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Easy methods to Enhance Commodity Momentum Utilizing Intra-Market Correlation
Momentum is among the most researched market anomalies, well-known and extensively accepted in each public and tutorial sectors. Its idea is easy: purchase an asset when its worth rises and promote it when it falls. The aim is to make the most of these developments to attain higher returns than a easy buy-and-hold technique. Sadly, during the last a long time, we have now been observers of the diminishing returns of the momentum methods in all asset courses. On this article, we are going to current an intra-market correlation filter that may assist considerably enhance commodity momentum efficiency and return this technique as soon as once more into the highlight.
Whereas early momentum analysis primarily centered on shares, related patterns have been recognized throughout numerous asset courses. As an example, our Quantpedia Screener lists a momentum technique particularly for commodity futures. The technique entails rating the commodity futures by efficiency over the previous 12 months and dividing them into quintiles. The highest-performing quintile is purchased, and the bottom-performing quintile is bought, with rebalancing going down every month.
In Quantpedia’s analysis titled “What’s the Finest Issue for Excessive Inflation Intervals?“, the momentum impact was discovered to be optimistic during times of excessive inflation round World Struggle II and the Oil Disaster of 1973. Nevertheless, lately, the efficiency of momentum methods has declined. Momentum has struggled to successfully distinguish between winners and losers in homogeneous funding universes, as completely analyzed within the latest Quantpedia analysis paper titled “Robustness Testing of Nation and Asset ETF Momentum Methods”. The findings counsel that momentum methods carry out higher in asset-based ETFs than in country-based ETFs as a result of decrease correlation between property.
Constructing on these insights, this paper goals to deal with the latest decline in momentum efficacy by exploring methods to implement momentum in homogeneous commodity ETFs, quite than commodity futures. First, we take a look at a primary momentum technique, which doesn’t produce important alpha. Subsequent, we enhance the fundamental technique through the use of the ratio of short-term to long-term common correlations as a sign for when it’s favorable to use momentum methods, yielding promising outcomes. We suggest a technique based mostly on this intra-market correlation filter.
Methodology and Knowledge
For this evaluation, we selected sector commodity ETFs because of their ease of use, size of information, accessibility, and no want for advanced rolling procedures. The technique focuses on 4 sector-specific commodity ETFs: DBA (agriculture), DBB (base metals), DBE (vitality), and DBP (valuable metals). These ETFs provide an extended backtesting interval, ranging from 2007, in comparison with particular person commodity ETFs. Knowledge have been sourced from Yahoo Finance, utilizing the adjusted shut costs (adjusted for inventory splits, dividend distributions, and different related occasions affecting inventory’s worth) for the chosen ETFs. From the each day information, we calculated each each day and month-to-month efficiency.
Step 1
Step one was to copy a easy momentum technique utilizing the 4 ETFs (DBA, DBB, DBE, and DBP). Every month, we calculated the 1- to 12-month momentum for every ETF and ranked them based mostly on their efficiency. This rating offered the indicators for which ETFs to go lengthy and which to brief. The technique concerned going lengthy on the 2 best-performing ETFs and brief on the 2 worst-performing ones mimicking the fundamental premise of momentum that winners will proceed to outperform and losers will proceed to underperform. The portfolio was equally weighted and rebalanced on a month-to-month foundation.
Outcomes of step 1
Desk 1 easy momentum traits
Determine 1 easy momentum technique
As anticipated, the momentum technique on commodities yielded poor efficiency. Desk 1 exhibits that whereas it barely outperforms the benchmark return, this comes at the price of larger volatility. This consequence aligns with earlier analysis, together with analysis by Quantpedia. In homogeneous markets like commodities, the place property are extremely correlated, momentum struggles to successfully differentiate between winners and losers, resulting in disappointing efficiency.
One potential manner to enhance efficiency of momentum methods in commodity ETFs is by turning to low-liquidity property. In one among Quantpedia’s earlier research “Easy methods to Use Unique Belongings to Enhance Your Buying and selling Technique”, the authors examined the illiquidity premium—the concept anticipated returns enhance with illiquidity—by working a set of momentum methods utilizing commodity futures contracts from two main commodity indices, S&P GSCI and BCOM. The outcomes confirmed that non-indexed, or unique, low-liquidity property outperformed listed ones, providing larger returns with almost the identical threat as listed commodity methods.
Step 2
Whereas turning to low-liquidity property was one possibility, we determined to discover other ways to make momentum methods work successfully in commodity ETFs. Our aim was to discover a dependable predictor that would sign when it’s favorable to use a momentum technique and when it’s not. We quickly found that the ratio of short-term to long-term correlation may function such a predictor.
The subsequent step in our evaluation concerned calculating common short-term (measured over 20 days) and aveage long-term (measured over 250 days) correlations from the each day efficiency of the 4 ETFs. If the typical short-term correlation exceeds the typical long-term correlation between ETFs, it signifies that commodities are trending in a single path, permitting momentum methods to extra successfully distinguish between winners and losers. Deploying momentum underneath these situations can subsequently be extra worthwhile. In abstract, correlation filter allows us to use the momentum technique selectively, utilizing it solely when market situations are favorable.
Outcomes of step 2
As proven in Desk 2, the correlation predictor results in extra pleasing outcomes in comparison with the fundamental momentum technique. It outperforms the momentum technique throughout all efficiency metrics, together with annual returns, volatility, most drawdown, Sharpe ratio, and Calmar ratio. The correlation filter seems to be fairly strong. Whatever the momentum rating interval (1-12 months), the filter reliably identifies when it’s applicable to commerce the momentum technique (determine & desk 2) and when it’s extra appropriate to commerce the reversal impact because the momentum technique constantly yields unfavorable outcomes (determine & desk 3).
Desk 2 lengthy predictor traits
Determine 2 lengthy predictor
Desk 3 brief predictor traits
Determine 3 brief predictor
Step 3
The insights gained from this analysis open the door for the event of latest, thrilling methods. Primarily based on these findings and current literature, we suggest the next technique utilizing a correlation filter: if the short-term correlation is larger than the long-term correlation, apply the momentum technique by going lengthy on the two best-performing and brief on the two worst-performing sector commodity ETFs, based mostly on a 12-month rating, and maintain the positions for 1 month. If the short-term correlation is decrease than the long-term correlation, apply a reversal technique by going lengthy on the two worst-performing and brief on the two best-performing sector commodity ETFs (based mostly on a 12-month rating), and maintain the positions for 1 month. As proven in Determine 4 and supported by the leads to Desk 4, this mixed technique (Mother+Rev) almost doubles the return of both the standalone momentum or reversal methods. Though the upper volatility and most drawdown counsel an elevated stage of threat, this can be justified by the considerably larger returns.
Desk 4 urged technique traits
Determine 4 urged technique
Conclusion
On this paper, we addressed the challenges of momentum in homogeneous markets like commodities utilizing extensively obtainable sector commodity ETFs.
In abstract, whereas a primary momentum technique utilized to commodities yields disappointing outcomes, incorporating a predictor based mostly on intra-market correlation considerably enhances momentum technique’s efficiency. This ratio between 20-day and 250-day correlation gives a dependable sign figuring out when commodities are trending strongly sufficient for momentum to differentiate between winners and losers.
Writer: Margareta Pauchlyova, Quant Analyst, Quantpedia
References
Quantpedia. (n.d.). Momentum impact in commodities. Retrieved September 1, 2024, from https://quantpedia.com/methods/momentum-effect-in-commodities/
Quantpedia. (n.d.). What’s the most effective issue for prime inflation durations? (Half II). Retrieved September 1, 2024, from https://quantpedia.com/whats-the-best-factor-for-high-inflation-periods-part-ii/
Du, Jiang and Vojtko, Radovan, Robustness Testing of Nation and Asset ETF Momentum Methods (March 25, 2023). Out there at SSRN: https://ssrn.com/summary=4736699 or http://dx.doi.org/10.2139/ssrn.4736699
Cisár, Dominik and Vojtko, Radovan, Easy methods to Use Unique Belongings for Buying and selling Technique Enchancment (September 3, 2021). Out there at SSRN: https://ssrn.com/summary=3916918 or http://dx.doi.org/10.2139/ssrn.3916918
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