By: Jack Zimmerman
Introduction
To predict the stock return, this is the wildest goal by most of investors all along. In the report, a methodology is showed to try to predict the return in stock market by some related effective element. The Michigan Consumer Sentiment Index (MCSI) is used as the main independent variable to predict the effect to stock return change in United State stock market.
MCSI and the US stock market
The Michigan consumer sentiment index is an indicator of future national economy and normally associated with the interest rate, inflation, consumption and unemployment, etc. It measures how consumers view prospects for their own financial situation and the state overall economy in the short run and long run. According to their own expectation of the future economy, they would make decisions of spending and investing at the present time. Basically, economic optimism is likely to stimulate the expenditure and investment while economic pessimism would lead to postponement of spending and investing.
There are different views whether CSI directly or indirectly affect stock returns in academic world. From conventional proposition, CSI has indirect effect for the stock prices via wealth effect, investment and credit market imperfections. Generally, improvements in consumer confidence stimulate consumption growth at least in the short run and also lead to the lower interest rates and higher expected returns. An negative relation between short-term interest rates and aggregate stock returns has been documented by Fama and Schwert (1977). And Fama (1975) also reported that expected returns are negatively related to expected inflation.
In contrast, Jansen & Nahuis (2002) claimed that CSI transmits influence on stock prices via independent channel. According to their empirical evidence of 11 European countries during the period form 1986 to 2001, they found CSI were positively correlated with stock returns for 9 countries. Furthermore, Lemmon & Portniaguina (2004) reported that high investor optimism are followed by lower returns on stocks with non-paying dividend, low earning growth, low sales and low institutional ownership.
Overall, higher CCI is likely associated with higher returns and vice versa. It is possible that consumers tend to hold on their money if they feel unsure enough about their future finances and they would like to be investors of individual stocks or mutual funds during the economical expansion.
Data
The Consumer Sentiment Index data is monthly time-series data from the University of Michigan, which is so-called Michigan Sentiment Index, from January 1978 to March 2006. The survey polls 5000 American households on their personal financial situation, the prospect to whole economy of the U.S. and their propensity to purchases of durable goods. Because all questions are about expectation for the future, it is possible that the preliminary results can be announced at the beginning of the current month.
The sector indices in the U.S. stock market are monthly data in 10 sectors, which are automobile manufacturing, finance, gas, industry, machinery, material, movie & entertainment, steel, telecommunication and transport, from Global Financial Data at the same time period. The indices data are obtained at the end of every month.
Comparison to A Benchmark Strategy
Both my sentiment strategy and a benchmark buy-and-hold Strategy start with a $1000 investment in April 1996. I am going to test how much it would be worth by adopting those two strategies at the end of March of 2006.
The buy-and-hold strategy is to buy six sector indices with the close price in April, 1996 and hold it until March of 2006. Then we can calculate average returns and standard deviations by taking this strategy.
My trading strategy is that investors should only buy sector indices when returns predicted this month is higher than risk-free rate; on the other hand, they only can make a one-month deposit at the risk free rate if it is lower than risk-free rate. By trading in this way, investors would outperform the buy-and-hold strategy and make excess profits. The results are shown as follows in table 5. Unfortunately, the coefficients ofβare not significant at all.
About The Author:
Jack Zimmerman is an associate staff writer. Upon graduation, he started working with other freelance writers for on-line writing agencies.
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