Shristi Dhakal


Whether stock prices can be accurately forecasted or not is usually associated with whether markets are efficient or not. The idea of market efficiency suggested by the Efficient Market Hypothesis has been debated among financial professionals for a long time, especially due to the occurrence of financial bubbles in the past. Some argue that stock prices prediction is no different than the results of “a series of tosses of a coin, rolls of a die, or spins of a roulette wheel,” while others argue that stock prices are affected by past patterns, which can be used to forecast future prices [11]. Although a concrete answer has yet to be found on the behavior of the stock market, researchers have continued exploring the topic and have established various quantitative models for forecasting, one of which is clustering. This paper evaluates the application of the clustering method of stock forecasting by analyzing the financial statements of technology companies over a period of four years.



To view the content in your browser, please download Adobe Reader or, alternately,
you may Download the file to your hard drive.

NOTE: The latest versions of Adobe Reader do not support viewing PDF files within Firefox on Mac OS and if you are using a modern (Intel) Mac, there is no official plugin for viewing PDF files within the browser window.