Distressed Production Lending:

A Stochastic Response

The steep decline in commodity prices during the last twelve months means that borrowing base calculations, for Oil and Gas Production Financings, are likely to lead to distressed situations. Oftentimes, deterministic or static cases are used to evaluate the collateral supporting these production loans. However, the use of stochastic analysis, such as Monte Carlo Simulation, is far superior for lenders and borrowers alike.

Companies that produce oil and gas in the United States have increased their debt burden from $128 billion in 2010 to $235 billion as of the end of Q1 2015. At the same time, crude oil prices are at five year lows, and natural gas is off 35% since July 2014. Producers rely on capital to fuel their drilling and production operations, but lower realized prices means that the value of the collateral underlying their loans is now less valuable. When lending gets reduced, it becomes harder and harder for a producer to replace oil and gas assets as they deplete. It is a circular trap that can be one of the biggest challenges for an independent oil and gas company.

This white paper takes on this timely topic in four sections. First, it examines production lending in general and outlines its primary characteristics. Second, there is a discussion of the valuation techniques commonly used to assess the collateral and firms that support this kind of financing. Third, the paper goes on to contend that a market view is essential and that the only thing that matters at the end of the day are commodity prices and where they are headed. Finally, Monte Carlo Simulation (MCS), a stochastic analysis tool, is introduced as a far superior method for assessing the risk/return profile of production lending from the perspective of all constituents: Creditors, Lenders, Borrowers, and Shareholders.


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