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Synthesizing Technical Analysis, Fundamental Analysis Artificial Intelligence – An Applied Approach to Portfolio Optimisation Performance Analysis of Stock Prices in India

机译:综合技术分析,基础分析和人工智能–印度股票价格组合优化和绩效分析的应用方法

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As the Wall Street saying goes: ‘The crowd is right in the trends and wrong at the ends.’ Most of the participants in the investment arena are unaware of the mathematics, science & psychology behind the Technical analysis, Fundamental analysis, & Artificial Intelligence in financial markets. In this paper, we use Technical Analysis (Relative Strength Index), Fundamental analysis, and Artificial Intelligence to optimize the portfolio & review of their performance on Nifty fifty selected stocks. i.e., Reliance Industry Ltd, ICICI Bank, HDFC Bank, Axis Bank, TCS. The main aim is to evaluate & validate Relative Strength Index efficiency & effectiveness of the Indian stock market. The following objective is to design a system trading setup & develop a backtesting strategy to optimize the portfolio. The empirical analysis includes backtesting of optimized indicators representing the desired portfolio, i.e., Reliance industry ltd, ICICI Bank, HDFC Bank from Jan 2013 to Jan 2020. To understand the efficiency of the portfolio & backtesting of portfolio done with the help of Amibroker software.
机译:正如华尔街所说:“趋势是正确的,终点是错误的。”投资领域的大多数参与者都不了解技术分析,基础分析和人工智能背后的数学,科学和心理学。在金融市场上。在本文中,我们使用技术分析(相对强度指数),基本面分析和人工智能来优化投资组合,并评估其在Nifty精选的50只股票上的表现。即Reliance Industry Ltd,ICICI银行,HDFC银行,Axis银行,TCS。主要目的是评估和验证印度股票市场的相对强度指数的效率和有效性。以下目标是设计系统交易设置并开发回测策略以优化投资组合。实证分析包括对代表所需投资组合的优化指标进行回测,即从2013年1月至2020年1月,是信实工业有限公司,ICICI银行,HDFC银行。要了解投资组合的效率以及借助Amibroker软件进行的投资组合回测。

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