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Trading in financial markets involves significant risk of loss which can exceed deposits and may not be suitable for all investors.
Before trading, please ensure that you fully understand the risks involved
Trading in financial markets involves significant risk of loss which can exceed deposits and may not be suitable for all investors. Before trading, please ensure that you fully understand the risks involved

Thursday, August 13, 2020

Pair Strategy: Sell Corn & Buy Rough Rice

By Century Financial in Investment Insights

Pair Strategy: Sell Corn & Buy Rough Rice
Sell Corn and Buy Rough Rice

The pair trade strategy is based on secular trends present in corn & rough rice prices. The strategy involves selling corn on one side and buying rough price on the other side (Equal Exposure).

Risks to the Outlook

  • The strategy is not a risk free strategy and involves taking opposite exposures on both sides of trades.
  • The strategy is based on past agro prices and primarily relies on the trend and macro view in order to establish a pair strategy direction.
  • Going ahead, as the effects of COVID 19 pandemic further pan out, both these commodities may react adversely to their current price trends and behave differently than the strategy.
  • Agro commodities owing to their very nature are highly subject to the effects from other exogenous factors. For instance, in corn, the actual outcome of US - China trade war may affect the prices more than the current crop fundamentals. Similarly for rough rice, if the actual effects of pandemic completely subside, the prices may collapse in near term.
  • Kindly get in touch with Century staff for more clarifications.

Sell Corn

After touching a high of $ 8.43/bushel in August 2012, corn has seen a rapid decline over the last 8 years with the agro commodity touching a low of $3.00/bushel in April of this year. Much of the decline in corn prices in the decade of 2011 – 2020 was on account of high & propped up prices in the previous period on account of US government policies. For instance, in the year 2005, the US converted 3.0 billion bushels of corn into Food, Seed and Industrial uses like ethanol. By 2010, that number was 6.4 billion bushels, a whopping increase of 682 million bushels a year. Owing to the rapid increase in this demand, the corresponding prices for corn rose from $1.9/bushel (2005) to high of $7.78 /bushel seen in 2008(300+% increase). Prices further spiked up all the way till $8.43/bushel in 2012 during the time when US suffered its drought period. What followed these high prices was period of high crop acreage causing prices to slide. Although 2018 & 2019 saw some amount of reduction in plant ages, prices nevertheless kept on falling.

Currently, the crop looks increasingly healthy with some market estimates also putting yield at 180 bushel/acreage, a new record. On the demand side, owing to COVID 19 pandemic, things look pretty bleak with key driver for corn demand – ethanol producers taking a backseat. Nearly 40% of U.S. corn is converted into ethanol fuel. With automotive demand likely to be relatively weak even as US economy opens in a staggered manner, less demand is leaving a massive supply glut of US ethanol. These factors indicate a further downside pressure likely to build up on corn prices.

Buy Rough Rice

Rough rice has outperformed all major agro commodities this year on back of increased demand for the food staple over the past few months. Prices touched a high of $23.64/cwt in this June, near its 2008 high of $25.07/cwt. Looking at the overall trend over the last 8 years, prices have managed to hold in the range of $9.5 - $ 14 since past couple of years. The crop has seen couple of years of tight stock.This year, rough rice prices were being largely supported by record export interest and domestic pick up as the Covid 19 pandemic bought food security to forefront. The commodity has also seen various logistical problems in the inner US regions owing to the pandemic which has resulted in sharp spike in prices during first 5 months of this year.

What is asset allocation

What is asset allocation

What is asset allocation

What is asset allocation

Strategy Statistics

The strategy has provided cumulative returns of 81% over the last 8.6 years period with average returns of 9.31% annually.

Net P & L on $ 100K exposure for both sides (No Leverage)

2012 -5.48% 1.23% -4.24% $(5,476) $1.234 $(4,242)
2013 40.25% 0.36% 40.61% $(40,248) $361 $40,609
2014 5.92% -23.08% -17.15% $(5,924) $(23,077) $(17,153)
2015 9.46% 0.47% 9.93% $(9,464) $467 $9,931
2016 2.09% -18.70% -16.61% $(2,086) $(18,697) $(16,611)
2017 0.36% 23.18% 23.53% $(335) $(23,176) $(23,532)
2018 -6.76% -13.05% -19.81% $(6,762) $(13,045) $(19,807)
2019 -3.33% 28.11% 24.78% $(3,331) $28,110 $24,779
2020 18.94% 20.99% 39.93% $18,940 $20,990 $39,930

Risks & Assumptions

The strategy might suffer from look-ahead bias which occurs due to use of information or data in a study or simulation that would not have been known or available during the period being analyzed. This can lead to inaccurate results in the study or simulation.
Future price movements may not be exactly the same as the historical price movements and this could lead to variation in performance.
Testing can sometimes lead to over-optimization. This is a condition where performance results are tuned so high to the past they are no longer as accurate in the future.
The model assumes no slippages in trading. Slippage refers to the difference between the expected price of a trade and the price at which the trade is actually executed.
Drawdowns in actual trading can be higher than the tested system and loses could significant in the event of leverage.
Unforeseen events can lead to variation in performance from the tested trading strategy.
The tested result has been computed with price feeds available from Bloomberg.
The testing environment has not considered transaction or any other costs.
Trading indicators used for the purpose of testing has been provided by Bloomberg.
The strategy might suffer from data mining fallacy, selection bias and backfill bias.

Data Source: Bloomberg

Arun Leslie John
Chief Market Analyst

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