Paper Title
Technical Analysis and Fundamental Analysis in Predicting Stock Market- A Systematic Comparison

Abstract
There have been different methods for predicting stock market fluctuations. There are several factors affecting the market price swings such as social, political, and financial changes. Stock market forecasting methods are classified into two broad categories, Fundamental Analysis, Technical Analysis. Although, there is an additional machine learning based method that takes advantage of algorithms such as Artificial Neural Networks, Decision Tree, and Support Vector Machines for predicting stock changes, this methodis rarely used on its own and is mostly used in combination with one of the Fundamental or Technical Analyses. In this research,comprehensive research on the application of the Fundamental and Technical Analyses including their pros and cons, effectiveness, and performance measures will be conducted. One of the most popular approaches to investment is trading in the stock market. Fundamental analysis and technical analysis are two common ways of forecasting stock prices. In fundamental analysis, financial reports of a company such as balance sheet, income statement, and statement of cash flows are the main parameters that investment decisions are based upon. The fundamental analysis is usually used by long-term investors, who wish to own an asset and take profit from the possession of those stocks. This type of analysis and investment requires a great deal of capital as well as a high level of knowledge in finance and mathematics. Mr. Warren Buffet is the most well-known investor, who has a long-term strategy and uses fundamental analysis. The short-term strategy for analyzing stock trends is called technical analysis, which is mostly used by institutional investor and day traders. The technical analysis is based on the analysis of the past trends to predict future changes. The reason for such an assumption is that price fluctuations are the results of the reaction of shareholders to different stimuli inside and outside the stock market such as market news, war, and political changes. Additionally, human beings tend to show almost the same psychological reactions in certain situations. For example, people tend to sell their winning stocks too early because they are afraid of losing the obtained benefit and also they prefer to keep the losing stocks too long to compensate for their loss in the future. In order to predict the stock trend, one way is to find repetitive patterns, learn from the repeatable patterns and use them for future predictions. Trend analysis and value trading are two methods of technical trading. Trend analysis was first introduced by Ralph Nelson Elliot (Prechter R. R., 2013), who proposed the concepts of waves in price trends. The ultimate goal in technical trading is to find the points, where the market trend gets reversed. In value trading, traders attempt to calculate the value of the stock by mathematical formulas such as moving averages and then compare the current price with its value to make trading decisions. If the price is bigger than its value, it will trigger a LONG signal, which is likely to result in profit. If the price falls below the actual value, it will trigger a SHORT signal to avoid losing more value. One of the first mathematical models to predict the actual value of the data was Graham’s number (Graham & Zweig, 2003). With the advancement of computer algorithms, a new type of trading called algorithmic trading has been used over the last 10 years. By using computer programs and also machine learning algorithms on historical data, future trends will better be predicted. Machine learning algorithms such as classification are used to fit the historical data into a model. These algorithms have the capability to learn from the repetition of the past patterns by training the algorithm with historical data. Keywords - Fundamental Analysis, Technical Analysis, Stock market prediction