This paper utilizes hybrid financial systems (HFSs) to model Karachi Stock Exchange index data, KSE100. These models are used for short-term forecasting of Karachi Stock Exchange index data, KSE100. These HFSs developed for this purpose are combination of artificial neural networks (ANN) model ...
shap_values(map2layer(to_explain, 7), ranked_outputs=2) # get the names for the classes index_names = np.vectorize(lambda x: class_names[str(x)][1])(indexes) # plot the explanations shap.image_plot(shap_values, to_explain, index_names) Predictions for two input images are explained...
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A thorough validation procedure and the most recent KSE 100 index prediction using LSTM and backpropagation algorithms demonstrate how machine learning may improve stock market forecasting. The study's accurate projections and consistent data through September 2023 are crucial...
Multiple regression model is applied on the data and the result shows that there is a weak relationship between the dependent variable and independent variables. The impact of interest rate and inflation is insignificant on stock returns of KSE 100 index while the exchange rate has significant ...
First stationarity of the data was checked through Augmented-Dicky Fuller test; then GARCH (1,1) model was estimated for both the spot and future index returns in order to investigate the volatility in either of the index. The results of GARCH (1, 1) suggest that the impact of the ...