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http://localhost:8080/xmlui/handle/123456789/437| Title: | The Predictive Power of Macroeconomic Variables on the Indian Stock Market Utilizing an ANN Model Approach : An Empirical Investigation Based on BSE Sensex |
| Authors: | Chhabra, Meghna |
| Keywords: | Foreign Exchange BSE Sensex |
| Issue Date: | 2023 |
| Publisher: | Folia Oeconomica Stetinensia |
| Abstract: | The paper focuses on the use of Artificial Neural Networks (ANNs) for forecasting time series data of the stock market since ANNs are dynamic and are more capable of handling complex data sets in comparison to conventional forecasting techniques such as regression, Logistic regression, and have massive potential for the prediction of stock market prices. |
| Description: | Stock market prediction has long been of great interest to several investors, professionals, and researchers. Due to an inherently noisy and highly volatile environment, an accurate prediction of stocks is a difficult procedure (Ticknor, 2013). Various factors, including market news, political developments, and crises like COVID-19, influence the stock market’s movement. Several factors that affect the stock market have been discussed in previous literature, including the foreign exchange rate, the “index of industrial production,” the “consumer price index,” the “long-term interest rates,” the price of gold, Crude oil prices, the Indian Volatility Index, Morgan Stanley Capital International (MSCI) World Index, and the MSCI Emerging Market Index is added as a new variable to add novelty to the research. |
| URI: | http://localhost:8080/xmlui/handle/123456789/437 |
| Appears in Collections: | PGDM |
Files in This Item:
| File | Description | Size | Format | |
|---|---|---|---|---|
| Chhabra.pdf | 306.83 kB | Adobe PDF | View/Open |
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