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Investment professionals who provide investment advice to their clients (“advice-givers”).
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An investment strategy that seeks trends across commodity, rates, currency, and equity markets.
Managed
Dynamic and tactical approach, not static
Futures
Takes long and short positions using futures contracts
Quant
Humans build models, models determine portfolios
Trends
Durable source of alpha based on prices, not macro calls
Andrew Beer (co-portfolio manager of DBMF) explains managed futures
What can managed futures do for your portfolio?
An incredibly valuable portfolio diversifier to stocks and bonds
Long-term returns
Source: Bloomberg. DBi. Data from 3rd January 2000 to 31st December 2025, net of fees. Data refers to cumulative past performance. Cumulative past performance is not a reliable indicator of future results. This data is being shown for illustrative purposes only. The index is not representative of the entire population of CTAs or hedge funds. The index’s performance may not be indicative of any individual CTAs or hedge funds. The index may not have been adjusted for fees/commissions. The index cannot be traded by individual investors. The actual rates of return experienced by investors may be significantly different and more volatile than those of the index.
Low correlation to traditional asset classes
Source: Bloomberg. DBi. Data from 3rd January 2000 to 31st December 2025, net of fees. Data refers to cumulative past performance. Cumulative past performance is not a reliable indicator of future results. This data is being shown for illustrative purposes only. The index is not representative of the entire population of CTAs or hedge funds. The index’s performance may not be indicative of any individual CTAs or hedge funds. The index may not have been adjusted for fees/commissions. The index cannot be traded by individual investors. The actual rates of return experienced by investors may be significantly different and more volatile than those of the index.
Alpha during prolonged crises
Source: Bloomberg. DBi. Data from 3rd January 2000 to 31st December 2025, net of fees. Data refers to cumulative past performance. Cumulative past performance is not a reliable indicator of future results. This data is being shown for illustrative purposes only. The index is not representative of the entire population of CTAs or hedge funds. The index’s performance may not be indicative of any individual CTAs or hedge funds. The index may not have been adjusted for fees/commissions. The index cannot be traded by individual investors. The actual rates of return experienced by investors may be significantly different and more volatile than those of the index.
Max drawdown significantly lower than traditional asset classes
Source: Bloomberg. DBi. Data from 3rd January 2000 to 31st December 2025, net of fees. Data refers to cumulative past performance. Cumulative past performance is not a reliable indicator of future results. This data is being shown for illustrative purposes only. The index is not representative of the entire population of CTAs or hedge funds. The index’s performance may not be indicative of any individual CTAs or hedge funds. The index may not have been adjusted for fees/commissions. The index cannot be traded by individual investors. The actual rates of return experienced by investors may be significantly different and more volatile than those of the index.
Managed futures & DBMF: The essential alternative asset class
Why DBMF ?
One of the lowest fees in the category
85 bps
DBMF expense ratio is at the bottom decile of peers
Net expense ratios in the Morningstar Systematic Trend category
Source: Morningstar, eVestment, DBi. Cumulative past performance is not a reliable indicator of future results. As of March 31st 2026, net of fees, since inception (5/7/19). This is an active ETF which is not managed in relation to any benchmark. This data is being shown for illustrative purposes only. The index is not representative of the entire population of CTAs or hedge funds. The index’s performance may not be indicative of any individual CTAs or hedge funds. The index may not have been adjusted for fees/commissions. The index cannot be traded by individual investors. The actual rates of return experienced by investors may be significantly different and more volatile than those of the index. Past results are not indicative of future results.
Aims to reduce risk of materially underperforming benchmark
80%
Confidence tracking to index
SG CTA index correlation to DBMF (NAV)
Source: Morningstar, eVestment, DBi. Cumulative past performance is not a reliable indicator of future results. As of 31th December 2025, net of fees, since (4/01/22). This is an active ETF which is not managed in relation to any benchmark. This data is being shown for illustrative purposes only. The index is not representative of the entire population of CTAs or hedge funds. The index’s performance may not be indicative of any individual CTAs or hedge funds. The index may not have been adjusted for fees/commissions. The index cannot be traded by individual investors. The actual rates of return experienced by investors may be significantly different and more volatile than those of the index. Past results are not indicative of future results. Investment correlation measures how different assets move in relation to each other. A perfect correlation of +1 means both asset prices move in the same direction (go up together, and go down together). A correlation of -1 indicates they move in opposite directions.
History of outperforming index
+8.64
DBMF has delivered returns over category for 5 years
Annualised returns since DBMF inception
Source: Morningstar, eVestment, DBi. Cumulative past performance is not a reliable indicator of future results. As of March 31st 2026, net of fees, since inception (5/7/19). This is an active ETF which is not managed in relation to any benchmark. This data is being shown for illustrative purposes only. The index is not representative of the entire population of CTAs or hedge funds. The index’s performance may not be indicative of any individual CTAs or hedge funds. The index may not have been adjusted for fees/commissions. The index cannot be traded by individual investors. The actual rates of return experienced by investors may be significantly different and more volatile than those of the index. Past results are not indicative of future results.
DBi’s approach to managed futures
The iMGP DBi Managed Futures Fund seeks to replicate the pre-fee performance of a representative basket of leading managed futures hedge funds.
Investment strategy
The iMGP DBi Managed Futures Fund seeks to replicate the pre-fee performance of a representative basket of leading managed futures hedge funds.
Factor analysis is used to determine the current positions of the managed futures hedge funds.
The positions are then replicated using highly liquid futures contracts in equity, fixed income, currencies and commodities.
This approach is a smart and efficient way to gain exposure to managed futures, with the aim of outperforming the representative basket by 300-400 bps per annum, net of fees.
Through this strategy, the fund aims to mitigate three key investment risks:
Concentration Single Manager, Single fund, industry, geography
Human Biases Selection bias, etc.
Fee reduction is the purest form of alpha
The strategy seeks to optimize net returns to investors by approximating the main exposures that drive performance, minimizing trading and implementation costs, and offering lower all-in fees.
DBi’s Strategies seek to outperform by delivering 80-100+% of pre-fee hedge fund returns with lower fees and expenses.
iMGP DBi Managed Futures Strategy ETF Update with Andrew Beer | January 2026
Andrew Beer & Mike Pacitto dive deep into comparing managed futures to all major asset classes in terms of historical performance, alpha-generation, drawdowns, Sharpe, etc.
The strategy is an extremely effective diversification tool for traditional portfolios. It has no long-term structural correlation to stocks, bonds, or commodities (because it can be long or short any market based on prevailing price trends). Adding managed futures has historically reduced portfolio volatility without significantly reducing expected returns, producing a smoother ride. Additionally, the strategy has historically produced attractive absolute returns during extended periods of losses for traditional assets, also known as “crisis alpha.”
Almost every other managed futures fund is an active strategy based on the manager’s models, primarily for capturing trends in different asset classes, usually using more than 50 or even 100 futures markets. Some managers may also include non-trend models (e.g. carry) to varying degrees. DBMF is based on replicating the (gross, pre-incentive fee) performance of the SG CTA Index, which is comprised of 20 of the leading managed futures hedge funds. DBMF’s model uses the daily returns of the index to create a portfolio highly correlated to the index, using only 10-15 of the most liquid futures contracts. By tracking 20 leading funds via the index, DBMF eliminates the “single manager risk” of being invested in only one fund that underperforms the index dramatically and/or over an extended period.
It is a passive strategy in the sense that it is model-based and attempts to replicate an index, but the “index” itself is comprised of 20 active managers. Also notable, the “index” includes the underlying fees of the active managers. DBMF seeks an “index-plus” outcome by extracting fees from the index it replicates.
Yes, the fund earns interest on the collateral portfolio (typically 3-month T-bills), which is distributed quarterly. Capital gains are distributed annually.
Because managed futures bring strong diversification benefits to a portfolio, based on the statistics, you should hold about as much in managed futures as you can confidently defend when the strategy isn’t performing well. (Almost no one allocates as much as an optimizer would suggest, which is typically about 25-50% of a portfolio, depending on a number of factors.) Despite the significant long-term benefits, managed futures can sometimes be frustrating for extended stretches. Sizing an allocation appropriately is critical: the allocation should be big enough to move the needle in your portfolio when it’s working, otherwise the inevitable challenging periods along the way will hardly be worth it.But the allocation can’t be so big that you (or your client) will throw in the towel during rough patches. The best asset allocation is one that you can stick to for the long term, including through down periods for every component asset class or strategy. Every situation is different, but we think an allocation to managed futures in the 5% to 10% range is the practical sweet spot for most balanced portfolio investors (although higher allocations are well supported by the statistics).
Because managed futures have essentially no long-term correlation to anything, it makes sense to fund them pro rata from an existing allocation. The existing allocation has presumably been “optimized” for the investor’s return goals and risk tolerance based on the performance and correlation characteristics of its underlying components. Funding pro rata from these sources should preserve the expected return profile of the portfolio’s core, while adding the diversification benefits and (likely) crisis alpha of managed futures.A reasonable case could also be made to fund an allocation more than pro rata from bonds, given stocks outperform bonds over long time horizons, and managed futures tend to perform well during extended stock market weakness (i.e., periods of weeks to months, not days to weeks). The “optimal” allocation depends on what is being optimized (risk-adjusted returns, expected maximum total return, etc.). For a client that is more concerned with risk from a specific asset class, or has some other consideration, the funding sources could of course be customized further according to individual circumstances.
Managed futures strategies are heavily (sometimes solely) based on trend following, a strategy that dates back hundreds of years, but is today executed by sophisticated managers with vast amounts of computing power to build and refine quantitative models.While the details and execution are complex, the underlying premise is simple: across equity markets, bond markets, commodities and currencies, go long assets/markets that are rising in price, and go short assets/markets that are falling in price, using liquid futures contracts to gain exposure. There are numerous theories addressing why trend following works, including divergent economic fundamentals across countries and industries, supply-demand dynamics, market structure, and investor psychology.Regardless of the “correct” explanation, over its history, trend following has produced positive returns with essentially zero long-term correlation to traditional asset classes, and has tended to perform best in extended bear markets for stocks and bonds.DBMF is a simple, cost-effective way to add the benefits of managed futures to a portfolio without the risks of choosing a single manager whose style may be out of sync with markets in any given month, quarter, etc.
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