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Stock Market Price Prediction Using Technical Analysis and ANN Model - P Karthikeyan - Bog

Bag om Stock Market Price Prediction Using Technical Analysis and ANN Model

The Book on ¿STOCK MARKET PRICE PREDICTION USING TECHNICAL ANALYSIS AND AN ATTEMPT WITH ARTIFICIAL NEURAL NETWORK MODEL¿ attempts to predict the stock price of the Nifty Fifty companies using Technical Analysis and ANN Model. The companies are grouped based on the sectors they belong to. Various analysis have used to predict the Stock prices. The time period taken for the study is from January 2017 to December 2017. The nature of the data is tested by using the descriptive statistics i.e. mean, median, mode, kurtosis and skewness. Then by calculating Moving Average and Exponential Moving Average, the price expectancy of the shares and the volatility of the share prices are known.Relative Strength Index is calculated to know whether the shares of the companies have to buy or sold or to hold by the investors. Rate Of Change is calculated to know the movement of the share price i.e. whether upward trend or downward trend. The results are interpreted sector wise by taking a single company from each sector that gives higher percentage return. An attempt to predict the stock price by using Artificial Neural Network is made.

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  • Sprog:
  • Engelsk
  • ISBN:
  • 9786139454358
  • Indbinding:
  • Paperback
  • Sideantal:
  • 116
  • Udgivet:
  • 25. februar 2019
  • Størrelse:
  • 229x152x7 mm.
  • Vægt:
  • 181 g.
  • 2-3 uger.
  • 12. december 2024

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  • BLACK WEEK

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Prøv i 30 dage for 45 kr.
Herefter fra 79 kr./md. Ingen binding.

Beskrivelse af Stock Market Price Prediction Using Technical Analysis and ANN Model

The Book on ¿STOCK MARKET PRICE PREDICTION USING TECHNICAL ANALYSIS AND AN ATTEMPT WITH ARTIFICIAL NEURAL NETWORK MODEL¿ attempts to predict the stock price of the Nifty Fifty companies using Technical Analysis and ANN Model. The companies are grouped based on the sectors they belong to. Various analysis have used to predict the Stock prices. The time period taken for the study is from January 2017 to December 2017. The nature of the data is tested by using the descriptive statistics i.e. mean, median, mode, kurtosis and skewness. Then by calculating Moving Average and Exponential Moving Average, the price expectancy of the shares and the volatility of the share prices are known.Relative Strength Index is calculated to know whether the shares of the companies have to buy or sold or to hold by the investors. Rate Of Change is calculated to know the movement of the share price i.e. whether upward trend or downward trend. The results are interpreted sector wise by taking a single company from each sector that gives higher percentage return. An attempt to predict the stock price by using Artificial Neural Network is made.

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