LITERATURE REVIEW
REVIEW 1:
According to Jan Ivar Larsen, the direction of future stock prices is predicted based on the historical stock data. ‘Novel Two-layer reasoning approach’ is used by the developed stock price prediction model; where the domain knowledge from technical analysis is employed in the first layer of reasoning to guide a second layer of reasoning based machine learning. The money management strategy supplements the model which uses the historical success of predictions made by the model to determine the amount of capital to invest on future predictions. In the review he objects to provide a knowledge-intensive and computationally efficient coarse-grained analysis of historical prices which can be analysed further in a second layer of reasoning.
The domain knowledge implemented in the module is thus limited to methods and techniques in technical analysis. The technical analysis literature includes a wealth of different stock analysis techniques, some of which involve complicated and intricate price patterns subjective in both detection and interpretation. These methods would be both expensive to detect and evaluate, and have consequently been disregarded. They thus apply Occam’s razor to the choice of methods in technical analysis, focusing on the most popular indicators that can be efficiently operationalized and are intuitive in interpretation. It seems overly presumptuous to believe that historical price fluctuations alone can be used to predict the direction of future prices. It may thus seem natural to include some fundamental analysis knowledge in the feature generation process. However, due to the inherent limitations in time and the added complexity of including a second analysis technique, this has not ...
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...0% to 40% of practitioners appear to believe that technical analysis is an important factor in determining price movement at shorter time horizons up to 6 months. Further an overview is provided of theoretical models that include implications about the profitability of technical analysis. Conventional efficient market theories, such as the martingale model and random walk models, rule out the possibility of technical trading profits in speculative markets, while relatively recent models such as noisy rational expectation models or behavioural models suggest that technical trading strategies may be profitable due to noise in the market or investors’ irrational behaviour. Finally, empirical studies are surveyed. In this report, the empirical literature is categorized into two groups, “early” and “modern” studies, according to the characteristics of testing procedures.
In the recent week, the Chevron Corp. stock can be easily categorized into one that has been oversold trading as low as $111.25 per share. A technical analyst defines an oversold position using the RSI, Relative Strength Index, to measure the momentum on a 0 to 100 scale. A stock will be called oversold, if the RSI falls below 30, and in the case of CVX Stock Analysis, it has already hit 28.1, which by comparison to other in the energy stock is low, the others averaging just above 50. Investor can always assume that the trend is one that will exhaust itself soon, but the analysts see the heavy selling as one that will continue for a few months, unless the Chevron stocks show a positive financial sign such as an increase in revenue, resumption of Gulf of Mexico operations, or some stretch in the margins of fuel products.
The Dow Theory was established from a series of Wall Street Journal editorials authored by Charles H. Dow from 1900 until the time of his death in 1902. Today, even after 110 years they remain the foundation of what we know today as technical analysis. Dow never published his complete theory, but several of his followers compiled his works and that has come to be known as "The Dow Theory”.
Over the last couple of decades there has been a debate going whether or not there are behavioral aspects in finance. This means that financial markets are subject to different investors’ sentiments and that markets are not efficient, i.e. the efficient market hypothesis (EMH) does not hold. The supporters of EMH argue that all available information is included in the stock prices, which means that any long-term abnormal returns earned are a matter of chance. On the other side, the supporters of behavioral finance argues that because of over- and under-reaction by investors to information, it takes time before prices fully adjust and thus there is an opportunity to earn long-term abnormal returns.
Over history financial advisors have played a very important role in society by handling the money of all different types of people, rich or poor, through depressions as well as economic booms. These advisors help people retire and save for events in life that are expected as well as unexpected and are ingrained in a society with ever-changing wants and needs. However, what if the same services that a human financial advisor can be made so that they are cheaper to use and can better predict market volatility? Computer programming using financial market data and other sources like the news are trying to do just that. With the availability of data on the Internet and other database resources with financial decision making tools like Morningstar
A generation ago, it was generally believed that security markets were efficient in adjusting information about individual stocks and stock market as a whole (Malkiel, (2003)). However, we cannot deny the efficient market hypothesis has several paradoxes.
Macroeconomic factors, like Gross Domestic Product, exchange rate, interest rate, inflation rate, money supply, economic crisis and economic liberalization affects the stock market returns in Malaysia. Stock market is critically important to our economy as it channels funds and capital from those who have excess to firms, corporations or individual that can use them more effectively. Several analysis were used to determine the accurate stock market returns and their relationships with the macroeconomic determinants in Malaysia. Precise information about the stock market returns volatility is crucial for decision making by firm from different industry to understand deeper about how Malaysia stock market works to be able to build the right strategy in handling their funds and creating better management portfolio and financial plans. Leverage effects, which stated that negative news and announcements brings bigger volume of shocks to stock market compared to positive news, causing volatility in stock market was found to be exist in Malaysia stock market. Several analysis such as dynamic stock returns volatility estimation, Exponential Generalized Autoregressive Conditional Heteroskedasticity (EGARCH), generalized least squares (GLS) regressions and Random effects (Feasible Generalized Least Squares)
We analyzed the market for two weeks to determine when the equity market would turn from a bearish to bullish market. Without a change in the market and a declining bond price, we decided to invest in equities according to our investment strategy, which brought us into the second phase of our portfolio. Therefore, at the beginning of February we bought shares in Sirius, Microsoft, Neon, Washington Mutual, and Nike. As assumed, the equity market continued to plummet decreasing the value of all our stocks except for our Gold Corporation stock.
Capital Asset Pricing Model (CAPM) is an ex ante concept, which is built on the portfolio theory established by Markowitz (Bhatnagar and Ramlogan 2012). It enhances the understanding of elements of asset prices, specifically the linear relationship between risk and expected return (Perold 2004). The direct correlation between risk and return is well defined by the security market line (SML), where market risk of an asset is associated with the return and risk of the market along with the risk free rate to estimate expected return on an asset (Watson and Head 1998 cited in Laubscher 2002).
Chapter 11 closes our discussion with several insights into the efficient market theory. There have been many attempts to discredit the random walk theory, but none of the theories hold against empirical evidence. Any pattern that is noticed by investors will disappear as investors try to exploit it and the valuation methods of growth rate are far too difficult to predict. As we said before the random walk concludes that no patterns exist in the market, pricing is accurate and all information available is already incorporated into the stock price. Therefore the market is efficient. Even if errors do occur in short-run pricing, they will correct themselves in the long run. The random walk suggest that short-term prices cannot be predicted and to buy stocks for the long run. Malkiel concludes the best way to consistently be profitable is to buy and hold a broad based market index fund. As the market rises so will the investors returns since historically the market continues to rise as a whole.
The efficient market hypothesis has been one of the main topics of academic finance research. The efficient market hypotheses also know as the joint hypothesis problem, asserts that financial markets lack solid hard information in making decisions. Efficient market hypothesis claims it is impossible to beat the market because stock market efficiency causes existing share prices to always incorporate and reflect all relevant information . According to efficient market hypothesis stocks always trade at their fair value on stock exchanges, making it impossible for investors to either purchase undervalued stocks or sell stocks for inflated prices. As such, it should be impossible to outperform the overall market through expert stock selection or market timing, and that the only way an investor can possibly obtain higher returns is by purchasing riskier investments . In reality once cannot always achieve returns in excess of average market return on a risk-adjusted basis. They have been numerous arguments against the efficient market hypothesis. Some researches point out the fact financial theories are subjective, in other words they are ideas that try to explain how markets work and behave.
Choosing two profitable stocks amongst a myriad of potential alternatives is a daunting task to say the least. In order to narrow my choices from thousands to two, I examined several aspects of companies I was interested in. Among these were, company overview, alpha and beta ratings, price ratios, price charts, and company headlines. After evaluating this information, I chose Intuit INC (INTU) listed on the NASDAQ and Johnson and Johnson (JNJ) listed on the NYSE.
Stock market prediction is the method of predicting the price of a company’s stock. It is believed that stock price is lead by random walk hypothesis. Random walk hypothesis states that stock market price matures randomly and hence can’t be predicted. Pesaran (2003) states that it is often argued that if stock markets are efficient then it should not be possible to predict stock returns. In fact, it is easily seen that stock market returns will be non-predictable only if market efficiency is combined with risk neutrality. On the other hand it is also been concluded that using variance ratio tests long horizon stock market returns can be predicted....
me on a volunteer project I did in high school. The summer after my junior year
Decision support systems (DSS) and expert systems (ES) play critical role in solving various financial and business problems, where data processing for deriving new information, yielding possible solutions or their alternatives is a significant part of relevant computations. Section 3.1 gives a brief introduction to DSS and ES, discusses their goals and main differences from standard information systems (IS). Section 3.2 reviews main types and taxonomies of DSS, while relating them to financial risk oriented problems. Section 3.3 discusses recent developments in DSS for financial problems, related to credit risk, while Section 3.4 enlists a number of requirements for modern DSS dedicated to banking decisions. Further, we discuss the development of novel DSS based on AI techniques, described in
This paper will define and discuss five financial theories and how they impact business decisions made by financial managers. The theories will be the Modern Portfolio Theory, Tobin Separation Theorem, Equilibrium Theory, Arbitrage Pricing Theory (APT), and the Efficient Markets Hypothesis.