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Parnassus Investments: A Deeper Look at the Performance

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Harvard Business School graduate Jerome L. Dodson founded San Francisco-based Parnassus Investments in 1984. Launching their first investment strategy in 1984 (the Parnassus Fund) with an eye towards responsible investing, their vision of expanding socially responsible investing (SRI) around the world has become one of their distinguishing characteristics. 

As of today, they manage close to $24 billion in assets across six different strategies that include domestic equity, foreign equity, and socially responsible fixed income. Their management and leadership hold quite an impressive resume with most graduating from top-rated business schools such as Harvard and Haas at U.C. Berkeley.

Like many of the investment companies we have analyzed before, intelligence and brilliance is most definitely not a missing element from the dedicated professionals who work at these firms. Nonetheless, we have also concluded that the vast majority of the funds offered by top investment management firms fail to consistently outperform their respective risk-adjusted benchmarks overtime, which has lead us to the overwhelming conclusion that attempting to find a manager who can consistently deliver “alpha” is extremely difficult. The argument we make for why this is the case has to do with competition and informational and operating efficiency of the capital markets where insights are quickly imbedded into market prices around the world making them the best estimate of “fair value” of any given company at any given time.

This is not a debate about the level of intelligence of the asset managers. Rather, it is the result of many brilliant and intelligent professionals competing for capital that lead to this efficacy.

We have done analyses like this before. The table below includes a list of the fund families we have dissected. Again, the overwhelming conclusion is that they have failed to deliver on the value proposition they profess, which is to reliably outperform a risk comparable benchmark. You can review our prior articles 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 6 strategies that are currently offered by Parnassus, it doesn't necessarily mean that these are the only strategies that Parnassus has ever managed. In fact, there are 2 funds that no longer exist which may be for a variety of reasons including poor performance or the fact that they were merged into another fund. We will show their aggregate performance shortly. 

Fees & Expenses

Our analysis begins with an examination of the costs associated with the strategies. It should go without saying that if investors are paying a premium for investment “skill,” 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 in comparison to those incurred by passively managed funds.

The table below details the hard costs as well as the turnover ratio for all 6 strategies offered by Parnassus 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 Global Category
Parnassus Fixed-Income PRFIX 39.47 0.68 US Fixed Income
Parnassus Asia PAFSX 46.04 1.25 Asia Equity
Parnassus PARNX 41.70 0.86 US Equity Large Cap Growth
Parnassus Endeavor Investor PARWX 34.08 0.95 US Equity Large Cap Growth
Parnassus Core Equity Investor PRBLX 22.89 0.87 US Equity Large Cap Blend
Parnassus Mid-Cap PARMX 18.81 0.99 US Equity Mid Cap

On average, an investor who utilized an equity strategy from Parnassus experienced a 0.98% expense ratio. For fixed income, an investor experienced a 0.68% average expense ratio. This 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 equity strategies offered by Parnassus is about 33% and 40% for fixed income. This implies an average holding period of about 1.5 to 3 years.  It is safe to say that Parnassus 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 Parnassus’s “skill.” We compare each of the 3 strategies that have at least 3 years of performance history 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 strategy at the bottom of this article. Here is what we found:

  • 63% (5 out of 8 funds) have underperformed their respective benchmarks since inception, having delivered a NEGATIVE alpha, or did not survive the time period.
  • 37% (3 out of 8 funds) have outperformed their respective benchmarks since inception, having delivered a POSTIVE alpha
  • 0% (0 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

Based on the historical performance of their strategies, it seems that Parnassus has been mixed in terms of delivering outperformance for their investors. The inclusion of statistical significance is key to this exercise as it indicates which outcome is the most likely vs. random-chance.

Regression Analysis

How we define or choose or benchmark is extremely important. If we relied solely on commercial indices assigned by Morningstar, then we may lead to the false conclusion that Parnassus 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 for 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, we could look at all of the US based strategies from Parnassus and 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. There is only 1 strategy offered by Parnassus that has consistently held U.S. stocks as the vast majority of their holdings since inception, which is the Parnassus Core Equity Fund (PRBLX). The chart below displays the average alpha and standard deviation of that alpha for PRBLX since inception (24 years: 1/1/1993 to 12/31/2016).

As you can see, PRBLX did not produce an alpha that was statistically significant at the 95% confidence level (green shaded area) even though their risk-adjusted performance has been quite impressive relative to other active funds. 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.

Style Drift

Some investors may be asking why the calculation for "alpha" is different between the Morningstar assigned benchmark (0.03%) compared to that of the Fama/French 3-Factor Regression (2.07%). The reason has to do with "Style Drift." As a quick reminder, style drift is when a fund manager deviates the fund's overall exposure to a specific asset class over time. We will use PRBLX as an example.

The chart below gives a visual representation of asset class exposure among four commercial indexes: Russell 1000 Growth (U.S. Large Cap Growth), Russell 1000 Value (U.S. Large Cap Value), Russell 2000 Growth (U.S. Small Cap Growth), and Russell 2000 Value (U.S. Small Cap Value). As you can see, from the year 1995 until about year 2000, PRBLX was mainly investing in value stocks, both large (green) and small (brown). Beginning in 2000, they shifted their overall exposure towards U.S. large cap growth stocks (blue). The fund steadily shifted away from any exposure to small cap stocks (orange or brown) and is now equally split between large cap growth (blue) and large cap value (green) stocks. 

PRBLX has had a journey across a few different asset classes. A Morningstar assigned benchmark only provides a snapshot of PRBLX's current exposure. If there has been style drift over time, which is the case of PRBLX, then you cannot accurately analyze the fund's performance, or more specifically its "alpha," by simply comparing its performance to its current Morningstar assigned benchmark, which happens to be the Russell 1000 Index. This seems to be an appropriate benchmark based on its current asset class exposure as depicted in its Style Drift chart. 

This is also difficult to control for when running regressions via asset pricing models. Each month, the performance of PRBLX is regressed against the market, size, and relative-price factors. Overtime, the regression attempts to find the "line of best fit" to most accurately caculate the overall correlations betwen PRBLX's monthly returns and the three factors. The wider the dispersion between each monthly datapoint and the "line of best fit," the more inaccurate the model at describing the correlations between PRBLX's monthly returns and the three factors. 

If a fund manager is engaging in style drift, it will be hard for the 3-factor model to determine the overall correlations between PRBLX's monthly returns and the 3-factors, which can lead to misleading conclusions about PRBLX in terms of its performance. In fact, when we run the Fama/French 3-Factor asset pricing model against PRBLX's monthly returns, we find that the regression has an R-Squared of 0.82 meaning that the model was only able to explain 82% of the variation of PRBLX's returns. About one-fifth of the fund's variation in returns is missing. We believe this is due to style drift. Ideally, we would like to see an R-Squared well into the 90th percentile in order to conclude that the model accurately described the fund's variation in returns. 


Like many of the other largest financial institutions, a deep analysis into the performance of Parnassus 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 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.