## 4 Data Processing and Features  
Most researchers used day-wise data having OPEN, HIGH, LOW, CLOSE, and VOLUME (OHLCV), and some researchers used tick data may be a minute-wise or five-minute tick, or fifteen-minute tick data for their research. Some researchers work on sentiment analysis used text data such as tweets and comments. _Different Types of Data Used in Stock Market Prediction_  
**(a) Historical Price Market Data (Day Wise)**  
Generally, the historical data consist of the stock's open price, high price, low price, close price, and traded volume. The following is an example of the TATAMOTORS day-wise data set [9; 10; 26; 27; 28; 36; 43; 54; 79; 80]. Table 4 shows date-wise stock market data. Generally, tick historical data contain the open price, high price low price, close price, and trading volume of the stock, and they are used for prediction in intraday trading. Table 5 shows minute-wise stock market data. \begin{table}
\begin{tabular}{l c c c c c c} \hline \hline
**Date** & **Prev. Close** & **Open** & **High** & **Low** & **Close** & **Volume** \\ \hline
1 December 2014 & 533.5 & 539.85 & 539.85 & 530.1 & 536 & 5093458 \\ \hline
2 December 2014 & 536 & 535.7 & 535.8 & 528.1 & 528.95 & 355543 \\ \hline
3 December 2014 & 528.95 & 535.2 & 538.8 & 526.3 & 529 & 3997174 \\ \hline
4 December 2014 & 529 & 534 & 537.25 & 522 & 527.75 & 3600835 \\ \hline \hline \(\ldots\)\(\ldots\) & \(\ldots\)\(\ldots\) & \(\ldots\)\(\ldots\) & \(\ldots\)\(\ldots\) & \(\ldots\)\(\ldots\) & \(\ldots\)\(\ldots\) & \(\ldots\)\(\ldots\) \\ \hline \hline \end{tabular}
\end{table} 
Table 4: A sample of the TATAMOTORS company’s day-wise historical data. \begin{table}
\begin{tabular}{l c c} \hline \hline
**Journal/Publisher** & **Count** & **Article** \\ \hline MDPI & 12 & [4; 7; 10; 20; 27; 28; 29; 37; 54; 56; 57; 63] \\ \hline Expert System with Application & 10 & [1; 39; 40; 59; 64; 72; 73; 74; 75; 76] \\ \hline Expert Systems & 2 & [38; 58] \\ \hline IEEE Access & 5 & [31; 32; 45; 61; 67] \\ \hline neurocomputing & 3 & [21; 34; 21; 34; 69] \\ \hline Applied Intelligence & 2 & [9; 36] \\ \hline IEEE Transactions & 1 & [8] \\ \hline Information Sciences & 1 & [46] \\ \hline Soft Computing & 3 & [49; 50; 51] \\ \hline PLoS ONE & 1 & [22] \\ \hline Conference Papers & 3 & [48; 70; 71] \\ \hline Others & 19+ & [3; 23; 24; 25; 26; 30; 33; 35; 44; 47; 53; 65; 66; 68; 77; 78] \\ \hline \hline \end{tabular}
\end{table} 
Table 3: Journal names and the total number of articles considered are included in this review. \begin{table}
\begin{tabular}{c c c c c c c} \hline \hline
**Stock Symbol** & **Time** & **Open** & **High** & **Low** & **Close** & **Volume** \\ \hline SBIN & 09:08 & 492.65 & 492.65 & 492.65 & 492.65 & 53244 \\ \hline SBIN & 09:16 & 492.8 & 494.6 & 491.85 & 494 & 159589 \\ \hline SBIN & 09:17 & 493.9 & 494.15 & 493.75 & 494.15 & 162984 \\ \hline SBIN & 09:18 & 494.3 & 495 & 493.5 & 494 & 123425 \\ \hline \hline \(\ldots\)\(\ldots\)\(\ldots\) & \(\ldots\)\(\ldots\)\(\ldots\) & \(\ldots\)\(\ldots\)\(\ldots\)\(\ldots\) & \(\ldots\)\(\ldots\)\(\ldots\) & \(\ldots\)\(\ldots\)\(\ldots\) & \(\ldots\)\(\ldots\)\(\ldots\) \\ \hline \hline \end{tabular}
\end{table} 
Table 5: An example of the minute-by-minute historical data collected by the State Bank of India. **(c) Tweets or Comments (Text Data)**  
Twitter is now one of the most often used social networks for performing sentiment research. The stock market is the topic of discussion in this collection of tweets' data. Tweets were carefully labeled as being in either the favorable, neutral, or negative categories [81,82]. **(d) Image data**  
Image processing is strong with CNN. These algorithms are the best for automated image processing. Many firms utilize these algorithms to detect visual items. Candlestick charts are used as the input image for stock prediction. Input image for stock prediction is often represented by a candlestick chart.