Traditionally the vast majority of market players focus their investment efforts in trading equities and bonds. This is because equities might enable high returns while bonds might protect the portfolio during bear markets. Alpha Growth Capital has traditionally focused in using predictive analytics to trade equities in its flagship strategy NEXT-alpha (https://www.alphagrowthcapital.co/next-alpha.html). In the quest to reduce the strategy volatility while possibly leaving the annualized returns unchanged, Alpha Growth Capital has explored the viability of investing in asset classes other than equities.
In this article, we will explore the viability of trading commodities. Corn was taken as case study and the historical data from the Teucrium Corn Fund (CORN) were used to evaluate different trading methodologies. The results were finally compared to buy & hold the S&P500 using different risk matrixes. The following trading strategies were investigated:
A commercial software (Matlab) was used to perform a parametric optimization of all the three strategies to find the optimal value of each parameter for each indicator. The optimization was targeting the maximization of the return of investment. Trading fees and ask-bid price spreads were neglected in the optimization.
In regards to the entry and exit signals:
Trading Methodology 1: the position is entered when the ratio between the conversion line period and the baseline period exceeds a threshold level. The position is close when the ratio is below the threshold level. Entries and exits signals are evaluated just before the market closes.
Trading Methodology 2: the position is entered when the Commodity Channel Index is above and given value and vice-versa. Entries and exits signals are evaluated just before the market closes.
Trading Methodology 3: this is a proprietary methodology developed by Alpha Growth Capital for its core strategy NEXT-alpha. With this methodology, the price action is expressed as function of the volatility of the equity market (VIX) instead of time. Depending on the volatility level of the market: different intraday exit price levels are established for the position opened at the previous end of trading day, position size is selected and intraday limit and stop orders are set at a pre-determined price.
Because of the contango/backwardation effect, buying and holding CORN from mid-2011 to December 2020 would have resulted in an annualized loss of 10.66%. When the conversion line is set at 8 days while the baseline line at 11 days, using a ratio threshold of 1%, the Trading Methodology 1 would have led to an annualized return of 5.04% with a maximum drawdown of 10.35%. With the second trading methodology, the Commodity Channel Indicator period was set at 3 while its threshold entry/exit level at 125. In this case the annualized return was 2.01% while the maximum drawdown 10.61%. The proprietary Trading Methodology 3 provided the best results. The annualized return was 16.62% while the maximum drawdown 17.55%. The risk adjusted return was the highest among the three strategies. An overview of the results is presented in Table 1. The simulated optimized price evolution for the three strategies is presented in Figure 1.
Table 1: Comparison of the three optimized trading methodologies. B&H = Buy & Hold. CAGR = Compounded Annual Growth Rate. STD = Standard Deviation.
Figure 1: Simulated price evolution of the three optimized trading strategies.
The Trading Methodology 3 has emerged to be the winner. The question now is how it would compare to buying and holding the S&P500 (SPY). From mid-2011 to end of December 2020, the S&P500 has returned an annualized 10.48%, 33.92% as maximum drawdown and a Sharpe ratio of 0.60. In comparison this optimized strategy has delivered an annualized return of 16.62%, 17.55% as maximum drawdown and a SharperRatio of 0.46%. As compared to the S&P500, the optimized strategy improves both the return and the drawdown while the Sharpe ratio slightly deteriorates.
As compared to NEXT-alpha, the Trading Methodology 3 shows both lower returns (29% vs. 17%) and lower drawdown (26% vs. 18%). If on one hand trading CORN might offer diversification on the other hand its implementation into the portfolio would lower the annualized returns of NEXT-alpha.
In conclusion, this article has evaluated three different trading strategies to trade CORN. Trading based on the Ichimoku and the Commodity Channel Index indicators can result in positive returns vs. buying and holding CORN. Looking at the price action in the volatility domain and define appropriate entry & exit levels as function of the market volatility can provide even better results than the above mentioned two indicators. The optimized strategy enables to achieve 16.62% annualized returns while trading based on the Ichimoku and Commodity Channel Index indicators: 5.04 and 2.01% respectively. The optimized strategy also delivers better returns versus buying and holding the S&P500 over the same time frame.