Risk Management

Overview of Risk Management

The Tasks of a Market Risk Manager

A risk manager is tasked with measuring so many risks. Their mandate is broad and wide reaching: from measuring the size of the book to determining the right collateral is posted. The primary goals of Risk Management will help us drill down to the more granular risks to pay attention to:

  • Defend the castle would be the overarching statement
  • Defend firm’s market share
  • Protect firm’s profit margin
  • Secure budgets
  • Maintain stabilized pricing in market making operations
  • Eliminate surprises

Work closely with your analysts as well as sales people so you have all information on every trading desk, relationship manager (loans), client or prospect (asset purchases or mgmt.) and able to make final decisions.

Setting Up Risk Management Controls

  • Trading Desk (Business Unit) Level Policies Defined with respect to
    • Funding costs
    • Position limits
    • Risk limits: Define Frequency and process for:
      • Stress Testing reported VaR figures
      • Back Testing reported VaR Figures
  • Designing A Hedging Policy:
    • Approved Hedging Products
    • Maximum Tenor for Products
    • Maximum amount which can be unhedged
  • Schedule External Audits and Benchmarks
    • Hire an auditor or Independent Consulting Firm
    • Can provide good information for regulators
    • Can keep risk managers up-to-date on industry trends
  • Sales Desk (Business unit) level Policies Defined with Respect to
    • Customer Compliance
    • Risk Management should have a redundancy point of contact to ensure all clients documentation is in order; salespeople are following the prescribed workflows & credit department is receiving the information from client as agreed.
    • Sales Person Compliance: Pitchbooks, emails and other client correspondence are approved by Compliance. A file should be maintained at Risk Management Level for ease and facility if a file is needed for an investigation. This allows risk management to operate privately without divulging an investigation is in process.
  • Create an Internal Risk Management Committee
    • Each task above is apportioned to a person or group
    • Regular meeting schedule of all participants locally
    • Head of local Risk Management Committees meet regularly to share what they’ve learned locally
    • Risk Managers come from a wide array of areas of an institution. Make sure your team includes the expertise and backgrounds your firm needs.
      • Junior staffing can be found from other risk mgmt. areas for career growth. These positions should be filled internally, if possible.

This overview provides a very shallow overview of implementing and operating a Market Risk management group.

Risk Management

Risk Management is, at last, getting our industry’s full attention. I hope that we can move forward and engage in constructive dialogue with our regulators and remain compliant. Risk Management encompasses several areas of the derivatives value chain. We’ll cover each area in turn.

Market Risk

Market Risk is calculated using Value-At-Rick or VAR. VAR calculates a probability statement such as: “I’m x% confident we won’t lose more than V dollars over the next N days”. It allows institutions to have a single number to define their market risk given the parameters used. Regulators require banks to report a 99% confidence level over the next 10 days. BIS requires the banks to have three times their 10 day VaR in capital.

  • “The Bank is 99% confident we won’t lose more than $100 million over the next 10 days.”
  • The Bank is 1% confident the Bank will lose more than $100 million over the next 10 days.

Bank Trading desks use the 99% & 95% VAR number for 1 day (tomorrow).

  • 99% number because it’s consistent with bank regulators, but they care about market moves for one day.
  • Bank trading desks are 1% confident they will lose more than VaR 1 day out of 100. (1/100 = 1%)
  • 95% confidence figure because that’s when the hedge funds will look to scale back positions.

Hedge Funds use a one day 95% confidence figure.

  • Hedge funds typically use a 95%, 1-day VaR, which they post on their websites.
  • In other words, they expect to lose more than their VaR figure once a month (1/20 = 5%)

So bank traders want to know how the other side of their trade might respond if the market moves big the next day. Although most money center banks now use Monte Carlo simulation not normal distribution. But using volatility (the square root of variance which presume the % returns are normally distributed) is easier to conceptualize.

How is Value at Risk Calculated?

There are three accepted methods of calculating VaR: For sake of brevity we will only discuss variance-co-variance in detail.

  1. Monte Carlo Simulation
  2. Historical Simulation
  3. Variance Co-Variance Method

Historical Simulation

Historical simulation uses the ACTUAL returns of the assets in which the bank has positions. They typically use the previous 200–500 days of actual price changes. EXAMPLE: using the last 200 days and calculating the daily returns they give you the actual 180th worst loss (given the Bank’s current position). Whatever loss is the 180th worst loss, while be reports as their VaR. The 180th worst loss out of 200 changes gives you the 90% confidence, one day VaR (180/200 = 90%)

Monte Carlo Simulation

The easiest way to view Monte Carlo Simulation begins with thinking of it as similar to Historical Simulation. EXCEPT, Historical Simulation implies the actual 180th worst loss in the past 200 days can re-occur on the exact same date over the next time frame (10 day or 1 day). Monte Carlo uses a random number generator and uses 10,000 “trials” (you can view this as daily changes) to estimate the price return of the asset at the end of the analysis horizon (10 or 1 day). However, you will find the detailed process for calculating VAR using Monte Carlo Simulation here.

The Variance Co-Variance Method

The variance-co-variance method uses the historical volatility of the asset over the past X number of days (typically 200 – 500 days).

Historical Volatility & Value At Risk

Perhaps you recall the bell-shaped curve. If not, let’s run through it quickly now: Normal distribution presumes the mean of the data series is zero. The resulting volatility number you hear in the market (i.e. , VIX) is the annual volatility. We can use the annual volatility to make probability statements which are described as standard deviations from the mean:

  1. STDEV = 68.3% of all occurrences, which is roughly 2 out of every 3 years
    • In forecasting probable price changes in the future we say:
    • The asset will be up or down 1 stdev or less 2 out of every 3 years.
    • The asset will be up or down MORE THAN 1 stdev 1 out of every 3.
  2. STDEV = 95.4% is roughly 19 years out of every 20
    • In forecasting probable price changes in the future we say:
    • The asset will be up or down 2 stdev or less 19 out of every 20 years.
    • The asset will be up or down MORE THAN 2 stdev 1 out of every 20 yrs.
  3. STDEV = 99.7% which is roughly 299 years out of every 300
    • In forecasting probable price changes in the future we say:
    • The asset will be up or down 3 stdev or less 299 of every 300 yrs.
    • The asset will be up or down MORE THAN 3 stdev 1 out of every 300 yrs.

If you look at the N= file attached here, you’ll see a 99% confidence interval on a normally distributed as is ~ 2.33 standard deviations.

Adjusting Annual Volatility to a Shorter Time Frame

We can adjust the annual volatility to a shorter time frame by adjusting the annual figure by the square root of time. Let’s calculate the daily VaR, using the following example:

EXAMPLE: long a single asset valued at 100 million.
  <200 day historical volatility is 25%.
  For 10-day volatility we need to adjust our annual number by the SQRT of 365/10 as there are 365 CALENDAR days in a year. PLEASE NOTE: WE ARE NOW USING CALENDAR DAYS.
  10-day Volatility = SQRT () = 6.0415
  10 day Vol = .25 / 6.0415=4.303% PER 10 calendar day period.
  We now need to adjust our daily volatility figure to reflect 2.33 stdev’s
  4.303% * 2.33 = 9.97%
  $100 million * .0997 = 10- day 99% var of $9,997,000
  “I’m 99% confident we won’t lose more than $9.997 million on this position over the next 10 calendar days. ”

Problems with VaR & Possible Solutions

It may be obvious that VaR focuses on the likely losses, but says little about the black swans. For a while we performed back testing and stress resting to ensure our VaR variables were correct. But notice, even if the volatility estimate was correct, the furthest I could go is “I’m 1% confident I’ll lose more than VaR tomorrow”. It could not tell me the size of that tail risk. For this reason, VaR has been challenged and looking to be replaced by Potential Exposure. This and other Trading Desk related risk measurements will come under the umbrella of Fundamental Review of the Trading Book (FRTB).

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Counterparty Credit Risk

Measuring & Assigning Counterparty Credit Risk Lines

In simple terms, counterparty credit risk is the risk of a customer (counterparty) defaulting on payment. There are levels of default, some easier to cure than others. A technical default is more easily cured than a straight “failure to pay” simply because the counterparty can prove receipt of said funds in a short time period. The delay in payment could be the result of human error, a failure to receive funds from their counterparty, etc. A “failure to pay” is a straight default where the counterparty can provide no assurance as to when they will be able to pay.

Counterparty Risk of Uncleared Derivatives

For uncleared swaps, counterparties will operate as they’ve done since the 1980’s. The counterparties had risk to each other — with the counterparty “in-the-money” having the risk that his counterparty be unable to meet their obligations. The mitigation of this risk will be managed in a similar manner, using similar documentation. You can read the details of uncleared documentation here. [ NEED URL/LINK ]

Counterparty Risk of Cleared Derivatives

The counterparty risk of cleared derivatives more fully mitigates counterparty credit risk, especially from the client’s point of view. For the individual clearing swaps, they are insulated against contagion of other clearing clients defaulting. For the clearinghouse as long as they’re fully operational, have a robust Risk Management Committee and meet with other CCP’s regularly they are able to provide this risk mitigation. But because of the number of moving parts (many dealers and many clients), the probability associated with default is larger.

Credit Risk

Measuring and Managing the Credit Risk of a Bond Portfolio

Credit risk is different from counterparty credit risk. Credit Risk relates to the default of assets in your portfolio.

  • Non-payment of interest on a note or loan
  • Non-payment of principal of a note or loan

When assigning a Credit Risk limit to a bond portfolio many risks are taken into account. Each risk is measured separately and as a portfolio of the same risk in other bonds.

  • Liquidity risk: is the asset liquid enough to trade; as bonds age, they become less liquid, the bid-ask spread gets wider. It will cost more to reverse your positions.
    • Measured as bid-ask spread / 2
    • The % of the outstanding bonds that are freely trading in the open market.
  • Concentration risk: risk your client has too much risk in one market sector
  • Collateral risk: especially under agreements which allow for re-hypothecation (to be lent), are carefully measured and care is taken not to post collateral of great value (the on-the-run note, the most liquid note in a class, etc. )
  • Call/Put risk: A callable bond will be called if interest rates go down or the credit risk of the corporation has improved significantly. The right to call the bond from the bond holders has a value, or premium. While we can use some of the same variables to price the bonds embedded call.
    • Typically a call is exercised if it’s “in-the-money”, the price of the bond is above the strike price.
    • In a corporate call, the corporation may not save enough money to call the bond making this variable very difficult to value
  • The Call feature’s value is often financed by the Put Feature
  • The Put feature allows a bondholder to “put” the bond back to the issuer and request their principal money back.
  • The Put feature is typically used to finance the cost of the call. So you will often see both features used together.
  • The Call feature requires the owner to replace the bond in their portfolio.

The Outline of Operational Risk

Operations Risk & the Derivatives Value Chain

Operational Risk speaks to any risk along the value chain. They are the errors which typically combine human error and misunderstanding.

Areas of Operational Risk

The areas known as “operational” are any risk which can be ascribed to events which placed the institution at risk of fine(s) or censure.

Errors Found During Regulatory Examinations

Banks, Broker-Dealers, Insurance Companies and other financial services related entities are examined by their Regulatory Oversight Organizations. Regulatory Examinations are vital to an organization. Personnel is given strict orders not to answer any questions and is given the name and contact information to whom they should refer the questioner. Eye contact was limited and the examiners were given their own space from which to work. The examiners were not allowed in the trading rooms or on floors where senior management would greet and meet with clients.

Errors resulting from Lack of Follow-Up

If certain notices to “cure” are given by regulators, the letter includes a period during which they were required to cure the issue. For example, if credit work had been delayed and was listed by regulators to review the entity and provide the updated report to the examining regulator. The cure list could include anything from credit reports to the number of time stamps on an execution ticket.

Errors Resulting From Human Error

Other types of risk are pure human error. For example:

  • Improper Affirmation of a contract
  • Non-Receipt of a signed confirmation
  • Error in static data
  • Error in cash accrual
  • Error in Documentation

Ways to Correct Operational Risk

Integrated Training, as taught by MHDS is an online or blended program given to the entire value chain. We pay particular attention to those job functions that worked directly before or after a specific function. For example, each middle office job function role play so that affirmation understands the process of submitting the trade (pre-affirmation) and ensuring receipt of a signed confirmation (post-confirmation). This allows all three functions to introduce redundancies and work as a well oiled team.

The Difference Between Cleared & Uncleared Documentation

The ISDA Master Agreement

The ISDA Master Agreement is an overarching contract covering all derivatives contracts with a customer. Even from the first iteration in 1992, most of the terms were standardized. Today in a post Dodd-Frank era The ISDA Master Agreement for Uncleared Derivatives is even more standardized that before.

Specified Entities

On that basis a Specified Entity is an affiliate of a counterparty which is covered by the Master Agreement for Cross Default in the event of bankruptcy or default of a subsidiary. The fifth Termination Event is called Credit Event Upon Merger (Section 5(b)(v) in 2002 ISDA Master Agreement). The aim is to draw in those members of your counterparty’s group (such as its parent or asset rich fellow subsidiaries) whose relationship is so close to your counterparty that if an Event of Default happened to them it would be very likely to affect your counterparty seriously too. A specified entity is one that is crucially important to the Parent Company or financially substantial companies to a Holding Company:

  • Sometimes these Specified Entities are specifically named and sometimes a general term “Affiliates” is used.
  • “Affiliates” essentially means any other company in your counterparty’s group. Specified Entities can be proposed to apply to all the above sub-sections or just to Section 5(a)(v) (Default under Specified Transaction).

In all cases which Specified Entities apply to each party is a credit decision. Specified Entities is a way of collapsing down all transaction at once. This can provide an advantage to the customer who may have profitable swaps on one entity and losing swaps in another. Cross default may mean the counterparty doesn’t have to pay a loss it cannot afford. Big companies are often able to negotiate that Specified Entities will not apply.

  • Smaller ones may be able to limit Specified Entities to Material Affiliates only. This would have to be defined but could cover those which account for, say, 15–20% of group pre-tax profits or assets.
  • Credit Support Providers are automatically included in these four Section 5 events and do not need to be named separately as Specified Entities for them.

While Specified Entities are not always needed, a counterparty which is a corporate holding company whose main financial substance of the corporate’s holding company is in those subsidiaries, the bank’s credit officer may want them as Specified Entities.

The Addendum A

The Addendum A includes very specific terms and conditions.

The Standard Collateral Support Annex (SCSA)

Another document which has become more standardized is the SCSA, which spells out the threshold level when collateral will be required. Today this includes:

  • Derivatives Risk: because it’s a leveraged product, the risk is always much greater than the notional amount of the contract. As time passes the derivatives line needed changes.
    • The amount of derivatives line required depends on the contracts years to maturity
    • he notional amount of the contract
    • The time difference between the pay leg and receive leg of the contract
      • i.e., A bank paying every quarter and receiving every six months has more counterparty credit risk than a contract where the bank is receiving quarterly and paying semi-annually.

The Standard Initial Margin Method (SIMM)

The SIMM codified uncleared derivative contracts and made them all more standard so as to place all counterparties on the same level.