Loomis Sayles: A Deeper Look at the Performance


Boston based asset manager, Loomis Sayles, has been around since just before the Great Depression. As of March 31, 2017, they managed close to $250 billion in assets across 10 mutual fund strategies, institutional separate accounts, collective trusts, and hedge funds.

As is typical with most large money managers, Loomis Sayles takes an active approach to managing money, believing that they can discover and exploit markets and/or securities that are inefficiently priced. It’s a parlance that has become all too common when it comes to speaking with investors. Given the large amount of uncertainty involved in investing, it is very attractive to find someone who can provide confident predictions about the future. These soothsayers look at market indicators and macroeconomic trends and extrapolate what they think is the future value of capitalism around world.

Unfortunately, it’s a false confidence that they are instilling in their investors, as more often than not they are no better at predicting the future than non-investment professionals. We have taken a deeper look at the performance of several other mutual fund companies and have come to one universal conclusion: they have failed to deliver on the value proposition they profess, which is to reliably outperform a risk comparable benchmark. You can review our past analysis by clicking any of the links below:

Controlling for Survivorship Bias

It is important for investors to understand the idea of survivorship bias. While there are 10 strategies that are currently offered by Loomis Sayles, it doesn't necessarily mean that these are the only strategies that Loomis Sayles has ever managed. In fact, there 17 funds that no longer exist due to a variety of reasons including poor performance or the fact that they were merged with another fund. Think about that for a second. The majority of strategies offered by Loomis Sayles ultimately did not survive. We will show what their aggregate performance looks like shortly. 

Fees & Expenses

Let's first examine the costs associated with their current strategies (10 total). It should go without saying that if investors are paying a premium for investment “expertise,” then they should be receiving above average results consistently over time. The alternative would be to simply accept a market's return, less a significantly lower fee, via an index fund.

The costs we examine include expense ratios, front end (A), level (B) and deferred (C) loads, as well as 12b-1 fees. These are considered the “hard” costs that investors incur. Prospectuses, however, do not reflect the trading costs associated with mutual funds. Commissions and market impact costs are real costs associated with implementing a particular investment strategy and can vary depending on the frequency and size of the trades executed by portfolio managers. We can estimate the costs associated with an investment strategy by looking at its annual turnover ratio. For example, a turnover ratio of 100% means that the portfolio manager turns over the entire portfolio in 1 year. This is considered an active approach and investors holding these funds in taxable accounts will likely incur a higher exposure to tax liabilities such as short term and long term capital gains distributions than those incurred by passively managed funds.

The table below details the hard costs as well as the turnover ratio for all 10 active funds offered by Loomis Sayles that have at least 3 years of complete performance history. You can search this page for a symbol or name by using Control F in Windows or Command F on a Mac. Then click the link to see the Alpha Chart. Also remember that this is what is considered an in-sample test, the next level of analysis is to do an out-of-sample test (for more information see here).

Fund Name Ticker Turnover Ratio % Prospectus Net Expense Ratio 12b-1 Fee Global Category
Loomis Sayles Investment Grade F/I LSIGX 23.00 0.48 0.00 US Fixed Income
Loomis Sayles Securitized Asset LSSAX 306.00 0.00 0.00 US Fixed Income
Loomis Sayles Inflation Protected Secs I LSGSX 61.00 0.40 0.00 Inflation Linked
Loomis Sayles Bond Instl LSBDX 13.00 0.66 0.00 US Fixed Income
Loomis Sayles Fixed Income LSFIX 14.00 0.57 0.00 US Fixed Income
Loomis Sayles High Income Opps Instl LSIOX 36.00 0.00 0.00 High Yield Fixed Income
Loomis Sayles Instl High Income LSHIX 17.00 0.68 0.00 High Yield Fixed Income
Loomis Sayles Global Bond Instl LSGBX 120.00 0.75 0.00 Global Fixed Income
Loomis Sayles Small Cap Growth Instl LSSIX 56.00 0.95 0.00 US Equity Small Cap
Loomis Sayles Small Cap Value Instl LSSCX 22.00 0.96 0.00 US Equity Small Cap

On average, an investor who utilized an equity strategy from Loomis Sayles experienced a 0.96% expense ratio. Similarly, an investor who utilized a bond strategy from Loomis Sayles experienced a 0.44% expense ratio. These expenses can have a substantial impact on an investor’s overall accumulated wealth if they are not backed by superior performance. The average turnover ratios for equity and bond strategies from Loomis Sayles were 39.00% and 73.75%, respectively. This implies an average holding period of about 16 to 30 months. It is safe to say that Loomis Sayles makes investment decisions based on short-term outlooks, which means they trade quite often. Again, this is a cost that is not itemized to the investor, but is definitely embedded in the overall performance. In contrast, most index funds have very long holding periods--decades, in fact, thus deafening themselves to the random noise that accompanies short-term market movements, and focusing instead on the long term.

Performance Analysis

The next question we address is whether investors can expect superior performance in exchange for the higher costs associated with Loomis Sayles’s “expertise.” We compare each of their 27 strategies, which includes both current funds and  funds no longer in existence, since inception against its current Morningstar assigned benchmark to see just how well each has delivered on their perceived value proposition. We have included alpha charts for each of their current strategies at the bottom of this article. Here is what we found:

  • 67% (18 of 27 funds) have underperformed their respective benchmarks or did not survive the period since inception.
  • 33% (9 of 27 funds) have outperformed their respective benchmarks since inception, having delivered a POSITIVE alpha
  • 0% (0 of 27 funds) have outperformed their respective benchmarks consistently enough since inception to provide 95% confidence that such outperformance will persist as opposed to being based on random outcomes

It is safe to say that the majority of funds offered by Loomis Sayles have not outperformed their Morningstar assigned benchmark or survived over their lifetime. Of the strategies that did have a positive alpha, 0 delivered enough consistency to yield a statistically significant result. The inclusion of statistical significance is key to this exercise as it indicates which outcome is the most likely vs. random-chance outcomes.

Regression Analysis

How we define or choose a benchmark is extremely important. If we relied solely on commercial indices assigned by Morningstar, then we may form a false conclusion that Loomis Sayles has the “secret sauce” as active managers. Because Morningstar is limited in terms of trying to fit the best commercial benchmark with each fund in existence, there is of course going to be some error in terms of matching up proper characteristics such as average market capitalization or average price-to-earnings ratio.

A better way of controlling these possible discrepancies is to run multiple regressions where we account for the known dimensions (Betas) of expected return in the US (market, size, relative price, etc.). For example, if we were to look at all of the US based strategies from Loomis Sayles that have been around for the last 10 years, we could run multiple regressions to see what their alpha looks like once we control for the multiple Betas that we know are being systematically priced into the overall market. The chart below displays the average alpha and standard deviation of that alpha for the last 10 years ending 12/31/2016.

As you can see, of the 2 funds that met the criteria, 0 produced an alpha that was statistically significant at the 95% confidence level (green shaded area). What we can say is that all strategies from Loomis Sayles do not have a statistically significant alpha once we control for their overall risk exposure. Why is this important? It means that if we wanted to simply replicate their risk exposure, we could do so more cost effectively through the use of index funds. Given the lower costs associated with index funds, we could have more confidence that we will experience a more desirable result compared to more expensive actively managed funds.


Like many of the other largest financial institutions, a deep analysis into the performance of Loomis Sayles has yielded a not so surprising result: active management is likely to fail many investors. We believe this is due to market efficiency, costs, and increased competition in the financial services sector. As we always like to remind investors, a more reliable investment strategy for capturing the returns of global markets is to buy, hold, and rebalance a globally diversified portfolio of index funds.

Here are the individual alpha charts for the existing Loomis Sayles funds that have 3 years or more of a track record. 












Here is a calculator to determine the t-stat. Don't trust an alpha or average return without one.
The Figure below shows the formula to calculate the number of years needed for a t-stat of 2. We first determine the excess return over a benchmark (the alpha) then determine the regularity of the excess returns by calculating the standard deviation of those returns. Based on these two numbers, we can then calculate how many years we need (sample size) to support the manager's claim of skill.