Benchmark

A benchmark is a standard against which the performance of a security, mutual fund or investment manager can be measured. Generally, broad market and market-segment stock and bond indexes are used for this purpose.

Benchmarks are indexes created to include multiple securities representing some aspect of the total market. Benchmark indexes have been created across all types of asset classes. In the equity market, the S&P 500 and Dow Jones Industrial Average are two of the most popular large cap stock benchmarks. In fixed income, examples of top benchmarks include the Barclays Capital U.S. Aggregate Bond Index, the Barclays Capital U.S. Corporate High Yield Bond Index and the Barclays Capital U.S. Treasury Bond Index. Mutual fund investors may use Lipper indexes, which use the 30 largest mutual funds in a specific category, while international investors may use MSCI Indexes. The Wilshire 5000 is also a popular benchmark representing all of the publicly traded stocks in the U.S. When evaluating the performance of any investment, it's important to compare it against an appropriate benchmark.

Identifying and setting a benchmark can be an important aspect of investing for individual investors. In addition to traditional benchmarks representing broad market characteristics such as large cap, mid cap, small cap, growth and value. Investors will also find indexes based on fundamental characteristics, sectors, dividends, market trends and much more. Having an understanding or interest in a specific type of investment will help an investor identify appropriate investment funds and also allow them to better communicate their investment goals and expectations to a financial advisor.

When seeking investment benchmarks, an investor should also consider risk. An investor's benchmark should reflect the amount of risk he or she is willing to take. Other investment factors around benchmark considerations may include the amount to be invested and the cost the investor is willing to pay.

The number of benchmarks has been expanding with product innovation. Benchmarks are often used as the central factor for portfolio management in the investment industry. Passive investment funds and smart beta funds are two strategies that are derived from benchmark investing. Replication strategies following customized benchmarks are also becoming more prevalent. Active managers are also in the market deploying actively managed strategies using indexes in the most traditional form, as benchmarks they seek to beat.

Passive

Benchmarks are created to include multiple securities representing some aspect of the total market. Passive investment funds were created to provide investors exposure to a benchmark since it is expensive for an individual investor to invest in each of the indexes’ securities. In passive funds the investment manager uses a replication strategy to match the holdings and returns of the benchmark index providing investors with a low cost fund for targeted investing. A leading example of this type of fund is the SPDR S&P 500 ETF (SPY) which replicates the S&P 500 Index with a management fee of 0.09%. Investors can easily find large cap, mid cap, small cap, growth and value mutual funds and ETFs deploying this strategy. 

Smart Beta

Smart Beta strategies were developed as an enhancement to passive index funds. They seek to enhance the returns an investor could achieve by investing in a standard passive fund by choosing stocks based on certain variables or by taking long and short positions to obtain alpha. State Street Global Advisors’ enhanced index strategies provide an example of this. The SSGA Enhanced Small Cap Fund (SESPX) seeks to marginally outperform its Russell 2000 benchmark by taking long and short positions in the small cap stocks of the index.

Market Segment Benchmarks

Market segment benchmarks can provide investors with other options for benchmark investing based on specific market segments such as sectors. The State Street Global Advisors SPDR ETFs provide investors the opportunity to invest in each of the individual sectors in the S&P 500. One example is the Technology Select Sector SPDR Fund (XLK).

Fundamental and Thematic Benchmarks

With the challenges of beating the market, many investment managers have created customized benchmarks that use a replication strategy. These types of funds are becoming more prevalent as top performers. These funds benchmark to customized indexes based on fundamentals, style and market themes. The Global X Robotics & Artificial Intelligence Thematic ETF (BOTZ) is one of the best performing non leveraged thematic ETFs in the investable universe. It uses an index replication strategy and seeks to track the Indxx Global Robotics & Artificial Intelligence Thematic Index. The Index is a customized index benchmark that includes companies involved in robotic and artificial intelligence solutions.

Active Management

Active management becomes more challenging with the growing number of benchmark replication strategies. Thus, for investors it becomes more challenging to find active managers consistently beating their benchmarks. In 2017, the ARK Innovation ETF (ARKK) is one of the top performing ETFs in the investable market. Year-to-date as of November 3 it had a return of 76.06%. Its benchmarks are the S&P 500 with a comparable return of 15.59% and the MSCI World Index with a comparable return of 17.55%.

The value of benchmarks has been an ongoing topic for debate bringing about a number of innovations that center around investing in the actual benchmark indexes directly. Debates are primarily derived from the demands for benchmark exposure, fundamental investing and thematic investing.  Managers who subscribe to the efficient market hypothesis (EMH) claim that it is essentially impossible to beat the market, and then by extension, the idea of trying to beat a benchmark isn’t a realistic goal for a manager to meet. Thus, the evolving number of portfolio strategies centered around index benchmark investing. Nonetheless, there are active managers who do consistently beat benchmarks. These strategies do require extensive monitoring and often include high management fees. However, successful active managers are becoming more prevalent as artificial intelligence quantitative models integrate more variables with greater automation into the portfolio management process.