Stock Open price Prediction

 In this reading, we are working on our first real time project.

 Development phases:

1. Data Acquisition
2. Data Exploration
3. Data Modeling and evaluation
4. Model Deployment & operations
5. Model optimization

 Algorithmic trading Automated stock open price prediction

Stock open price is a price when trading starts. Algorithmic trading is also known as Automated trading, it uses computer program that fallows set of instructions to place a trade.

A mutual fund organization wants to set up an automated trading process in their stock trading unit.

Here the scenario is, Fund manager select a list of stocks for trading. For that they want to know open price. Based on that estimated price, they will decide to booking orders for trading(whether buying or selling).

Estimate the stock open price for the selected stock on a trading platform with web interface. Web interface is the web page where client will select stocks and get estimated open price. This estimated price should be available during the trading hours means when the trading begins.

Capture real time ticks, means change in price for one trade to next trade these can be integrated with estimated price with web interface.

* If we provide E-mail notification and mobile alerts for the selected stocks open price before trading begins, which will be additional advantage.

This is the case the convergence happened between client and us. For fulfilling these requirements we need to build a model and train it for better accuracy.

Estimated price verified with real time ticks, and average accuracy of the estimated price is above 90% with tolerance of below 10% in individual values. Means variations in individual values should not be greater than or equal to 10%.

• Web interface is a place where an interaction happened between the user and software. Here client will submit selected stocks and get an estimated open price.
• Web server can handle and process the web interface.
• Python API is an application program interface that retrieve output from ML model.
• Database is where vast amount of data is stored and retrieved when it required.