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Authors

Shristi Dhakal

Abstract

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.

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