Risk Management in a New Market Era

By David Newton, CEO, Amphora, Inc.

There are many opportunities to realize returns through improved risk management along the petroleum supply chain. All energy market players need the right data at the right time for faster and more accurate decisions on fast-paced transactional opportunities. With the extreme price volatility and high trading volumes in the liquid hydrocarbons market, software tools must improve market participants' trade floor knowledge of stock levels and feedstock/product qualities, even as they also address shorter-term trades and new deal structures. Optimizing stock levels for risk-free margins in storage plays, blending for better product value, and scheduling flexibility for commercial and arbitrage opportunities are key priorities. Better coordination of trading and logistics will help participants stay ahead of the market.

Dynamic Limits

The recent financial market upheaval illustrates the challenges posed in this complex new environment. Energy derivatives trade around illiquid markets with high volatility and are also exposed to underlying impacts of currencies and interest rates. Traditional risk management practices have focused on placing limitations on maximum exposure to identify and track opportunities and threats. However, there are many cases where the business processes to manage these limits are not updated to the complexity of today's marketplace – for example, when oil moves $5 or $10 per barrel in a single day. Similarly, setting static limits on outright or spread positions may restrict market participants' ability to squeeze out margin when the opportunity presents itself.

Market participants must be able to combine actionable intelligence with detailed P&L attribution and separation of model components. Specifically, they must have the ability to accurately attribute P&L changes resulting from a variety of factors including those arising from market curve shift, deviations in delivered product quality, outturn losses, timing, additional costs, new trades, hedging and pricing events, and so on. Given this, a dynamic set of limits which react to changes in market price levels, changes to volatilities and other factors such as currency rates, interest rates and credit ratings is essential.

Combining deep P&L attribution with the ability to set dynamic limits allows companies to better understand where money is being made or lost. Taking this further, the ability to perform "what if" and hypothesis testing around deal terms, risk, scheduling, credit, etc. is of critical importance for understanding the impacts of different scenarios on position, P&L and true cost basis. Examples would be to estimate changes in quality on supplies from a vendor as well as P&L trends on particular blending transactions, yield matrices, or credit term flexibility to certain counterparties.

Contract Standardization

Increasing pricing complexity around crude and refined products transactions requires greater scrutiny of the terms of every deal. However, a large percentage of physical trades have similar terms across counterparties, many of which book-out or net-out and never go physical. If data transfer standards are adopted, these deals can lend themselves to automation. The challenge to sharing this data is in reaching agreement between counterparties on a wide swath of physical contract details. This is why the use of industry data integration standards is essential.

As market contracts get standardized, either through clearing on the exchange platforms, direct exchange trading, or subscribing to industry organizations such as ISDA or LEAP, the multiple combinations that must be managed are reduced. Further, new CTFC regulatory policies that push for stricter position limits on energy futures contracts may well require going beyond the current documentation requirements calling for new levels of reporting flexibility and transparency.

Automated Data

There is already a key part of the market that has provided full electronic information exchange. The ICE, Nymex and many brokerage houses today already have established standards for providing the market platform and trade information to their customers for the most liquid instruments. Most of these data flows are already tested and secured, and can be configured to enable significant automation of executed trades. Other areas for automation are letter-of-credit and treasury management, specialized scheduling and tank management, specialized risk systems for value at risk and cash flow at risk, and specialized tax management systems.

Market participants need actionable intelligence should a trading spike breach basic trading limits. The solution is to combine detailed P&L attribution, splitting out the components of the model used to calculate the measure, with a dynamic set of limits that better coordinate all functions in the petroleum markets. The resulting flexibility will accommodate new deal structures and create attractive new commercial and arbitrage opportunities for the market participants who employ these practices.

David Newton can be reached at info@amphorainc.com or +1 713 339 5600.

 

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