Investigating Beef Market Volatility

by Marcus Brix, CattleFax

Summary

If you were to ask the cattle feeder about volatile markets across history, you would get many of the same answers. Often the first response is December of 2003, “the cow that stole Christmas.” It is still staggering today to recall the devastation caused by the first U.S. case of bovine spongiform encephalopathy, or BSE, which was found in a Canadian-sourced Holstein cow. Spot live cattle futures broke sharply from the December 23rd closing price of $92.35/cwt to what would become a multi-year low of $72.50/cwt, a loss of roughly $275/head for a fed animal. The biggest damage was inflicted from the loss of beef exports, which research from Kansas State University estimated to be between $3.2 and $4.7 billion dollars in 2004 alone. Another historically volatile time is one that most all Americans would be familiar with, the collapse of the U.S. financial system in 2008. Already nine months into a recession, the greatest financial risks occurred with the bankruptcy of the Lehman Brothers investment bank, which at the time was the 4th largest U.S. bank of its kind. Spot live cattle futures fell from a closing price of $103.75/cwt on September 2nd, 2008 to a recessionary low of $79.18/cwt on June 8th, 2009.  Feedyards were forced to sell cattle into the lowest fed cattle demand level in 30 years.

Background

It is hard to believe with the magnitude of these two past events, that a more recent market could compete in scale with the degree of cattle market volatility described above, but it’s true and measurable. Volatility is a statistical measure of price risk, evaluated by calculating the standard deviation of price changes over a given period. Analyzing the 30-day volatility against the live cattle strip allows for an easily comparable measure of price risk in late 2015 versus the two previously mentioned cases. The strip is a simple average of the front six live cattle futures contracts which covers a full calendar year. Using the live cattle strip is preferred over spot futures for this analysis because it removes the additional risk of changing price spreads across futures contracts. 

Thirty-day volatility reached as high as 23.8 percent in late 2003, which was the first time above the 20 percent mark since November 1987. The highest recorded volatility during the recession was 25.8 percent in October of 2008. For context, 30-day volatility has averaged 11.1 percent per day over the last 10 years of data with a variance of about 4 percent, so values above 20 percent are considered to be extreme. Volatility at year-end 2015 reached 24.4 percent, actually higher than during the BSE-driven volatility of 2003. From August to October live cattle prices declined 20 percent, then rallied 18 percent into early November. From here, prices declined another 18 percent through mid-December, and finally rallied yet again leaving prices 17 percent off the December lows entering the New Year. From close to close, the live cattle strip was moving on average 1 percent per day in this time period, compared to a 10-year average daily change of only 0.13 percent. For many producers, hedging with plain futures contracts was much too risky. Despite expensive option premiums, largely due to the immense volatility in the market, managing risk using options became the only viable strategy.

Discussion
There were a multitude of reasons for the volatile price decline. The cattle market had been trending lower already that year, dealing with a large front end supply of cattle. Volatility spiked, however, immediately after the closure of the Tyson meat packing plant in Dension, IA. The sudden loss of packing capacity hurt the cattle feeders from a leverage standpoint; leverage was accountable for $10/cwt of the rally seen in 2014.  Cattle weights were also record large and had been trending higher into the fall. This compounded the situation as feedyards tried to unload the heavy cattle and accepted discounts to do so. 

While fundamentals turned negative on the live cattle side, fundamentals turned negative on the beef product side as well. Total meat supplies were building much faster than anticipated as pork and poultry production pushed higher, beef exports were stifled by the strong U.S. dollar and poultry exports were drastically reduced by HPAI-related bans in China and new protectionist trade policies in Angola. As a result, per capita net meat and poultry supplies increased by an estimated 9.4 pounds per U.S. resident, about seven pounds of the increase being poultry product. As an interesting parallel, exports as a percentage of meat and poultry production fell from 17 percent in 2014 to 15 percent in 2015. This was the largest yearly drop since BSE in 2003.

Conclusion
These abrupt year over year changes explain why the market grew weaker and more volatile, but there might still be an unexplained piece of the puzzle, intraday volatility. From August to December 2015, the spot live cattle average daily range from high to low was 1.73 percent. This is compared to an average range of 1.27 percent for the same monthly range in 2014, and a 1 percent range for the 5-year average. The cattle industry has recently pointed a finger at high frequency trading as being a main source of this extra volatility. Although some of these claims are speculative at this point, many are based on sound evidence. Since the adoption of electronic trading, research has suggested higher volume of trade leads to better liquidity, but to increased volatility as well. An underlying issue with high frequency algorithmic trading, however, is that orders can be entered and bounced between different trading stations before a manual trader can act on the order, potentially causing changes to the bid-ask spread. This behavior would then not be increasing liquidity, but still increasing volatility. This scenario increases the transaction costs to manage risk not only through futures, but options as well, because increased volatility is transferred into option costs as risk premium. The CME Group is evaluating several options for reducing volatility, including shorter trading hours and a maintaining a stricter watch over trades. This is a complex problem, and the solution will have to ensure contracts trade at adequate volume, but also on an even playing field for all market participants.

Additional Resources

Tags: Beef Issues Quarterly, Spring 2016, Trends Analyses

March 29, 2016