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 value rises and promote it when it falls. The objective is to make the most of these tendencies to realize higher returns than a easy buy-and-hold technique. Sadly, over the past many years, now we have been observers of the diminishing returns of the momentum methods in all asset lessons. 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 targeted on shares, comparable patterns have been recognized throughout numerous asset lessons. As an illustration, 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 offered, with rebalancing going down every month.
In Quantpedia’s analysis titled “What’s the Greatest Issue for Excessive Inflation Durations?“, the momentum impact was discovered to be constructive in periods of excessive inflation round World Conflict II and the Oil Disaster of 1973. Nonetheless, in recent times, 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 handle the latest decline in momentum efficacy by exploring the way to implement momentum in homogeneous commodity ETFs, moderately than commodity futures. First, we take a look at a fundamental momentum technique, which doesn’t produce vital alpha. Subsequent, we enhance the essential technique by utilizing 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 method primarily based on this intra-market correlation filter.
Methodology and Information
For this evaluation, we selected sector commodity ETFs attributable to their ease of use, size of information, accessibility, and no want for complicated rolling procedures. The technique focuses on 4 sector-specific commodity ETFs: DBA (agriculture), DBB (base metals), DBE (vitality), and DBP (treasured metals). These ETFs provide an extended backtesting interval, ranging from 2007, in comparison with particular person commodity ETFs. Information had 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 day by day information, we calculated each day by 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 primarily based on their efficiency. This rating offered the indicators for which ETFs to go lengthy and which to quick. The technique concerned going lengthy on the 2 best-performing ETFs and quick on the 2 worst-performing ones mimicking the essential 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 reveals that whereas it barely outperforms the benchmark return, this comes at the price of greater 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 certainly one of Quantpedia’s earlier research “Methods to Use Unique Belongings to Enhance Your Buying and selling Technique”, the authors examined the illiquidity premium—the concept that 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 greater returns with practically the identical danger 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 objective 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 might function such a predictor.
The following step in our evaluation concerned calculating common short-term (measured over 20 days) and aveage long-term (measured over 250 days) correlations from the day by 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 route, permitting momentum methods to extra successfully distinguish between winners and losers. Deploying momentum below these circumstances can subsequently be extra worthwhile. In abstract, correlation filter allows us to use the momentum technique selectively, utilizing it solely when market circumstances are favorable.
Outcomes of step 2
As proven in Desk 2, the correlation predictor results in extra pleasing outcomes in comparison with the essential 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 sturdy. Whatever the momentum rating interval (1-12 months), the filter reliably identifies when it’s acceptable to commerce the momentum technique (determine & desk 2) and when it’s extra appropriate to commerce the reversal impact because the momentum technique persistently yields detrimental outcomes (determine & desk 3).
Desk 2 lengthy predictor traits
Determine 2 lengthy predictor
Desk 3 quick predictor traits
Determine 3 quick 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 greater than the long-term correlation, apply the momentum technique by going lengthy on the two best-performing and quick on the two worst-performing sector commodity ETFs, primarily based 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 quick on the two best-performing sector commodity ETFs (primarily based 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) practically doubles the return of both the standalone momentum or reversal methods. Though the upper volatility and most drawdown counsel an elevated degree of danger, this can be justified by the considerably greater returns.
Desk 4 recommended technique traits
Determine 4 recommended technique
Conclusion
On this paper, we addressed the challenges of momentum in homogeneous markets like commodities utilizing extensively accessible sector commodity ETFs.
In abstract, whereas a fundamental momentum technique utilized to commodities yields disappointing outcomes, incorporating a predictor primarily based 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 tell apart between winners and losers.
Creator: 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 one of the best issue for top 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). Accessible at SSRN: https://ssrn.com/summary=4736699 or http://dx.doi.org/10.2139/ssrn.4736699
Cisár, Dominik and Vojtko, Radovan, Methods to Use Unique Belongings for Buying and selling Technique Enchancment (September 3, 2021). Accessible at SSRN: https://ssrn.com/summary=3916918 or http://dx.doi.org/10.2139/ssrn.3916918
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