Future Stock Prices are Based on the Past

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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.
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