Financial planning is very important specially in uncertain times like this decade. We have seen how devastated the world could get by a blow of a pandemic and in event of a war. Price hikes and market crashes could leave thousands of families in distress. However, things could’ve been much different if financial knowledge was accessible to the common people. In fact not just Canadian, most of the world’s earning population does not have a proper retirement plan and does not know where to start when building a portfolio. This project aims to solve that problem by building an application that is user friendly and contains all the knowledge of where to start investing, how to build a portfolio, where to invest and how their investment could look like in the next 5-10 years including technical insights of whats affecting or could influence their investment. Furthermore this project provides suggestions of whether a person can retire in the next few years based on their current plan and what changes needs to be brought in if not. The builtin features of this app will enable the users to have an in-depth knowledge of the companies they would like to invest and what others are saying about it. Any further confusion the user may have, could be answered by the Chatbot which will be trained every now and then to provide as much accurate answers and solutions as possible.
More than 54% of Canadians do not have a retirement plan. More than half of that does not have a proper savings. This might not seem like a big problem just by eyeballing it, but when we consider what the world has been going through for the past few years, these numbers are very critical. This means in an event of a recession, half the population are not prepared to face it, and half of that won’t survive the month after loosing their jobs. Hence, financial planning is very necessary, no matter how much the annual income of a family is, building a portfolio and having an emergency fund by investing and putting money at the right place is very important.
Data Cleaning and Analysis
Predictive Models and implementing future projections using APIs
Using Twitter and News API for sentiment analysis using NLP
Getting Hands on with the streamlit app
Training and testing the ML models
Training and Testing the ML models continued.
Deploying the application.
1. Collection of Data. 2. Data Cleaning. 3. Data Analysis. 4. Data Visualization. 5. Use of API in finance. 6. Algorithmic Trading. 7. Deep Learning. 8. AWS