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Baron Funds: A Deeper Look at the Performance

Stock Analysis Pic C

Ronald S. Baron is widely known as one of the most successful investors in the U.S. Getting his start in the brokerage industry, Mr. Baron focused on the smaller, less desirable companies that didn’t seem necessarily attractive to most money managers. Finding success early on in this particular niche, he formed Baron Capital Management in 1982, building strategies focused on small cap growth stocks and then slowly building a more diversified product line covering international and emerging markets, real estate, and even specific sectors such as energy. As of today, Baron manages close to $25 billion in assets.

Mr. Baron's background and story are very impressive. Studying chemistry and law while in school, creating a successful business, and having a net worth of over $1 billion is not easy to find among many people. Given the large amount of uncertainty involved in investing, it is very attractive to find someone who can provide confident predictions about the future, and have a background that seems to acknowledge that they have been very successful in doing so.

Today, we are going to take a deep dive into Baron Capital’s long-term performance in order to shed light on what has become increasingly apparent within the active money management industry. We have taken a deeper look at the performance of several other mutual fund companies and hedge funds 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 read our previous reviews 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 13 strategies that are currently offered by Baron, it doesn't necessarily mean that these are the only strategies that Baron has ever managed. In fact, there is one fund that no longer exists. This can be due to a variety of reasons including poor performance or the fact that they were merged with another fund.

Fees & Expenses

Let's first examine the costs associated with their current strategies (13 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 amount of cost 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 due to short term and long term capital gains distributions relative to those incurred by passively managed funds.

The table below details the hard costs as well as the turnover ratio for all 13 active funds offered by Baron that have at least 3 years of complete performance history. On average, an investor who utilized a strategy from Baron experienced a 1.23% expense ratio and a 0.25% 12b-1 fee for those strategies that have a 12b-1 fee associated with them. These expenses can have a substantial impact on an investor’s overall accumulated wealth if it is not backed by superior performance. The average turnover ratio for the strategies offered by Baron was 30.35%. This implies an average holding period for each position of about 3.5 years. It is safe to say that Baron 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.

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
Baron International Growth Retail BIGFX 38.90 1.35 0.25 Global Equity Large Cap
Baron Global Advantage Institutional BGAIX 21.48 1.10 0.00 Global Equity
Baron Emerging Markets Institutional BEXIX 25.31 1.13 0.00 Emerging Markets Equity
Baron Fifth Avenue Growth Retail BFTHX 19.30 1.10 0.25 US Equity Large Cap Growth
Baron Small Cap Retail BSCFX 10.25 1.32 0.25 US Equity Small Cap
Baron Discovery Institutional BDFIX 90.74 1.10 0.00 US Equity Small Cap
Baron Asset Retail BARAX 12.54 1.31 0.25 US Equity Mid Cap
Baron Growth Retail BGRFX 4.68 1.30 0.25 US Equity Mid Cap
Baron Opportunity Retail BIOPX 32.38 1.41 0.25 US Equity Mid Cap
Baron Partners Retail BPTRX 15.59 1.35 0.25 US Equity Mid Cap
Baron Focused Growth Retail BFGFX 14.31 1.35 0.25 US Equity Mid Cap
Baron Energy and Resources Institutional BENIX 53.52 1.10 0.00 Energy Sector Equity
Baron Real Estate Institutional BREIX 55.50 1.07 0.00 Real Estate Sector Equity

Performance Analysis

The next question we address is whether investors can expect superior performance in exchange for the higher costs associated with Baron’s “expertise.” We compare each of their 14 strategies, which include 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:

  • 29% (4 of 14 funds) have underperformed their respective benchmarks or did not survive the period since inception.
  • 71% (10 of 14 funds) have outperformed their respective benchmarks since inception, having delivered a POSITIVE alpha
  • 7% (1 of 14 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 quite impressive that the vast majority of funds offered by Baron have outperformed their Morningstar assigned benchmark. However, of the 10 funds that did have a positive alpha, only one delivered enough consistency of alpha to yield a statistically significant result. The inclusion of the statistical significance of alpha is key to this exercise, as it indicates which outcomes are due to a skill that is likely to repeat and those that are more likely due to a random-chance outcome.

Examining statistical significance always needs to be taken in context. We can find high statistical significance of a random variable with simply two observations. The problem with relying solely on statistical significance without context is that we can be basing conclusions off of small samples, which you can imagine is problematic, especially for a long-term investor.

This is what we see with the one Baron fund that does have a statistically significant alpha. While Baron has been around for over 30 years, this particular strategy, the Baron International Growth Fund (BIGFX), has only been around since 2009. To illustrate our point, it would only take BIGFX to underperform its benchmark by 1.50% this year in order for its alpha to become statistically insignificant since 2009. One year of relative underperformance should not have such an impact on the investment conclusions we draw from our analysis. This is the major problem with drawing conclusions based on small sample sizes (Law of Small Numbers).

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 Baron 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. Let alone the fact that the style attribution of a fund often changes over time (see Step 6: Style Drifters).

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 funds from Baron 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 5 funds that met the criteria, 0 produced an alpha that was statistically significant at the 95% confidence level (green shaded area). In fact, all 5 funds had a negative alpha after controlling for market, size, and relative-price risk factors. 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 financial institutions, a deep analysis into the performance of Baron has yielded a not so surprising result: active management is likely to fail the majority of investors. We believe this is due to market efficiency, costs, and increased competition in the financial services sector. Although most of Baron’s funds have outperformed their Morningstar assigned benchmark, all of the outperformance of those with a 10 year record can be explained away by differences in Beta exposure. 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. 

Below are the individual alpha charts for each one of the currently available Baron funds. 
















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.