Dec 1, 2014

Visualizing Trade EVA: Best Practices for Analyzing Trade Profitability

With regulations such as Dodd-Frank and Basel III being rolled out and implemented in different phases, today’s derivative practitioners continue to face growing pressure on their current business models.

Financial institutions are working overtime to address an onslaught of costs associated with trading derivatives. For example, in addition to calculating fair value, banks need to account for what many practitioners fondly call the XVAs (a term which includes CVA, DVA, FVA and other adjustments) to truly capture the costs of conducting derivatives business.

Given the current environment, financial institutions need to adopt a more integrated and holistic approach for assessing trade profitability and allocating capital to their businesses. It is no surprise that with the smorgasbord of costs and adjustments clearly impacting the bottom line, we’re seeing a growing trend amongst practitioners introducing the concept of Economic Value Added (EVA) —a global profitability measure—into the derivatives lexicon.

So, just why has the concept of Trade EVA become so important? Well, first off, Trade EVA enables us to measure and attribute risk, funding and capital costs to each individual trade.

Visualizing EVA Analytics

In order to support the concept of more holistic decision making, below we highlight several concrete examples involving the ‘visualization’ of EVA analytics. A Trade EVA Framework, as shown in Example 1., enables us to quantify all of the costs related to a particular trade and to tie all of these costs back to the client margin and thus, net profitability of the trade.


Example 1. Trade EVA and the Development of a Trade Profitability Framework



The Trade Profitability Framework Brings the XVAs into Trading Decisions: A trade that is profitable at first glance can turn out to be a loss-making trade when all costs are incorporated.

In fact, the Trade Profitability Framework and Pricing Stack analysis in the diagram above, enable us to attribute portfolio-level risk, margin and capital analytics back to the trade. In this example, we see how a trade with a high customer margin (top bar) can become a net negative EVA (bottom bar) trade due to various costs attributed to this trade. For this trade, we see that FVA and Cost of Regulatory Capital are quite large and eat into the client margin in a significant way.

This type of breakdown obviously enables us to also ask and answer additional questions for making more effective pre-trade decisions. For example, one could ask “How can we structure this trade to create a positive EVA outcome?” which may lead to different trade terms, CSA terms, break clauses or other adjustments to the position.

Example 2. Exposure Profile



Since all XVA measures depend on exposure profiles, this is often one of the most important and basic views that traders and risk managers need to have. Also, while some of the XVA adjustments and measures can be complex and difficult to understand—the Exposure Profile is something that almost everyone intuitively understands as the matrix of future prices over time and over the number of Monte Carlo paths in the simulation.

The Exposure Profile provides a method of analysis in which traders and risk managers can drill down and really see how a trade MtM can evolve and how the different XVA measures come about. This type of analysis tool is intuitive and easy to use—allowing one to drill down, debate and discuss trade profitability intelligently.

Example 3.  Pricing Stack Evolution - Time Profile

Another useful view is the Pricing Stack Evolution or Time Profile analysis below. This type of chart provides insights into how a trade EVA evolves over time. For this specific profile, we can observe that in 2015 and beyond, the trade EVA becomes positive. Also, we can observe that while the Client Margin is linear, the FVA and CoRC measures are non-linear and falls more rapidly. Again, insights and analytics such as these open up discussions on how to create positive EVA from the outset.

Viewing derivative trade profitability from the macro-level is no longer sufficient, given today’s highly regulated, lower ROE environment. The integration of risk and capital intelligence into trading— including intra-day or real-time/pre-trade analysis is one of the most important ways to achieve efficiency for a derivatives operation.

Using integrated analysis tools with drill down capabilities is essential for effective decision-making in today’s complex derivatives trading arena. Integrating risk, collateral and capital costs into the front office opens the gateway for real efficiencies to be created within a derivatives operation.

For more detailed analysis, read the recently published whitepaper:

Integrating Risk into Pre-Trade Analysis: Practical Ways of Bringing Credit, Liquidity, Funding & Regulatory Costs into an Integrated Profitability Framework authored by Numerix SVP, Satyam Kancharla.

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