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    Risk Management for Non-Quantssm

    June 17 - 18, 2014, Charlotte         July 15 - 16, 2014, Chicago

    Registration Fee: US$1,895.00      Register  

    Beginner/Intermediate Level, 14 CPE Credits
    Instructor: Prof. Bernard Donefer
    Hours: 9:00 am - 5:00 pm; Registration/Breakfast begins at 8:30 am
    New York City Location: Club Quarters Hotel, 52 William Street (off Wall Street) Directions
    Chicago Location: Club Quarters Hotel, 75 E. Wacker Drive (off Michigan Ave) Directions
    Charlotte Location: Holiday Inn Charlotte - City Center, 230 N. College St (Uptown) Directions 

    Bernard S. Donefer, a Wall Street veteran and now professor at NYU Stern and Distinguished Lecturer at Baruch CUNY graduate business schools, has created a unique 2-day seminar covering the essential topics of risk management, requiring only basic high school math skills This course has been given at the SEC and Federal Reserve Bank in Washington DC, as well as to hundreds of major financial firms in New York, Chicago, Boston, Los Angeles, Canada and the UK.

    Who should take this seminar?

    If you need to read and understand risk reports, interact with risk managers or just want to broaden your expertise in a critical skill, this is the seminar. It is not aimed at financial engineers looking for hedging and trading strategies, but for those managers responsible for monitoring, measuring and controlling risks. It is a pragmatic course for practitioners who must deal with or are regulators, board members or senior management. Portfolio and asset managers, traders, bank, hedge fund and securities firm management, compliance officers and back office operations staff all need a good understanding of risk management concepts and their regulatory and technical drivers.

    Anyone who needs to answer the question: If today is a bad day, how much can we expect to lose? Is our return appropriate to the potential losses? What are the sources of the risk and what could I be doing to better control those risks?  

    What will you learn?

    • Review the underlying assumptions in the efficient markets hypothesis and statistics and why these may be misleading and lead to under estimating risk.  

    • The risk components and measurements in market, credit, liquidity, model and operational risk.  

    • How Value at Risk, (VaR), is computed and, more importantly, what questions to ask to ensure you understand its implications to your portfolio.  

    • Expect Black Swans, how to use Extreme Value Theory (EVT), back and stress testing to prepare for worst case scenarios. 

    • CDOs and CDSs, what are they and how did they precipitate the market crash.  

    • What are the regulators looking at? What are the recommended best practices by the Basel II Accord? How to look at risk management as an enterprise activity.  

    Several cases will be examined and implications identified. Excel spreadsheets will be provided so that participants can review concepts demonstrated in class. All class notes and readings are provided, including references to additional sources (books, articles and websites). 

    Topics to be covered include:

    DAY 1

    Background

    • What is the efficient market hypothesis and how does it drive risk management concepts?

      • CAPM, alpha, beta, behavioral finance  

    • Review of underlying statistical and probability concepts 

      • Normal distributions, standard deviation, correlation 

    • Financial industry trends 

    • Introduction to risk management. What risks can we manage?  

      • Categorize and define market, credit, liquidity, model and operational risk 

      • Importance of context in defining risk 

    • Barings Bank case – How a sophisticated 225 year old international bank was brought down. What happened, how it happened and what lessons can we learn from their experience. Compare to Societe Gernerale and recent $7B loss and new rogue trader prevention policies. 

    Value at Risk Concepts

    • How do we measure risk? Market volatility?  

    • What is Value at Risk (VaR)? How to calculate it for a single security and portfolio, Marginal and incremental VaR 

      • Calculating VaR historically and parametrically 

        • Excel exercise to graph volatility, calculate VaR  

      • Using Monte Carlo simulations 

        • Excel exercise to create a Monte Carlo simulation of stock prices 

    • Aggregating VaR over different time horizons Risk Adjusted Return on Capital (RAROC)

    Advanced Value at Risk

    • Back testing and stress testing - how good is your VaR model?

    • Calculating multi-asset (portfolio) VaR

    • VaR decomposition – using marginal VaR to identify the impact of changes to a portfolio   

    • Excel exercise 2 asset VaR and VaR decomposition

    • How to use this data to manage a portfolio’s risk

    • Baring’s revisited – What VaR would tell us about Nick Leeson’s portfolio  

    • Comparing VaR calculation methodologies 

    Extreme Events – Worst Case Situations

    • Fat tail (worst case) analysis  

      • GARCH  

      • Extreme Value Theory (EVT) 

    • Back testing and Stress testing 

    • Model risk 

    • What’s wrong with VaR? 

    DAY 2

    Regulatory Environment

    • Why regulate? Who is being protected? 

    • Basel II Accord – What is it? Who created it? Whom does it impact?  

    • Capital requirements 

    • How do we satisfy its requirements - best practices? 

    Hedge Funds

    • Risk Measures 

      • Sharpe, Sortino, etc.

    • Disclosure best practices 

    Liquidity Risk

    • Liquidity risk is the hidden killer – asset and funding liquidity

    • Impact of leverage 

    • Market impact and trading liquidity 

      • Market fragmentation and dark pool issues 

    • Long Term Capital Management case – How did a firm filled with experts and two Nobel Prize winners almost bring down the world’s financial systems? What new lessons have we learned? 

    • How Bear Stearns and Lehman Bros were driven by liquidity risk 

    Credit Risk

    • What is Credit Risk? What are the different types? 

    • Estimating probability of default (PD) 

      • Subjective – CAMEL or the 5 C’s 

      • Credit rating and ratings based models 

      • Objective – Z score, CreditMetrics, KMV, Kamakura, CDS based 

        • Merton (stock price) and Jarrow (interest rate) based 

    • Basel II capital requirements for credit risk 

    • Credit default swaps (CDSs)  

    • Collateralized Debt Obligations (CDOs)  

    • CDS and CDO impact on the economy  

    Multifactor Models

    • Risk measurement with factors other than asset price 

    Operational Risk

    • BIS definition of oprisk 

    • Control Self Assessments (CSAs)

    • Key Risk Indicators (KRIs) 

    • Basel II Op Risk best practices

    • Example of an op risk system

    • Using Six Sigma and Balanced Scorecard techniques in op risk management 

     Wrap up, summary and sources of further information.