For those looking to participate in the crude oil market without managing a futures account, the Invesco DB Oil ETF (NYSEARC: BOD) (the “Fund”) provides an exchange-traded fund (“ETF”) that provides this service. BOD returns do not correspond to a simple calculation of investing in NYMEX WTI (“NYMEX”) crude oil futures contracts, but the difference could be due to “rolling” contracts and related commissions, as shown below.
Moreover, DBO had a maximum drawdown of 92% since its inception (2007), which is an unacceptable result. Therefore, it is not suitable as a long-term investment, but can serve as a trading vehicle for sophisticated traders.
Finally, I explain my crude oil trading strategy and present real-time results against BOD since June 2022.
As Invesco states in its summary fact sheet:
This Fund is not suitable for all investors due to the speculative nature of an investment based on the Fund’s trading which takes place in highly volatile markets. Because an investment in futures contracts is volatile, such frequency of movement in the market prices of the underlying futures contracts could result in significant losses. Please see Investment Risks, Important Information and the Prospectus for additional risk information.
The Fund has been created to provide investors with a financial product designed to replicate the returns of the Index.
The Fund is currently long in the December 2022 WTI Crude Futures contract, which is the third close contract, with October being the close one.
Expense ratio and AUM
The Fund charges an expense ratio of 0.75% and has assets under management (“AUM”) of approximately $371 million.
Looking for Alpha assigned the Fund a “D” grade for its expense ratio.
Since its inception in January 2007, DBO has had a total return of -30%, even with the surge in oil prices over the past year.
In addition to the loss since 2007, the Fund’s risk was huge. Typically, downside risk is measured as Peak-to-Valley (“P2V”) and the maximum drawdown (“MD”) over a period is the largest P2V encountered. To learn more about P2V calculations, read here. (I’m taking the opposite sign of the drawdown, so it’s a positive number.)
According to my calculations, the DM of DBE was 90%. In other words, from the Fund’s highest peak since mid-2008, it has lost 90% of its investment value. The Fund is still down 70% from its high since inception.
The second near NYMEX WTI crude futures contract excludes rollover gains/losses, excludes brokerage fees, returned 44.75% over the same period as the DBO results. “Rollover” refers to trades that sell one long contract and buy the next contract.
Rolling gains or losses result depending on whether the futures market is in backwardation (i.e. far months are cheaper than the near month) or in contango (i.e. months distant are more expensive than the near month). Over the months since DBO’s inception, I calculated that the market was in contango for 64% of the months and the average premium paid (a loss) was $0.19/bbl.
In addition, commissions and brokerage fees would apply. These fees vary and depend on the volume of transactions in many cases.
In summary, rolling costs and brokerage fees may explain the difference in results between DBO and a simple calculation of futures market results.
The MD of the futures strategy was 92% over the same period of DBO results. It was an almost identical result.
Over the past 10 years, DBO has lost -39.30%, less than a large peer fund (AUM $2.1 billion), USO, which has lost -76.08%. However, the (SP500TR) returned 236.53% over the same period.
But over the past year, when crude oil prices have surged, DBO has returned 31.64%. This was lower than the 47.71% return for (USO), but exceeded the SP500TR’s 8.3% loss.
Comparison with BRS crude oil trading results
I started trading a portfolio of energy futures from June 23, 2022, consisting of NYMEX WTI Crude, RBOB Gasoline, Fuel Oil and Natural Gas. I publish daily positions and track records on my Seeking Alpha Marketplace service, Boslego Risk Services (“BRS”).
My Algorithmic Trading (AT) strategy is based on behavioral finance theory and, more specifically, on an article written by Nobel Laureate in Economics (2013), Robert J. Shiller. In his article, “From the theory of efficient markets to behavioral financeShiller discusses the failure of efficient market theory to explain stock prices and the “rise of behavioral finance” efficient market theory.
In particular, he describes one of the oldest theories in financial markets, which he calls the price-price feedback theory. Essentially, he argues that the emotions of greed and fear push market prices way too high on the upside and way too low on the downside.
Source: Journal of Economic Perspectives -Volume 17, Number 1-Winter 2003-Pages 83-104.
In his book, Irrational Exuberance (2000), Shiller argued that:
“Market reactions, transmitted by word of mouth as well as through the media, played a role in producing the bubble we were seeing then. I further argued that the natural self-limiting behavior of bubbles and the possibility of a downside reaction after the bubble was over.”
He created a feedback model to describe price changes with a distributed lag and compared them to price changes, if they had behaved like a random walk, as the theory of efficient markets argues.
Source: Journal of Economic Perspectives-Volume 17, Number 1-Winter 2003-Pages 83-104.
I developed and tested hypotheses to try to quantify conditions that might make investors greedy or fearful. And, it turns out that the size of market gains and losses, combined with their speed, does a pretty good job of determining when to go long (bullish), when to go short (bearish), and when to exit (neutral). There are other unique positioning techniques built into my model, such as position adjustment based on market price volatility for risk control.
Risk management is essential
In The smart investor, says Benjamin Graham, “the essence of investment management is risk management, not return management.” At the heart of this approach is loss minimization, deliberately protecting against severe losses. Warren Buffett has described this book as “by far the best investing book ever written”.
My approach is to separate emotions from investment decisions by executing an algorithmic (AT) trading strategy that provides systematic quantitative signals. The advantage of an AT strategy is that it can be tested in many different market conditions to determine the potential risks and returns of its future use. Although such a strategy cannot guarantee future results, it can show how it would have worked in the past, unlike discretionary strategies, which depend on a trader’s skill. And at least it can weed out strategies that may have worked poorly in the past.
For the period from June 23 to September 7, the total return for DBE was -13.03%, while my BRS raw strategy was 16.5%.
DBO’s MD over the same period was 19%, while it was 8% for the BRS strategy.
DBO manages the futures accounts while providing exposure to the NYMEX crude futures market. For many individual investors, this is an attractive feature because managing margins in a futures account can be time-consuming and error-prone.
However, DBO should not be a long-term investment for anyone. It simply exposes the investor to far greater losses than anyone else should suffer.
This leaves oil trading short term. Relatively few individual investors have the knowledge and skills to succeed in oil trading. This business is best left to sophisticated traders.