Details

Autor(en) / Beteiligte

• Das, Kaushik
• Ahmed, Nazia
• Tabasshum, Anika
• Azad, Tahzib
• Chowdhury, Nuzhat
• Mostakim, Moin
• Noor, Jannatun

Titel

Stock Price Prediction During Pandemic Situation

Ist Teil von

• 2023 26th International Conference on Computer and Information Technology (ICCIT), 2023, p.1-6

Ort / Verlag

IEEE

Erscheinungsjahr

2023

Quelle

IEEE Xplore

Beschreibungen/Notizen

• Accurately predicting the stock value enables investors to earn more money, reducing their uncertainty on whether to buy or sell. Again during the COVID-19 period, many companies have shown a different picture of the stock market situation. That is why investors cannot consider the company's exact status in the stock market. The primary objective of our paper is to predict the future behavior of the stock market in the event of a pandemic using machine learning classification. To consider the future stock market condition, first, we looked at the past stock market condition and tried to make predictions by collecting data from two companies. Second, we tried to understand what happened in the stock market during the pandemic and used machine learning algorithms. Finally, make predictions through machine learning classifications by merging the data during the pandemic with past data. In conclusion, we have attempted to identify what was lacking in our instance and provide a concise description of the next steps.