Today we continue our three part series breaking down three common arguments against trend following. Today's topic- the idea that momentum frequent trading creates material tax inefficiencies within your account.
Note- this is the third edition of a larger study detailing how you can answer several frequently asked questions your clients might have when considering the broader momentum factor. Click here to read part 1 and Here to read part 2, addressing the ideas that momentum investing is “streaky” in comparison to other factors or momentum incorrectly chases winners. We have also included, linked here, a PDF of all three reports together to make it easy to reference going forwards. With any questions/concerns, email miles.clark@nasdaq.com
Like any investment process, trend following is not without its share of ups and downs. Over time, buying winners and cutting losers can foster a strong point‑to‑point return stream, but the inter‑period experience of momentum investing can be difficult to stomach as natural rotation occurs and trends change. Time and time again, shifts in leadership create uncomfortable situations that often run counter to our natural “gut” instincts, causing even the most loyal trend follower to consider deviating from the rules. These untimely breakdowns in systematic rule‑following allow emotion to creep in at precisely the wrong moment, potentially erasing years’ worth of discipline- either psychologically, monetarily, or quite often, both.
With that in mind, we have taken the opportunity to break down several of the major roadblocks and common arguments that inevitably arise for trend followers. Our hope is that by better understanding the typical pitfalls of momentum investing, we can more appropriately contextualize returns over time.
Major arguments commonly raised against the momentum factor typically include:
- Trend following is “streaky” and, as a result, does not belong in the average portfolio.
- Trend following often “chases winners” inefficiently, leading to frequent whipsaws.
- Frequent rotation driven by changing market leadership creates material tax inefficiencies.
Turnover and its Effect on Tax Efficiency
While the previous two sections highlight why it is so important for momentum strategies to rotate to new strength, the discussion thus far has omitted one major player: Uncle Sam. In the real world, trading out of one security and into another generally creates a taxable event depending on the performance of the security. As momentum‑focused strategies tend to trade more frequently than many other factors, it is easy to assume that any excess returns generated through favorable asset rotation may quickly be offset by a higher tax bill, particularly when compared to other factors which see less overall rotation. We do know, however, that not all taxes are treated the same- investors generally prefer the lower rates associated with long-term gains (LTG), which occur when an asset has been held for over a year. Meanwhile, investors want to avoid the higher tax rate associated with short-term gains (STG), which occur when we hold profitable positions for under one year. Given the universal preference for minimizing tax liability, this raises an important question: do tactical strategies inherently lead to unfavorable tax outcomes?
To test this theory, we can take a look back at our Large Cap Core model discussed in the previous sections. This time, because holding period directly influences the favorability of tax treatment, we include holding period as an observable data point, pictured below. If momentum strategies generally lead to unfavorable tax outcomes, we would expect to see a clear pattern emerge: a larger share of total gains coming from short‑term gains rather than long‑term gains.Note that you can see trade efficiency scores for any of your models, including custom ones by clicking on the "trade efficiency" tab on the models page.
Observing all 1,455 trades in aggregate via the “cumulative trade efficiency” section of the graph above, some interesting trade tendencies emerge. First, and most importantly, long-term gain generating trades actually occur more frequently than short-term gain trades (28.7% vs. 22.7%, respectively), running counter to what many would typically assume for a tactical strategy. Secondly, short-term losses represent the most common trade outcome, accounting for roughly 44% of total trades in the dataset. At first glance this seems less than ideal- a potential “death by 1,000 cuts” scenario. However, at its core, this is the systematic nature of trend following at work. By consistently cutting small losers short, the magnitude of downside left‑tail events is reduced (a result that aligns with the trade distribution discussed in the "chasing winners" section). In doing so, momentum can unemotionally move on from a losing position in an effort to find a new possible right-tail winner.
While trade frequency provides useful context, the more relevant consideration for long‑run tax efficiency is the magnitude of gains realized within each tax classification. It is for this reason that NDW developed a “tax efficiency score” which calculates the percentage of total gains generated over a given timeframe that would have been tagged at the more favorable LTG tax rate. The score is calculated as the proportion of gains realized at long‑term rates relative to total realized gains (both short‑ and long‑term). To put it simply, a more tax efficient model has a score closer to 100, meaning that most (or all) of captured gains would have been taxed at a lower rate. In this case, our model earns a score of nearly 77%, suggesting that just over three-quarters of realized gains were taxed favorably- a result far more efficient than many might expect from a strategy that continuously rotates into new market leadership.
There is no question that momentum comes with its fair share of roadblocks a prospective investor would need to be cautious of before considering including the factor within their portfolio. That said, many of the risks commonly associated with momentum appear to be overstated, most notably those centered on trading frequency and its perceived impacts on apparent “streakiness” of yearly returns or overall tax efficiency. While it is true that the frequency of security rotation is steeper than other factors, momentum’s systematic approach to security selection sidesteps several other issues present in other factors, particularly those based around human emotions. Overall, the ability for trend followers to largely remove human biases creates a factor-unique return distribution focused on right tail events, while still largely protecting the integrity of the yearly return profile and tax efficiency over time. Taken together, these characteristics suggest that many of momentum’s perceived drawbacks are better understood as features of a disciplined, rules‑based process rather than inherent flaws in the strategy itself.
