The Impact of the Ameritrade Online Investor Index on the Autocorrelations and Cross-Correlations of Market Returns (2001)

ABSTRACT This paper investigates the value of the information contained in the Ameritrade Online Investors Index (AOII) for the returns of two exchange traded funds. The AOII measures the buying and selling decisions for a group of online investors. The returns of the funds for the Nasdaq 100 and the S&P Mid-Cap 400 are examined using the quartiles of the Index. Overall, results show no influence on the returns from a broad market index and a negative impact from the lagged value of the return of the given fund. An investment strategy is suggested that incorporates short-selling when low values of the AOII are found in conjunction with negative returns of a given asset. INTRODUCTION The predictability of market returns is a topic of great interest to practitioners and financial researchers. If financial markets are truly efficient and follow a random-walk process, the cost of developing a forecast of future returns is an unrecoverable investment of time, energy and resources. At the other end of the efficiency spectrum, perhaps the future return on a market portfolio of securities is somehow linked to readily available public information and some degree of predictability is attainable. In this paper, the daily returns for two exchange traded funds, the first for the Nasdaq 100 (Ticker: QQQ) and the second for the Standard & Poor's Mid-Cap 400 (Ticker: MDY), are examined to measure the role an index of online investors play in determining future market returns. The explosive growth of the Internet and online trading, in conjunction with vast amounts of financial information, are some of the major forces that shape individual investor decision making today. Recent papers by Miller (1988), Lakonishok and Maberly (1990) and Abraham and Ikenberry (1994) investigated the way investors use information in making investment choices. Their central conclusions are that there are certain time periods where it is more costly to process and use information in buying and selling choices for investors. More specifically, Abraham and Ikenberry state that increased costs to process information exist during the work week and this result leads to increased selling and lower returns of securities on Mondays. The benefits and costs of information processing by online traders are one of the primary research questions for this study. Chordia and Swaminathan (2000) employed autocorrelations and cross-correlations and found that returns on stocks with high trading volume can be used to predict returns of low trading volume stocks, regardless of the size of the firm. This paper uses a methodology implemented by Perfect and Peterson (1997) and Higgins, Howton and Perfect (2000) by investigating the autocorrelations and cross-correlations in the returns of two exchange traded funds (ETFs) for two major market indices. While the two previous articles investigated the returns of an asset on a given day of the week, this research looks at the role a given level of buying and selling by online investors play in determining market returns. The daily autocorrelations of the QQQ will be examined first, followed by the daily cross-correlations between the QQQ and the ETF for the broader market index of the S&P 500. For comparison purposes, similar results are provided for the MDY. Finally, the relative strengths of the two statistical measures will be estimated jointly to determine if the lagged returns of a given security or the cross-correlations dominate the most recent return of the examined stock. DATA One of the major online brokerage firms, Ameritrade, has began to publish the Ameritrade Online Investor Index (AOII), a daily measure of the amount of buyer participation based on a decisions made by the firm's online investors (Ameritrade Press Release, 12/1/1999). On every trading day, after the U.S. markets have closed, Ameritrade posts the Ameritrade Index page on the Internet. One of the stated goals of the index is to measure the individual investment decisions of online investment individuals. …