The problem Stock Market Predictor and Analyzer solves

So as we all know the complexities of the stock market and how volatile and unpredictable it is. So we thought that there is a need of something like this model that can analyze and predict the future trends of stock market then it will be very useful for all investors and traders who are there in the stock market field. This model will specially be more useful to those people who sometimes loose all their money in the stock market or incur heavy losses and due to which infact many person even commit suicide. So to prevent such type of incidents , our model can be beneficial for them, we don't claim that our model will predict 100% accurate results but at least it can inform them or give them an idea about the future trends of a particular stock so that they can be cautious about it in the near future. We will also try to incorporate some new features in our model that will add some extra value to it and can be of more use and convenience to our customers , our family. Like we will also add portfolio manager or you can say we will tell the users their expected portfolio returns based on the stocks that are present in their portfolio. So that they can manage their portfolio accordingly. This will be of great help to them as any investor or trader focuses on their overall portfolio returns as that's the thing that matters the most in the stock market field.

Challenges we ran into

Yeah, there were lots of challlanges we faced like 1st was to get or importing a clean data of some particular stocks so that we can analyze and predict its future trends with ease. so we overcame that by searching on web about from where to get free opne source clean and genuine data, Then we also faced some prob in plotting the candelstick pattern graphs in the analyzer part. so again we surfed the net regarding it and watched some videos on youtube and sorted it out. Next in the predictor part the most challenging task was to build a model with good accuracy as we choose ARIMA model so selecting the value of p,d and q was a diificult task but again we got some idea from internet and calculated mean squared error and other errors and the goal was to minimize it by taking p,d and q values accordingly. so finally we were able to minimize that error for two stocks but ig in the model of last stock that error eas still high. So to a great extent we faced difficulties but we sorted it out based on our knowledge, Internet surfing and watching videos.