The current El Niño weather phenomenon could be among the strongest on record and is likely to reach peak intensity between November and January. Then, it rapidly diminishes. The impact on crops and their prices, however, could last a lot longer. Our previous article (El Niño: Corn Cares; Cows & Pigs Care; You Should Care, Too) shows that El Niños can raise crop prices, and their impact on agricultural markets can last one to two years after they started forming along the equator in the Pacific Ocean.
In this paper we explore the relationship between El Niño, its counterpart, La Niña, and the volatility of prices for agricultural goods.
El Niño is a macro-scale weather anomaly that occurs when sea surface temperatures become unusually warmer-than-normal across the central and east-central Equatorial Pacific Ocean. Warmer waters tend to have more evaporation. Where the extra precipitation comes down depends on the direction the winds blow. And El Niño shifts wind patterns, too. The warmer-than-usual air over the equator in the Pacific Ocean leads to rising air currents, which can exert a southerly pull on storm tracks in North America.
The likelihood that the current El Niño peaks soon and turns into a potentially strong La Niña by late 2016 or early 2017 is something that participants in agricultural markets should track closely because it has the potential to increase volatility and raise the cost of buying options as protection.Strong El Niños, like the current episode as well as the 1972-73 and the 1997-98 occurrences, often quickly turn into La Niña’s (Figure 1). La Niña is characterized by lower-than-normal temperatures across the central and east-central Equatorial Pacific and leads to largely the opposite impacts on weather, winds and currents. In contrast with El Niño, La Niña historically correlates with declining prices for agricultural goods. The likelihood that the current El Niño peaks soon and turns into a potentially strong La Niña by late 2016 or early 2017 is something that participants in agricultural markets should track closely because it has the potential to increase volatility and raise the cost of buying options as protection.
In terms of volatility, we observe the following consistent relationships across corn, soy and wheat:
Previously, we looked at the one-year change in the inflation-adjusted spot price from the time that the temperature index crosses an arbitrary threshold of +1 degree Celsius in the event of El Niño or -1 degree Celsius in the event of La Niña (Figure 2). To smooth out the data, we took a 20-business-day moving average of the first nearby futures (spot) price, which is approximately one month’s worth of data. For instance, if the temperature index crossed +1 degree Celsius above the moving average in September 1963, we looked at the return from the average price in September 1963 to the average price in September 1964. Here we focus on the annualized daily volatility in corn, soy and wheat.
Overall, volatility levels under significant El Niños are very similar to what they are under normal conditions. We define “normal conditions” as being when Pacific Ocean temperatures are between -1 and 1 degree Celsius of their normal. By contrast, when significant La Niñas occur, agricultural markets tend to experience much higher levels of volatility (Figure 3, 4 and 5). This may be related to the negative price trends observed after the Niño Index crosses the -1 degree threshold. Generally speaking, markets tend to be more volatile when they are declining than when they are rising, a relationship that holds true for energy, metals, equities and agricultural goods.
Higher volatility during La Niña holds equally true for corn, soy and wheat. That said, there is a high degree of variation within the different El Niño and La Niña episodes (Figures 6-11). One thing to note is that volatility, in general, was much lower during the 1960s than it has been subsequently.
There is also a relationship between the peak intensity of the El Niño or La Niña episode and the degree of volatility generated in agricultural goods prices. This relationship is stronger for La Niña than it is for El Niño and it tends to be stronger in soy than in corn, and especially strong for wheat (Figures 12-17). For each of these charts (Figures 12-17), we measure the correlation and the “p-value,” which is a statistical measure of the likelihood of getting such a strong result randomly, taking into account the correlation and the number of observations. A p-value of 5%, for instance, implies a 5% likelihood of getting such a strong correlation randomly, given the number of observations.
The fact that the current El Niño episode is quite intense creates the potential for elevated levels of volatility. Moreover, the possibility that the current strong El Niño could snap back into a powerful La Niña over the course of the next 12 months should also raise concerns about the potential for higher volatility in agricultural goods prices going forward. Nothing could be further from the market’s mind, however. Corn, soy and wheat options are trading near five-year lows in terms of implied volatility (Figure 18).
It wouldn’t surprise us if the current El Niño creates more volatility before it ends. So far, the current El Niño episode hasn’t generated big moves in agricultural goods prices. The U.S. and Canada had decent harvests of corn, soy and wheat while Argentina and Brazil have had bumper harvests of soy and wheat. Some even argue that El Niño might depress prices of agricultural goods since it might boost South American harvests. Perhaps, but we are skeptical of such arguments. We think that it is wiser to wait for an entire year or one full crop cycle to see what impact El Niño has on crop prices, and by our measure (one degree Celsius above normal), the current episode only began in June. This El Niño and its consequences will be with us for many months to come.
All examples in this report are hypothetical interpretations of situations and are used for explanation purposes only. The views in this report reflect solely those of the authors and not necessarily those of CME Group or its affiliated institutions. This report and the information herein should not be considered investment advice or the results of actual market experience.
Erik Norland is Executive Director and Senior Economist of CME Group. He is responsible for generating economic analysis on global financial markets by identifying emerging trends, evaluating economic factors and forecasting their impact on CME Group and the company’s business strategy, and upon those who trade in its various markets. He is also one of CME Group’s spokespeople on global economic, financial and geopolitical conditions.
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