.
This lecture talks about:
· Default correlation for credit portfolios.
· Drawbacks in using the correlation-based credit portfolio framework.
· The effects of correlation on a credit portfolio and its Credit VaR.
· How a single factor model can be used to measure conditional default probabilities given economic health.
· The variance of the conditional default distribution and the conditional probability of default using a single-factor model.
· The relationship between the default correlation among firms and their single-factor model beta parameters.
· How Credit VaR of a portfolio is calculated using the single-factor model, and how correlation affects the distribution of loss severity for intermediate values between 0 and 1.
· How Credit VaR can be calculated using a simulation of joint defaults with a copula.
This lecture talks about:
· The role of capital structure and credit losses in a securitization.
· A waterfall example in a securitization with multiple tranches.
· The key participants in a securitization, and some conflicts of interest that can arise in the process.
· One or two iterations of interim cash-flows in a three tiered securitization structure including the final cash-flows to each tranche holder.
· A simulation approach to calculating credit losses for different tranches in a securitization of a portfolio of loans.
· How the probability of default and default correlation among the underlying assets of a securitization affects the value, losses and Credit VaR of equity, junior, and senior tranches.
· How default sensitivities for tranches are measured.
· Some of the different types of risks that play a role in structured products.
· Implied correlation and how it can be measured.
· The motivations for using structured credit products.
This lecture talks about:
· Counterparty risk and how it differs from lending risk.
· Types of transactions that carry counterparty risk.
· Some ways in which counterparty risk can be mitigated.
· The following terminology related to counterparty risk: credit exposure, credit migration, recovery, mark-to-market, replacement cost, asymmetric exposure, and potential future exposure.
· The different ways institutions can manage counterparty risk.
· The drawbacks of relying on triple-A rated, “too-big-to-fail” institutions as a method of managing counterparty risk.
· How counterparty risk is quantified and briefly describes credit value adjustment (CVA).
· How counterparty risk is hedged and explains important factors in assessing capital requirements for counterparty risk.
· The following metrics for credit exposure: expected mark-to-market, expected exposure, potential future
This lecture talks about:
· The difference between a two-way and one-way agreement and the purpose of an ISDA master agreement and credit support annex (CSA).
· Types of default-remote entities and describe problems associated with the assumption that they are in fact default remote.
· How termination and walk-away features work in credit contracts.
· Netting and close-out procedures (including multilateral netting), their advantages and disadvantages, and how they fit into the framework of the ISDA master agreement.
· The effectiveness of netting in reducing exposure based on correlation between contract mark-to-market values.
· The effect of netting on exposure metrics.
· Collateralization and the mechanics of the collateralization process, including the role of a valuation agent, the types of collateral that are typically used, and reconciliation of collateral disputes.
· The following features of collateralization agreements: links to credit quality, margins and call frequency, thresholds, minimum transfers, rounding, haircuts, interest, and rehypothecation.
This lecture talks about:
· The following techniques used to quantify credit exposure: add-ons, semi-analytical methods, and Monte Carlo simulation.
· The Monte Carlo simulation technique for quantifying exposure, and the choice of risk “hotspots” on the exposure profile.
· Typical exposure profiles for the following security types: loans, bonds, repos, swaps, FX, options, and credit derivatives.
· How payment frequencies and exercise dates affect the exposure profiles of securities.
· The difference between risk-neutral and real probability measures in the context of how they are used in credit exposure models.
· The parameters used in simple single-factor models of the following security types: equities, FX, commodities, credit spreads, and interest rates.
· How netting is modeled and the netting factor.
· Marginal expected exposure and the effect of correlation on total exposure.
This lecture talks about:
· The expected exposure and potential future exposure over the re-margining period given normal distribution assumptions.
· The assumptions and parameters involved in modeling collateral.
· The impact that each factor of collateral modeling has on the exposure profile, starting from a simple case of full collateralization.
· The relevant risks involved as a result of entering into a collateral agreement.
This lecture talks about:
· The motivation of pricing counterparty risk.
· Credit value adjustment (CVA) when no wrong-way risk is present and the process of approximating the CVA spread.
· The incremental CVA and the marginal CVA.
· How collateralization and netting affect the CVA price.
· Challenges in pricing CVA arising from the presence of exotic products and the issue of path dependency.
· CVA and CVA spread in the presence of a bilateral contract.
· Issues that need to be considered in pricing bilateral CVA.
Lectures (43-46) talks about:
· The relationship of credit spreads, time to maturity, and interest rates.
· The differences between valuing senior and subordinated debt using a contingent claim approach.
· The fundamental differences between CreditRisk+, CreditMetrics and KMV credit portfolio models.
· A credit derivative, credit default swap, and total return swap.
· A vulnerable option, and explain how credit risk can be incorporated in determining the option’s value.
· How to account for credit risk exposure in valuing a swap.
This lecture talks about:
· The RAROC (risk-adjusted return on capital) methodology and some of the potential benefits of its use.
· How capital is attributed to market, credit, and operational risk.
· The capital charge for market risk and credit risk.
· The difficulties encountered in attributing economic capital to operational risk.
· The Loan Equivalent Approach and use it to calculate RAROC capital.
· How the second-generation RAROC approaches improve economic capital allocation decisions.
· The adjusted RAROC for a project to determine its viability.
This lecture talks about:
· The economic capital implementation framework that describe the challenges that appear in:
o Defining risk measures
o Risk aggregation
o Validation of models
o Dependency modeling in credit risk
o Evaluating counterparty credit risk
o Assessing interest rate risk in the banking book
· The BIS recommendations that supervisors should consider to make effective use of risk measures not designed for regulatory purposes.
· The constraints imposed and the opportunities offered by economic capital within the following areas:
o Credit portfolio management
o Risk based pricing
o Customer profitability analysis
o Management incentives
This lecture talks about:
· Liquidity risk and describe factors that influence liquidity.
· The bid-ask spread as a measure of liquidity.
· Exogenous and endogenous liquidity.
· The challenges of estimating liquidity-adjusted VaR (LVaR).
· LVaR using the Constant Spread approach and the Exogenous Spread approach.
· Endogenous Price approaches to LVaR, its motivation and limitations.
· The relationship between liquidation strategies, transaction costs and market price impact.
· Liquidity at risk (LaR) and describe the factors that affect future cash flows.
· The role of liquidity in crisis situations and approaches to estimating crisis liquidity risk.
This lecture talks about:
· Model risk; identify and describe sources of model risk.
· The challenges involved with quantifying model risk.
· Methods for estimating model risk, given an unknown component from a financial model.
· Ways risk managers can protect against model risk.
· The role of senior managers in managing model risk.
· Procedures for vetting and reviewing a model.
· The function of an independent risk oversight (IRO) unit.
This lecture talks about:
· Ways that errors can be introduced into models.
· The types of horizon, computational and modeling decisions which could result in variability of VaR estimates.
· Challenges related to mapping of risk factors to positions in making VaR calculations.
· How improper mapping can understate specific risks such as basis or liquidity risk.
· Reasons for the failure of the long-equity tranche, short-mezzanine credit trade in 2005 and how such modeling errors could have been avoided.
· The two major defects in model assumptions which led to the underestimation of systematic risk for residential mortgage backed securities (RMBS) during the 2008-2009 financial downturn.
Lectures (51-53) talks about:
· The difference between sources of liquidity risk, including transactions liquidity risk, balance sheet/ funding liquidity risk and systemic risk.
· The process by which a fractional-reserve bank engages in asset liability management.
· Issues related to systematic funding liquidity risk with respect to LBOs, merger arbitrage hedge funds, and convertible arbitrage hedge funds.
· Specific liquidity issues faced by money market mutual funds.
· The economics of the collateral market and explain the mechanics of the following transactions using collateral: margin lending, repos, securities lending and total return swaps.
· A firm’s leverage ratio, the formula for the leverage effect, and the relationship between leverage and a firm’s return on equity.
· A firm’s leverage and a firm’s balance sheet given the following types of transactions: purchasing long equity positions on margin, entering into short sales, and trading in derivatives.
· The main sources of transactions liquidity risk.
· The expected transactions cost and the 99 percent spread risk factor for a transaction.
· The liquidity-adjusted VaR for a position to be liquidated over a number of trading days.
· Characteristics used to measure market liquidity, including tightness, depth and resiliency.
· The challenges posed by liquidity constraints on hedge funds during times of financial distress, with an emphasis on handling redemptions.
This lecture talks about:
· Enterprise risk management (ERM) and how implementing ERM practices and policies create shareholder value both at the macro and the micro level.
· How an ERM program can be used to determine the right amount of risk.
· The development and implementation of an ERM system.
· The relationship between economic value and accounting performance.
· The role of and issues with correlation in risk aggregation.
· The difference between regulatory and economic capital.
· The use of economic capital in the corporate decision making process.
This lecture talks about:
· The loss distribution approach to measuring operational risk.
· Issues related to external and internal operational loss data sets.
· How frequency and severity distributions of operational losses are obtained.
· How a loss distribution is obtained from frequency and severity distributions.
· How operational losses are aggregated across various types using dependence modeling.
This lecture talks about:
· The nature of operational loss distributions.
· The consequences of working with heavy tailed loss data.
· The amount of data required to estimate percentiles of loss distributions.
· Methods of extrapolating beyond the data.
· The loss distribution approach to modeling operational risk losses.
· The challenges in validating capital models.
This lecture talks about:
· The major functions of large dealer banks and the firm-specific and systemic risk factors attendant to each.
· The structure of the major markets in which large dealer banks operate.
· How diseconomies of scope in risk management and corporate governance may arise in large dealer banks.
· Factors that can precipitate or accelerate a liquidity crisis at a dealer bank and what prudent risk management steps can be taken to mitigate these risks.
· Policy measures that could alleviate some of the firm-specific and systemic risks related to large dealer banks.
This lecture talks about:
· The three “lines of defense” in the Basel model for operational risk governance.
· The eleven fundamental principles of operational risk management as suggested by the Basel committee.
· The role of the Board of Directors as well as senior management in implementing an effective operational risk structure per the Basel committee recommendations.
· The elements of a framework for operational risk management, including documentation requirements.
· Examples of tools which can be used to identify and assess operational risk.
· Features of an effective control environment and specific controls which should be in place to address operational risk.
· The Basel committee’s suggestions for managing technology risk and outsourcing risk.
This lecture talks about:
· The concept of a risk appetite framework (RAF), the elements of a RAF and the benefits to a firm of having a well developed RAF.
· Best practices for a firm’s Chief Risk Officer (CRO), Chief Executive Officer (CEO) and Board of Directors in the development and implementation of an effective risk appetite framework.
· The role of a RAF in managing the risk of individual business lines within a firm.
· Metrics which can be monitored as part of an effective RAF and the classes of metrics to be communicated to various managers within the firm.
· The benefits to a firm from having a robust risk data infrastructure and key elements of an effective IT risk management policy at a firm.
· Factors which could lead to poor or fragmented IT infrastructure at an organization.
· The challenges and best practices related to data aggregation at an organization.
This lecture talks about:
· The differences in the features and scope of stress tests before and after the Supervisory Capital Assessment Program (SCAP).
· The problem of coherence in modeling risk factors during the stress testing of banks.
· The challenges in mapping from broader macroeconomic factors to specific intermediate risk factors in modeling losses.
· The challenges in modeling a bank's balance sheet over a stress test horizon period.
This lecture talks about:
· The key elements of the three pillars of Basel II:
o Minimum capital requirements
o Supervisory review
o Market discipline
· The type of institutions that the Basel II Accord will be applied to.
· The major risk categories covered by the Basel II Accord.
· The major elements of the three options available for the calculation of credit risk:
o Standardised Approach
o Foundation IRB Approach
o Advanced IRB Approach
· The major elements of the three options available for the calculation of operational risk:
o Basic Indicator Approach
o Standardised Approach
o Advanced Measurement Approach
· The major elements—including a description of the risks covered—of the two options available for the calculation of market risk:
o Standardised Measurement Method
o Internal Models Approach
· The context of Basel II:
o Capital ratio
o Capital charge
o Risk weights and risk-weighted assets
o Tier 1 capital and its components
o Tier 2 capital and its components
o Tier 3 capital and its components
o Probability of default (PD)
o Loss given default (LGD)
o Exposure at default (EAD)
o Maturity (M)
o Stress tests
o Concentration risk
o Residual risk
This lecture talks about:
· Reasons for the changes implemented through the Basel III framework.
· Changes to the regulatory capital framework, including changes to:
· The measurement, treatment, and calculation of Tier 1, Tier 2, and Tier 3 capital
· Risk coverage, the use of stress tests, the treatment of counter-party risk with credit valuations adjustments the use of external ratings, and the use of leverage ratios
· Changes designed to dampen the procyclical amplification of financial shocks and to promote countercyclical buffers.
· Changes intended to improve the handling of systemic risk.
· Changes intended to improve the management of liquidity risk including liquidity coverage ratios, net stable funding ratios, and the use of monitoring metrics.
This lecture talks about:
· The minimum liquidity coverage ratio.
· The net stable funding ratio.
· Practical applications of prescribed liquidity monitoring tools, including:
o Contractual maturity mismatch
o Concentration of funding
o Available unencumbered assets
o Liquidity coverage ratio by significant currency
o Market related monitoring tools
This lecture talks about:
· The objectives for revising the Basel II market risk framework.
· The capital charge for specific risk and general market risk.
· The stressed Value-at-Risk measure and the frequency which it must be calculated.
· The market risk capital requirement.
· The qualitative disclosures for the incremental risk capital charge and for trading portfolios under the internal models approach.
· The regulatory guidance on prudent valuation of illiquid positions.
This lecture talks about:
· Gross loss and net loss
· The process and considerations suggested by the Basel committee for a bank to use in determining a loss data threshold.
· The four data elements which are required to compute a bank’s operational risk capital charge per the Basel Committee’s AMA framework.
· An operational risk management framework (ORMF) and an operational risk measurement system (ORMS) and the relationship between a bank’s ORMF and its ORMS.
· Key guidelines for verification and validation of a bank’s ORMF and ORMS.
· Key supervisory guidelines for the selection of a reference date for an internal loss.
· Key guidelines for the selection of a bank’s Operational Risk Categories (ORCs).
· Key guidelines for modeling the distribution of individual ORCs, including the selection of thresholds, necessary adjustments, and selection of statistical tools and probability distributions.
This lecture talks about:
· The use of VaR parameters and confidence intervals in the Basel II/III and the Solvency II frameworks.
· The difference between classes of risks taken into account in Basel II/III and Solvency II.
· The difference between solvency capital requirements (SCR) and minimum capital requirements (MCR)
· The difference between the Basel II/III and the Solvency II frameworks for the capture of diversification benefits.
· The difference between Basel II/III and the Solvency II frameworks with respect to: 1) risk classes and capital requirements, 2) risk measure and calibration, 3) time perspective, and 4) valuation.
· The Basel II/III and Solvency II frameworks with respect to qualitative risk management aspects, including the internal risk management process, governance, and supervision.
· The key differences between Basel II/III and Solvency II with respect to public disclosure
This lecture talks about:
· The inputs to the portfolio construction process.
· The motivation and methods for refining alphas in the implementation process.
· Neutralization and methods for refining alphas to be neutral.
· The implications of transaction costs on portfolio construction.
· Practical issues in portfolio construction such as determination of risk aversion, incorporation of specific risk aversion, and proper alpha coverage.
· Portfolio revisions and rebalancing and the tradeoffs between alpha, risk, transaction costs and time horizon.
· The optimal no-trade region for rebalancing with transaction costs.
· The following portfolio construction techniques, including strengths and weaknesses:
o Screens
o Stratification
o Linear programming
o Quadratic programming
· Dispersion, explain its causes and methods for controlling forms of dispersion.
Lectures (68-69) talks about:
· The difference between individual VaR, incremental VaR and diversified portfolio VaR.
· The role of correlation has on portfolio risk.
· Diversified VaR, individual VaR, and undiversified VaR of a portfolio.
· The challenges associated with VaR measurement as portfolio size increases.
· How one can use marginal VaR to guide decisions about portfolio VaR.
· The difference between risk management and portfolio management, and how to use marginal VaR in portfolio management.
This lecture talks about:
· Risk budgeting.
· The impact of horizon, turnover and leverage on the risk management process in the investment management industry.
· The investment process of large investors such as pension funds.
· The risk management challenges with hedge funds.
· The following types of risk: absolute risk, relative risk, policy-mix risk, active management risk, funding risk and sponsor risk.
· How VaR can be used to check compliance, monitor risk budgets and reverse engineer sources of risk.
· How VaR can be used in the investment process and development of investment guidelines.
· The risk budgeting process across asset classes and active managers.
This lecture talks about:
· VaR and tracking error as risk measures.
· Risk planning including objectives and participants in its development.
· Risk budgeting and the role of quantitative methods.
· Risk monitoring and its role in an internal control environment.
· Sources of risk consciousness within an organization.
· The objectives of a risk management unit in an investment management firm.
· How risk monitoring confirms that investment activities are consistent with expectations.
· The importance of liquidity considerations for a portfolio.
· The objectives of performance measurement.
· Common features of a performance measurement framework.
This lecture talks about:
· The expected return-beta relationship implied in the CAPM, and the methodologies for estimating the security characteristic line and the security market line from a proper dataset.
· The two-stage procedure employed in early tests of the CAPM and the concerns related to these early test results.
· Roll’s critique to the CAPM, as well as expansions of Roll’s critique.
· The methodologies for correcting measurement error in beta, and historical test results of these methodologies.
· The test of the single-index models that accounts for human capital, cyclical variations and non-traded business.
· The tests of multifactor CAPM and APT.
· The Fama-French three-factor model, and explain historical test results related to this model.
· Different models used to measure the impact of liquidity on asset pricing and asset returns.
· The “equity premium puzzle” and the different explanations to this observation.
This lecture talks about:
· The difference between the time-weighted and dollar-weighted returns of a portfolio and their appropriate uses.
· The different risk-adjusted performance measures, such as Sharpe’s measure, Treynor’s measure, Jensen’s measure (Jensen’s alpha), and information ratio.
· The uses for the Modigliani-squared and Treynor’s measure in comparing two portfolios, and the graphical representation of these measures.
· The statistical significance of a performance measure using standard error and the t-statistic.
· The difficulties in measuring the performances of hedge funds.
· How portfolios with dynamic risk levels can affect the use of the Sharpe ratio to measure performance.
· Techniques to measure the market timing ability of fund managers with a regression and with a call option model.
· Style analysis.
· The asset allocation decision.
This lecture talks about:
· The common characteristics attributed to hedge funds, and how they differentiate from standard mutual funds.
· The investment strategies used by hedge funds to generate returns.
· How hedge funds grew in popularity and their sub-sequent slowdown in 2008.
· The fee structure for hedge funds, and the use of high-water marks and hurdle rates.
· Academic research on hedge fund performance.
· How hedge funds helped progress the financial markets.
· The liquidity of hedge fund investments and the usage of lock-ups, gates and side pockets.
· Hedge funds to private equity and mutual funds.
· Funds of funds and provide arguments for and against using them as an investment vehicle.
This lecture talks about:
· Equity-based strategies of hedge funds and their associated execution mechanics, return sources and costs.
· How macro strategies are used to generate returns by hedge funds.
· The common arbitrage strategies of hedge funds, including fixed-income-based arbitrage, convertible arbitrage and relative value arbitrage.
· The mechanics of an arbitrage strategy using an example.
· Event-driven strategies, including activism, merger arbitrage and distressed securities.
· The mechanics involved in event-driven arbitrage, including their upside benefits and downside risks.
· A numerical example of the following strategies: merger arbitrage, pairs trading, distressed investing and global macro strategy.
This lecture talks about:
· The difference between major types of private equity investment activities.
· The basic structure of a private equity fund and its sources and uses of cash.
· Private equity funds of funds and the secondary markets for private equity.
· The key characteristics of a private equity transaction.
· The key participants in a private equity transaction and the roles they play.
· Methods of funding private equity transactions.
· Issues related to the interaction between private equity firms and the management of target companies.
· Typical ways of capitalizing a private equity portfolio company.
· The potential impact of private equity transactions, including leveraged recapitalizations, on target companies.
This lecture talks about:
· The characteristics of hedge funds and the hedge fund industry, and comparison of hedge funds with mutual funds.
· The evolution of the hedge fund industry and landmark events which precipitated major changes in the development of the industry.
· The different hedge fund strategies, explain their return characteristics, and the inherent risks of each strategy.
· The historical performance trend of hedge funds compared to equity indices, and statistical evidence related to the strategy of investing in a portfolio of top performing hedge funds.
· The market events which resulted in a convergence of risk factors for different hedge fund strategies, and the impact of such a convergence on portfolio diversification strategies.
· The problem of risk sharing asymmetry between principals and agents in the hedge fund industry.
· The impact of institutional investors on the hedge fund industry and reasons for the trend towards growing concentration of assets under management (AUM) in the industry.
This lecture talks about:
· How proper risk management can itself be a source of alpha for a hedge fund.
· The limitations of the VaR measure in capturing the spectrum of hedge fund risks.
· How survivorship bias poses a challenge for hedge fund return analysis.
· How dynamic investment strategies complicate the risk measurement process for hedge funds.
· How the phase-locking phenomenon and nonlinearities in hedge fund returns can be incorporated into risk models.
· How autocorrelation of returns can be used as a measure of liquidity of the asset.
This lecture talks about:
· The role of third party due diligence firms in the delegated investment decision-making process.
· How past regulatory and legal problems with hedge fund reporting relates to expected future operational events.
· The role of the due diligence process in successfully identifying inadequate or failed internal process.
This lecture talks about:
· Bernard Madoff Investment Securities (BMIS) and its business lines.
· What is a split-strike conversion strategy.
· The returns reported on Madoff’s feeder funds.
· How the securities fraud at BMIS was caught.
· The operational red flags at BMIS conflicting with the investment profession’s standard practices.
· Investment red flags that demonstrated inconsistencies in BMIS’ investment style.
This lecture talks about:
· Three key initial conditions that helped spread of the economic crisis globally among sovereigns.
· Three ways in which the financial sector risks are transmitted to sovereigns.
· Five ways in which sovereign risks are transmitted to the financial sector.
· The activity of banks and sovereigns in the European Union during the 2002-2007 period leading up to the economic crisis.
· The activity of banks and sovereigns in the European Union during the economic crisis.
· How risks were transmitted among banks and sovereigns in the European Union during the economic crisis, giving specific examples.
· The economic condition of the European financial sector in 2012, and some possible policy implementation that can help mitigate the spread of future crises.
This lecture talks about:
· The events of the Icelandic debt crisis.
· The typical solvency and liquidity scenarios present at Icelandic banks in the periods leading up to the Icelandic debt crisis.
· How the weighting of shocks in short-term assets and short-term liabilities are adjusted in stress tests that account for a liquidity crisis.
· Several ways to improve the management of solvency risk at banks.
This lecture talks about:
· The history of normality in physical, social, and economic systems.
· The evidence of fat tails, the implications of fat tails, and explanations for fat tails.
· Examples of system-based interactions that can lead to fat tails.
· Non-normality in regards to asset pricing and risk management tools.
This lecture talks about:
· Heuristics and why using heuristic rules can be an optimal response to a complex environment.
· The advantages and disadvantages of using simple versus complex rules in a decision making process.
· Ideal conditions and situations where simple decision making strategies can outperform complex rule sets.
· The evolution of regulatory structures and regulatory responses to financial crises, and criticisms of the level of complexity in current regulatory structures.
· The effectiveness of simple and complex capital weighting structures in predicting bank failure given smaller and larger sample sizes, and the results of the study of FDIC-insured banks.
· The results provided by simple and complex statistical models in estimating asset returns and portfolio VaR over varying time periods and portfolio sizes.
· Possible solutions to manage or reduce complexity in a regulatory framework.
This lecture talks about:
· Crucial functions of a financial system.
· How accounting systems and protocols can affect how risk is presented.
· Significant issues related to risk in the savings market.
· The use of hedging versus raising equity capital as it relates to managing risk.
· The interaction between speculative behavior and financial innovation.
This lecture talks about:
· The chronology of the Flash Crash and the possible triggers for this event discussed in recent research.
· The data set, measurements, flags, and multiple regression models used in the study.
· The maximum drawdown, concentration ratio, and the volume and quote Herfindahl index.
· The results of the study including the descriptive statistics, the time series variation in fragmentation, and the determinants of fragmentation and drawdown.
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