Statement of the Problem
Basically I want to see if Stock “A” will reach its 52 week high on day one and on day two if it will break it again. This would be useful for investing because we would have information on the probability what Stock “A” will do the next day. Ultimately “Do I bet that a 52 week high stock will go up or down the next day?”
I became interested in a study like this because I participated in the Ohio Stock market Challenge, and feel this data could give me an advantage over other investors.
Overview:
The purpose of this study was to gain valuable investor knowledge in the stock market, especially with the “52 week high stocks”. Due to an assignment in which my class competed in a stock market simulation, I decided to test the 52 week high stocks. I always noticed that most 52 week high stocks, after breaking their high, rarely continue to break their high again on the next day.
I did some background research about the stock market prior to completing my study. Buying a stock means that you want the price of the stock to go up. Shorting a stock means that you want the price of the stock to go down. An easy way to think of it is that by buying a stock you are betting for the price to increase. Shorting a stock you are betting against the stock, and betting for the price to decrease. In my research I also learned that many investors react differently to 52 week high stocks. Some see 52 week high stocks and immediately buy, which can sometimes be called overconfidence.
On the website http://www.barchart.com/stocks/high.php I collected my data from. I collected information every morning before the stock market opened on the current day. I would take the stocks from all exchanges and copy it into excel. The number of 52 week high stocks for each day was: 198, 38, 103, 138, and 248 for a total of 477. The number of stocks that hit their 52 week high on consecutive days from those days was: 9, 8, 22, and 83 for a total of 122. When I ran a one Prop z test of the data I collected I rejected the null hypothesis that the proportion of 52 week high stocks breaking their high on consecutive days was = .30. I obtained a P-value of .0175 so at the .05 level of significance I rejected the null hypothesis. I failed to reject the alternative hypothesis that the proportion was less than .30. Therefore my study was a success because I have statistical information that the proportion of stocks hitting their 52 week high on consecutive days is rather smaller than the opposite proportion. So anyone looking to day trade by shorting some 52 week high stocks for a short time after the stocks break will have a reasonable and decent chance at succeeding and being successful in their investing.