Course description
Python for Finance
Python is increasingly being seen as an essential skill for everyone working in finance. This highly practical course is intensively focused on how Python can be used in a range of real-world finance applications.
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Upcoming start dates
Suitability - Who should attend?
Who Should Attend
Anyone who wants to use Python in practical financial applications.
Prerequisites
You should be familiar with the content of our Introduction to Python course.
Outcome / Qualification etc.
CPD: 14 hours
Learning Outcomes
By attending this course, you will:
- Explore a wide range of Python libraries essential for building financial applications
- Explore how to source, download, scrub, analyse, and visualize financial data
- Learn how to build practical Python applications in investment management, derivatives pricing, and algorithmic trading
Training Course Content
Review of Essential Skills
- Defining and using functions
- 💻 Creating and using a PV function
- Working with classes
- 💻 Creating and using a bond class
- Working with arrays
- Generating random numbers
- 💻 Implementing random-walk price sequence
Python Libraries for Finance
- The essentials:
- Pandas
- SciPy
- NumPy
- Statistics
- Matplotlib
- Finance libraries:
- Pyfin
- QuantPy
- QuantLib
- Quant DSL
- Ffn
- Quandl
- Pynance
- PyAlgoTrade
- Zipline
Working with Data
- Sources of financial data
- Time-series data
- Downloading
- Cleaning / scrubbing
- Transformations
- Analyzing
- Displaying
- Data visualization
- Interfacing Python with Excel
- 💻 Analyzing historical volatility
Real-World Finance Applications
Investment Management
- Working with securities portfolios
- Generating the efficient frontier
- Calculating alpha, beta, and the Sharpe ratio
- 💻 Building an optimal investment portfolio
Option Pricing
- 💻 Implementing the Black Scholes model for option pricing
- 💻 Implementing a Monte-Carlo pricing model for a vanilla option
- 💻 Implementing a Monte-Carlo pricing model for exotic options
Trading Strategies
- Machine learning techniques
- Analyzing financial markets data
- 💻 Implementing an algorithmic trading strategy
Why choose ACF Academy
Over 100,000 professionals trained globally
Award-winning practical financial simulations
Consistently high ratings
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Expenses
- London: £1,825 (plus VAT)
- New York: $2,300
- Virtual: £1,575 (plus VAT)