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Managing Margin (Part 3) – The Importance of Transparency

In Part 2 of our series on the challenges of calculating margin, we discussed how data requirements and the support effort involved can be overwhelming. In this Part 3 of the series, we address the importance of transparency in a margin system.

Broker-dealers understand the importance of producing accurate margin calculations for their clients’ accounts, but they need to know more than just how much margin each client must post; they need to know why the margin system came up with a given result. This is especially true when markets are volatile and margin levels are changing rapidly. This need to know the why behind the margin numbers underpins the importance of having transparency in margin calculations.

Transparency leads to understanding

One of the key challenges of working with a margin system lies in understanding how its results were actually generated. Calculating margin is a path-dependent process and the outcome depends on the path the analysis takes in applying rules to a portfolio’s positions. When defending the results, a client relationship manager often has to figure out which “branch” the margin system chose, i.e., were regulatory or house rules applied? This allows clients’ questions to be answered based on fact, rather than speculation. 

To explain margin results, one must be able to show how the calculations proceeded, which inputs were used, and where the system branched off to one set of rules or another. While this may occasionally reveal that a calculation went awry or a component failed, more often than not it proves that the result is entirely consistent with the agreed-upon margin plan and up-to-date rules. It also allows “what if” scenarios to be considered; for example, would changing X or Y make the portfolio more capital efficient?

Cross-client margin reports are also important for broker-dealers to generate. When multiple clients are exposed to the same risk, the firm has greater exposure in that area. Although clients put up margin that should protect the firm, if volatility suddenly spikes for a given factor and the posted margin is insufficient, the firm could be exposed. Since haircuts differ across clients, knowing what types of clients (e.g., stat-arb, long/short hedge fund, etc.) are behind a given risk exposure is useful.

Attribution: Another level of transparency

Attribution is the process of determining which exposures have the greatest impact on a margin calculation. It is tempting to think that one can do this simply by sorting the margin per individual position, from largest to smallest; however, that approach would be insufficient because the amount of margin does not reflect offsetting exposures. Similarly, sorting by quantity (notionals) does not reveal offsetting positions. Sorting by the VaR of each exposure is also inadequate because VaR is an absolute value that provides no insight into how long and short positions interact. Sorting by the VaR for a given factor has some appeal – for example, if there is a concern about a spike in oil prices, VaR would show the sensitivity to oil prices. However, it would not show whether the portfolio is long or short that factor. A thoughtful margin attribution analysis can show what drives the total margin. Unlike VaR, which is not additive (the sum of the VaRs of individual exposures does not equal total VaR), Imagine’s margin attribution is additive – the sum of the margin values attributed to specific factors equals the total margin.

Transparency’s real-world implications

When evaluating a margin system, the level of transparency that the system will be able to provide the organization is vital not only for clients and regulators but for internal teams too.

Here are some real world implications to keep in mind:

  1. Broker-dealers have thousands of accounts for which clients must post margin, and transparency in margin calculations is critical to customer service. Clients are requiring more in-depth explanations about margin calculations so that they can make their portfolios more capital efficient. Responding to margin questions with clarity helps to keep clients satisfied. For broker-dealers with private client portals, the ability to provide some of this information to their clients online can be a significant advantage.
  2. Broker-dealers must be able to defend their margin numbers to their clients and show that the rules and inputs are up-to-date. This often requires extracting various Exchange rules. A transparent margin system will allow the client service team to do this. 
  3. Some teams within the firm just want the “headline” margin number; others want the details of how it was calculated. Transparency with respect to exchange rules, haircuts, securities data and positions allows for flexibility in reporting that is needed to satisfy both. 
  4. Prioritizing transparency in margin calculations can improve how the firm shares information internally. For example, transparency must extend to the security master database, because it is important to confirm that correct terms and conditions were used in the calculations when justifying margin numbers.
  5. A broker-dealer’s internal risk management, sales and client relationship managers, and operations teams need the margin system to be transparent so that they can answer questions such as, “what is the peak intra-day or multi-day margin for this client?” This allows the firm to defend and explain margin numbers before revealing them to clients.

The Imagine platform’s margin system, designed around the concepts of Margin Plans, Margin Rules, and a scalable structure based on criteria, values and overrides, is flexible and adaptable, and can offer truly astonishing improvements that can deliver tangible benefits to those who rely on margin calculations to keep critical functions operating smoothly. For more information about how Imagine’s approach could help your business, please contact us.

Follow us on LinkedIn to be alerted about the next article in the series on workflow-oriented margin engines.

The Margin Series

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