Russell indexes Definition
- Russell 3000 Index
- Russell 2500 index
- Russell 2000 Index
- Russell 1000 Index
A Little More on What is the Russell Indices
The Russell 2000 index shows the performance of the 3000 biggest US corporations whose market capitalization falls within $170 million to $200 billion. This category accounts for 98 percent of the U.S equity market.
The Russell 2500 index shows the performance the 2500 smallest companies in the US with a mean capitalization of $733 million. This figure accounts for 23 parent of the equity market.
The Russell 2000 index shows the performance of the 2000 smallest U.S. companies with an average capitalization of $467 million. This represents 10 percent of the local equity market.
The Russell 1000 index measures the performance of stocks of the top 1000 firms on the Russell 3000 index, amounting to an average of $7.6 billion in capitalization and 90 percent of the local equity market.
Russell Top 200 Index analyzes the performance of the largest 200 companies in the Russell 3000 index, with an average capitalization of $2.4 billion and 65 percent of the equity market.
Russell Midcap Index assesses the performance of the 800 smallest companies on the Russell 3000 index which accounts for $2.9 billion capitalization and 35 percent of the equity market.
References for Russell Index
Academic Research on Russell indexes [or indices]
Active versus passive index management: A performance comparison of the S&P and the Russell Indexes, Shankar, S. G. (2007). Journal of Investing, 16(2), 85. This study compares the performance of the S&P which uses an active index management and the Russell index that works with a passive index management. The author finds that active index management performs better than passive management and recommends the former for investors especially for the small capitalization sector.
Equity-style timing: A multi-style rotation model for the Russell large-cap and small-cap growth and value style indexes, Arshanapalli, B. G., Switzer, L. N., & Panju, K. (2007). Journal of Asset Management, 8(1), 9-23. In this paper, the authors create a multinomial timing model using macroeconomic variables and public information based on the Frank Russell indexes. The study posits that multi-style rotation strategies offer improved performance compared to buy-and-hold portfolios and offer reasonable profits.
Earnings Management and the Reconstitution of the Russell Indexes, Cho, J. H., Leshchinskii, D., & Zaima, J. K. (2017). Journal of Accounting and Finance, 17(4), 10-31. This paper examines the behavior of firms moving from the Russell 1000 to the Russell 2000, those that move to the Russell 1000 and companies that remain in the Russell 2000. The study finds that firms moving into the Russell 2000 show positive cumulative abnormal returns while those that move into the Russell 1000 index show negative cumulative abnormal returns.
The Effect on Stock Price from Changes to the Russell Indexes, Lapalme, J., & Jelusic, Z. (2009). This article looks at the impact of changes to the Russell Indexes on stock price.
The Russell reconstitution effect, Madhavan, A. (2003). Financial Analysts Journal, 59(4), 51-64. This paper looks at the Russell reconstitution effect on abnormal returns of statistical and economic significance. The author posits that the yearly reconstitution of the Russell Index causes unexpected return volatility in liquidity of the firms on the index.
Performance evaluation and self-designated benchmark indexes in the mutual fund industry, Sensoy, B. A. (2009). Journal of Financial Economics, 92(1), 25-39. This study examines the impact of self-designated benchmark indexes on the returns of mutual funds. The paper concludes that the effect of self-designated benchmark indexes on mutual funds is a strategic behavior caused by the drive to boost flow of returns.
The transmission of shocks among S&P indexes, Ewing, B. T. (2002). Applied Financial Economics, 12(4), 285-290. In this paper, the authors analyze the relationship between five major S&P stock indexes and how shocks are transmitted from one index to others. The study uses the generalized forecast error variance decomposition technique to determine transmission of shocks.
A simple test of the Fama and French model using daily data: Australian evidence, Faff, R. (2004). Applied Financial Economics, 14(2), 83-92. This paper uses daily Australian data to test the Fama and French three-factor model. The study suggests that a negative size premium casts doubts over the continued existence of the model.
Response latency versus certainty as indexes of the strength of voting intentions in a CATI survey, Bassili, J. N. (1993). Public Opinion Quarterly, 57(1), 54-61. In this CATI study, researchers test predicting the differences between voting intentions and voting behavior. Using a logistic regression model, the paper shows that response latency provides the more accurate prediction of the discrepancies between voting intention and voting behavior compared to certainty.
Desperately seeking pure style indexes, Amenc, N., Faff, R., & Martellini, L. (2003). Risk and Asset Management Research Centre. This paper provides evidence of a high heterogeneity in the information found in competing indexes and the challenges this poses for modern portfolio analysis and empirical tests of the asset pricing theory. The study offers potential solutions to the problem and suggests ways to develop a pure style index using competing index returns.
Fundamental Indexes™: Current and future applications, Arnott, R. D., & West, J. M. (2006). Institutional Investor Journals, Fall. In this study, the authors analyze the applications of Fundamental Indexing in determining the actual value of a firm’s stocks.