Bogey is a slang term used to describe a benchmark used to evaluate an investment’s performance. A bogey can be used in mutual funds as an index benchmark through which the performance of the fund can be evaluated. Oftentimes, fund or portfolio managers strive to match the performance of the bogey. In a particular market, a bogey can be used to compare the results of two investments mutual funds and portfolios. This index performance also gives insight into the performance of a fund.
Bogey also refers to the benchmark set by a fund company to evaluate the performance of its funds. This benchmark is set aside to help them measure the performance of their funds compared to other investments in the market. Aside from evaluating the performance of a fund, investment or portfolio, a bogey also examines other characteristics such as the risks of the funds. The S&P 500 is a popular example of a bogey used in the market to check how well an investment is performing.
There are different reasons for which an investor or a fund company will set a target benchmark (bogey) for its funds, the major reason is to give insight into how an investment is performing as against other investments in the industry.
Bogey Benchmark Analysis
A bogey benchmark is often in alignment with the objectives or goals of a mutual fund company, along with its investment strategy. Usually, a bogey has a similar performance as a fund. Some bogeys are set so with the goal of a fund replicating the performance and characteristics of an index, while some bogey benchmarks are used as a technique to outperform the market benchmark. In some cases, however, mutual fund companies and investors set bogeys just to make a comparison between their investment and the broader market.
Below are the major terms associated with a bogey;
- A benchmark: This refers to the standard used in measuring the performance of an investment, fund or portfolio.
- Index: This is a measure of the performance of a group of securities that are expected to replicate the market benchmark such as the S&P 500.
- Alpha: This measures the excess return of an investment as compared to the return of the benchmark index.
- Security Market Indicator Series (SMIS): This is an indicator series where the performance of a group (subset) of securities is a representation of the general performance of a broad market.
- Aggressive Growth Fund: This is a mutual fund that invests in aggressive growth stocks, seeking excess capital gains.
Reference for “bogey”
Academic research on “Bogey”
Incentive fees and mutual funds Elton, E. J., Gruber, M. J., & Blake, C. R. (2003). Incentive fees and mutual funds. The Journal of Finance, 58(2), 779-804. This paper examines the effect of incentive fees on the behavior of mutual fund managers. Funds with incentive fees exhibit positive stock selection ability, but a beta less than one results in funds not earning positive fees. From an investor’s perspective, positive alphas plus lower expense ratios make incentive‐fee funds attractive. However, incentive‐fee funds take on more risk than non‐incentive‐fee funds, and they increase risk after a period of poor performance. Incentive fees are useful marketing tools, since more new cash flows go into incentive‐fee funds than into non‐incentive‐fee funds, ceteris paribus.
Hedge Fund Indexes: Benchmarking the Hedge Fund Marketplace Anson, M. (2004). Hedge Fund Indexes: Benchmarking the Hedge Fund Marketplace. Working Paper, EDHEC Graduate School of Business, EDHEC-Risk Institute, Nice, France. Available at http://www. edhec-risk. com/research_news/choice/RISKReview108089352936435435/attachments/HF% 20Indexes% 20-% 20Anson. Pdf. Hedge funds do not easily fit into the current way institutions go about investing. Based on a survey of recent academic and practitioner research, this article reviews six competing frameworks for how to incorporate hedge funds in institutional portfolios. Each framework has very different implications for institutional asset allocation, manager selection, and benchmarking.
Performance evaluation with portfolio holdings information Wermers, R. (2006). Performance evaluation with portfolio holdings information. The North American Journal of Economics and Finance, 17(2), 207-230. Few topics in the field of finance have generated as much interest and spirited debate as the issue of active versus passive investing. Empirical evidence in support of the superiority of passively managed portfolios is persuasive. (See, for example, Davis (2001); Arnott, Berkin, and Ye (2000); Sorensen, Miller and Samak (1998); Carhart (1997); Gruber (1996); Malkiel (1995); or Brinson, Hood, and Beebower (1995)). Conversely, equally sound empirical or logical evidence in defense of the value of active portfolio management has been presented. (See, for example, Pastor and Stambaugh (2002); Wermers (2000); Elton, Gruber, and Blake (1996); or Etzioni (1992)). Moreover, “behavioral” arguments in favor of actively managed funds have been offered (Timbers 1997). A recent article by Holmes (2007) provided findings that were relatively consistent with several previous studies: on an aggregate basis, actively managed mutual funds have not outperformed their passive peers, net of fees. Holmes provided a comprehensive analysis of the active/passive debate versus much of the previous research. But several of the cited studies share one or more methodological problems, and in this paper we will use the Holmes study as a basis for demonstrating these problems and how they can
EMERGING MARKETS OF SOUTH-EASTERN EUROPE: CROATIAN MUTUAL FUNDS AND BOSNIAN INVESTMENT FUNDS. Podobnik, B., Balen, V., Jagrič, T., Kolanovic, M., Pehlivanovic, B., & Strašek, S. (2009). EMERGING MARKETS OF SOUTH-EASTERN EUROPE: CROATIAN MUTUAL FUNDS AND BOSNIAN INVESTMENT FUNDS. Our Economy (Nase Gospodarstvo), 55. In this article we study the performance of Croatian mutual funds and Bosnian investment funds. The risk/ return measures are assessed by using the Sharpe ratio, the Treynor ratio, Jensen’s Alpha, and the Treynor appraisal ratio. Furthermore, we analyze the timing ability of the funds using the quadratic regression of Treynor and Mazuy. To emphasize the financial perspective of South-eastern Europe, we also analyze returns of major financial indices in Croatia, Bosnia and Herzegovina, Slovenia, Serbia and Montenegro, Bulgaria, and Macedonia, and show that financial markets in the whole region exhibit a strong performance recently.
Hedge Funds: Alpha, Beta, and Replication Strategies Dubil, R. (2011). Hedge Funds: Alpha, Beta, and Replication Strategies. Journal of Financial Planning, 24(10), 51-60. We demonstrate the value of disaggregating mutual fund performance into stock selection and sector allocation. Consistent with most studies, we find the average active equity mutual fund manager underperformed the market from 1994-2005. However, underperformance was driven by poor stock selection within sectors, undoing abnormal gains from sector allocation. The best funds outperformed in both sector allocation and security selection while worst underperformed mainly in stock selection during four three-year sample periods from 1994-2005. We also argue that using alphas from models with size and growth factors may result in biased and unreliable performance evaluation