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WEATHER FORECASTING AND ENERGY TRADING

NOTES FROM THE TRENCHES April 15, 2010

Vincent KaminskiRice University

Jesse H. Jones Graduate School of Business

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Outline

Energy Impact on the Commodity Markets

Notes from the Trenches: My Interactions with Weather Forecasters

The Future Trends

Weather Derivatives

Algorithmic Trading

In-house Weather Modeling?

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WEATHER IMPACT ON THE COMMODITY

MARKETS

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The Channels of Transmission

The impact of weather on the agricultural markets

The dominant transmission channel: the supply side

The impact unfolds relatively slowly over time, except for some extreme event

Extremely cold weather in Florida affecting orange juice market

Freeze in the coffee producing regions

The potential for systemic impact due to long-term weather trends (Pinot Noir from Scotland?)

The impact on the demand side: local and short-term

The impact of weather on the agricultural markets was recognized in the relatively early stages of development of the futures exchanges

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Words of Wisdom From the Past

“So much for the financial conditions.

The spring had been backward, cold, bitter, inhospitable, and Jadwin began to suspect that the wheat crop of his native country, that for so long had been generous, and of excellent quality, was now to prove—it seemed quite possible--scant and of poor condition. He began to watchthe weather, and to keep an eye upon the reports from the little county seats and "centres" in the winter wheat States. These, in part, seemed to confirm his suspicions.

From Keokuk, in Iowa, came the news that winter wheat was suffering from want of moisture. Benedict, Yates' Centre, and Douglass, in southeastern Kansas, sent in reports of dry, windy weather that was killing the young grain in every direction, and the same conditions seemed to prevail in the central counties. In Illinois, from Quincy and Waterloo in the west, and from Ridgway in the south, reports came steadily to hand of freezing weather and bitter winds. All through the lower portions of the State the snowfall during the winter had not been heavy enough to protect the seeded grain. But the Ohio crop, it would appear, was promising enough, as was also that of Missouri. In Indiana, however, Jadwin could guess that the hopes of even a moderate yield were fated to be disappointed; persistent cold weather, wintercontinuing almost up to the first of April, seemed to have definitely settled the question.”

Frank Norris (1870-1902), “The Pit,” New York, 1903

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The Channels of Transmission (2)

The channels of transmission in the case of energy markets: primarily through the demand side

The impact on the supply side: primarily through specific events of varying magnitude, both in terms of scope and duration

Hurricanes

Precipitation impact on hydro power

Special local events

The events require good understanding of local conditions

The impact varies from long-term to short-term and fairly local

Fog in the Houston Ship Channel

High waters of the coast of California

Low water level in the Rhine river

Wells freeze-offs

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The Channels of Transmission (3)

The challenge: weather forecasting for an energy trading operation

Practically everybody has the access to the same source data and analytical skills (for a price)

The competitive advantage can be acquired through:

Better interpretation of the conflicting forecasts (when the models diverge)

Improved skills in the process of selection of the weather forecasting firms

Moving up the supply chain to beat the competition

Faster acquisition, processing, visualization, and delivery of the weather information

Elimination of some links in the supply chain

Direct acquisition of the model results and atomic weather data

Most important: better understanding of the impact of weather on the energy markets, contingent on other conditions (trading positions, conditions of the energy infrastructure)

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THE EARLY DAYS

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Weather Function in Energy Trading

Financial firms trading agricultural futures had weather teams supporting traders

Many weather analysts made contributions to energy trading in free time or when market conditions required their involvement

The first energy weather group was started by Enron

The Enron’s move was quickly replicated by the rest of the industry

The weather group was considered to be critical to the success of Enron trading

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UNFOLDING TRENDS

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WEATHER DERIVATIVES

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Weather Derivatives: Definition

A special version of weather insurance

Structured as derivative transactions

Regulatory considerations were the most compelling reason

Designed to hedge the risk of low severity, high probability events

By definition, actively traded on multiple platforms

A very successful take-off

The merchant energy industry used conditional probability distributions (unlike some counterparties in the insurance industry)

Some companies exploited successfully the human island phenomenon and data errors

Very limited repeat business

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Weather Derivatives: The Future

My opinion: it’s not a viable business, as opposed to highly structured, customized weather insurance

The reasons:

Weather derivatives put on head the very principle of weather derivatives (the few will pay for the losses of the many instead of the many paying for the losses of the few)

The high probability events represent permanent and recurring conditions of doing business and are most effectively addressed by incorporating the cost in the price of a product

The cash flow smoothing aspect of weather derivatives: the premiums are effectively capped by interest rates

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In-house Modeling

Some energy trading organizations move to direct acquisition of certain raw or intermediate data

Model outputs

Certain critical data sets

For example, sea surface temperatures

It can not be excluded that at some point some companies will engage in direct modeling of weather and/or computational activities

Will the market size justify this effort?

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Algorithmic Trading

Several energy trading organizations are experimenting with trading strategies based on data mining

Search for the patterns of markets response to the weather data

Automatic execution of transactions

The challenges

The difficulty of identifying and capturing all the relevant data

The reaction to the weather data depends on many factors, which may not be measurable

Example: positions held by other traders

The volume may not be sufficient to bother

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Contact information:

vkaminski@aol.com