One of the hottest Technologies into the Finance (and also Investment Banking) field actually is Python, and the reason it is pretty simple:
- Easy to Read and Learn
- The most used modules are written in C++, so it is Efficient.
Also, you can use Cython to obtain the vantages of a “Compiled language” - Huge Community: this means huge numbers of libraries, modules, and readily available functions.
Some people (non-programmers) believe that coding is necessarily a “Techincal” thing, the truth is that is more a Creative thing than a “procedural one”.
If you can imagine it, you can develop it: nobody and nothing can stop you.
A good programmer is more creative than procedural.
So, since I’m recently transferred in Nice a few days ago to study Finance (the top 3 University for MSc in Finance worldwide), I was strongly motivated to develop my Network and get the attention of my new Course Colleagues.
The reason is simple: if I’m useful to someone, the other person can become useful to me (win-win strategy), maybe developing some interesting future project.
Having a free weekend before the starting of the lessons, I decided to ideate a creative project building a Fintech Advisor, using Python (ML), AWS Cloud Computing and Telegram.
The 3 main features it has are:
- Crypto Sentiment Analysis.
You can select whatever crypto you want (from the Coinmarketcap website), and using a starting period (which define the horizon of your analysis), you can obtain an Estimation of the True Crypto Price according to his Community’s Size obtained with a Machine Learning Algorithm (a methodology described in one of my past articles). - Cover Letter Keywords.
How many times did we ask how to write a Cover Letter or which words to use in our CV?
Now we just have to use the Data: you insert the name of your desired job, and after 2-3 minutes the bot will send you an estimation of the most frequent Keywords used by Employers in their Job Offers (estimation made in real-time on approximately 1000 Job Offer). - Stock Price Time Series Download.
Sometimes is difficult for a student to find online Financial Datasets.
So I made it pretty easy, you insert the Ticker of the Stock (ex. AAPL for Apple), the starting period and the end period.
You will obtain a plot of this time series (close price) and a Dataset (CSV format) with the main financial data (daily).
You can test it on this link (you have to Download Telegram, an App similar to WhatsApp but more powerful):
https://t.me/DisruptiveFinance_bot
Let’s try it! And if you discover some interesting correlation on unknown crypto on a specific time horizon and you make money, please remember me!
I hope that sharing my project is useful: if you want to learn more please comment here or contact me via the contact section!