Learn Python for a Bright Future in Finance
Aaditya Jain Classes has created a platform where finance professionals can increase their earning capabilities by enrolling in these professionally crafted extensive certification courses.
Python: — Python is an exciting and powerful language with the right combination of performance and features that make programming fun and easy. It is simple, high-level, object-oriented, and a reliable language. It’s being used by leading companies in a variety of fields. For example, Bank of America’s Quartz and JPMorgan’s Athena platforms both use python, and big companies like Google, Facebook, Instagram, and Spotify are built on python only.
Python is used for :-
- Web development (Server-side)
- Software development
- System Scripting
- Finance, etc.
Python In Finance
Over the years, Python has become one of the best programming languages in financial institutions. According to the HakerRank, 2018 Developer Skills report Python was among the top three most popular languages in financial services. eFinancial Careers showed that during the last two years the number of finance-related jobs in Python has almost tripled. Some Organisations now offer to provide Python coding and learning classes to banking analysts and traders as a process of their education program.
It is easy to conduct various market analyses using Python. For example, one can draft scripts that will analyze the present information on the market and make predictions based on that. Python is currently the main language used to create pricing, risk, and trade managing platforms for investment banks.
Python- A great technology especially for finance professionals:-
Several attributes of Python make it a great choice for financial professionals. Although, here is a list of the most important ones:
1. Simple and flexible:-
It is the best choice for handling financial services applications that are complex, as Python is easy to write and implement. The syntax is simple and enhances the speed of helping organizations to build software to integrate with their products. It also mitigates the rate of errors during product development in finance that comes under high regulations.
2. Develops Minimal Viable Product (MVP) faster:-
It allows building an MVP quickly. The financial services industry needs to be more responsive to the growing demands, offering customized experiences and value-added services. This is why financial organizations need a technology that is quite flexible and measurable — and that’s what Python exactly offers. After validation of the MVP, businesses can change parts of the coding or add new ones to create a perfect product.
3. Bridges the gap between data science and economic:-
Python simplifies calculations for a finance professional with its simplicity and practicality in creating formulas and algorithms to integrate the work of economists in the Python platform.
Uses of Python in Finance:-
1. Banking Software: — Finance organizations build payment solutions and online banking platforms with Python as well. Venmo is an excellent example of a mobile banking platform that has grown into a full-fledged social network. Python comes in handy for developing ATM Software that enhances payment processes.
Example of such products:-Venmo, Zopa, Robinhood.
2. Crypto-currency: — Every business that sells crypto-currency needs tools for carrying out crypto-currency market analysis to get insights and predictions. The Python ecosystem called Anaconda assists developers in retrieving crypto-currency pricing and in analyzing it or creating visualizations.
Examples of such products:-Dash, enigma, ZeroNet, Crypto-signal.
3. Building a trading strategy with Python: — Stock market generates massive amounts of data that require a lot of analysis. Developers can use it to create solutions that identify the best trading strategies and offer predictive analytical insights into the condition of specific markets.
Example of such product: — Zipline, IBPy, Braktrader.
4. Analytics tools:- Python is widely used in finance in providing solutions that process and analyze large databases and big financial data. Libraries such as Pandas simplify the processes of data visualization and thus allow carrying out sophisticated calculations.
Example of such product:- Iwoca, Holvi