White Papers Managing Forward Curves in a Complex Market | Page 2

Introduction
Any company that owns commodities, either through production or merchant activities, needs to know not only the
current value of those commodities based on market prices, but also needs to develop a view of the future value
of those commodities during the time that they are projected to be held in inventory. Additionally, agreements to
purchase commodities in the future must be accounted for, not only at their agreed or projected purchase price,
but also during their anticipated holding period.

Commodity prices are constantly changing and are
driven by market forces that are virtually impossible
to predict with any degree of certainty. As such,
accurately forecasting costs and price exposures is
difficult at best, and particularly so now, given the
rapidly changing supply and demand patterns that
define the global commodity complex. Huge growth
in demand for all commodities in Asia, the rapid rise
of agricultural exports from developing countries in
the Asia-Pac region, and the shale revolution that
is driving unprecedented growth in US oil production, are all examples of the new dynamics that have
fundamentally altered price formation in markets
around the world. In this globalized and increasingly
interconnected market-place, which is being constantly buffeted by economic uncertainty, predicting
future prices is more difficult, but perhaps more important, than ever.

Along with ever shifting supply and demand
patterns, new markets, trading hubs, and storage
facilities have opened, creating new trading locations where none existed just a few short years ago.
Though many have already become recognized pricing centers, others are, and continue to be, rather
illiquid, with few transactions and little knowledge in
the broader market as how to price those locations
on a future basis.

Even in areas and markets that have had a long
and sustained history of prices, new productive regions (such the massive growth in natural gas production from the Marcellus Shale in the Northeast
US, for example) can create a lasting and dramatic
© Commodity Technology Advisory LLC, 2014

change in futures prices. Future price prediction then becomes difficult
as the sudden change in fundamentals produces prices that are uncorrelated from historical activity.

With these market changes, the ability to interpret market activity
and measure the future impact of anticipated developments becomes
more imperative. Defaulting to a common exchange price curve or attempting to simply project historical prices forward is insufficient in this
dynamic environment as it ignores the both the global impact of changing supply and demand patterns and the growing inter-relationships
amongst commodities and markets.

While some wholesale spot markets that trade on exchanges,
such as Henry Hub’s natural gas contract, are well established, highly
liquid and somewhat seasonally predictable, the majority of commodity
trading locations and markets around the globe are not, and exchange
data is either not directly reflective or is unreliable. It’s these imperfect,
inefficient and sometimes insufficiently liquid wholesale spot markets
where the need for careful and thoughtful modeling of future prices, or
the “forward curve”, becomes an essential exercise in risk management
and financial reporting for commodity trading companies.

In this paper, we’ll examine the complexities associated with the
development, and the specific uses, of forward price curves. In addition, we’ll review a sophisticated technology available from DataGenic –
the Genic CurveBuilder - that can automate and reduce the complexity
associated with the development of forward price curves.