Hybrid Consulting Group, Ltd. / Commodities Practice

Case #1
A major trading house approached Hybrid Consulting Group for quantitative analysis to support its new energy trading operations. The firm planned to make a market in correlation sensitive energy derivatives products. That is, the value of these products were very sensitive to the correlations between heating oil, gasoline, and crude oil prices. In response to the client's request, Hybrid undertook an exhaustive analysis of these energy market correlations. Hybrid utilized advanced econometric methods to estimate time-varying correlations that depend on prevailing market conditions (such as the spread between gasoline and crude oil prices). Hybrid also developed an algorithm to forecast the relevant correlations over any time horizon. The client has implemented this methodology in its new energy trading operations.

Case #2
A major electric utility was dissatisfied with existing methods for pricing electricity derivatives, including electricity forwards, options, and structured supply contracts. The utility recognized that traditional pricing approaches applied in financial markets (and some other commodity markets) were inappropriate for electricity due to the unique characteristics of this product. Hybrid proposed and implemented a novel valuation and risk measurement approach that addresses the utilities concerns about traditional pricing approaches. The Hybrid approach (described in our Electricity page on this web site) exploits the transparency of the fundamentals in the power market and explicitly models the effects of the non-storability of power, the seasonality of demand, and the non-linearities in power prices. Hybrid used this model to create a customized derivatives pricing software for this client. Hybrid is currently working with the utility to adapt this pricing methodology to a wide variety of issues facing the firm, including the pricing of generation and the valuation of complex structured physical supply contracts.

Case #3
A major trading house was interested in using a generalized flexible time series model to capture the time varying variance, skewness, and kurtosis of returns for various assets and commodities. Although their model of choice had the advantage of being general and capable of capturing salient featuers of the data, solving for the conditional distribution of the asset price or total returns associated with arbitrary dates in the future proved to be extremely difficult.
Hybrid Commodities Practice was approached to provide a solution to this problem. Although substantial academic literature exists relating to the undconditional moments, very little research exists to provide a solution for the moments which are most relevant to traders - the moments which exploit known information today. Using rigorous analysis and advanced statistical theory, Hybrid Commodities Practice provided a solution to this problem, and outlined in detail, a combination of numerical and analytical procedures to solve for the conditional distribution of asset prices or returns, for any arbitrary date in the future, based on the original model.