How to evaluate portfolios, mitigate risk exposure, and use the Monte Carlo simulation to model probability. Next, you’ll learn how to rebalance a portfolio using neural networks. Through interactive coding exercises, you’ll use powerful libraries, including SciPy, statsmodels, scikit-learn, TensorFlow, Keras, and XGBoost, to examine and manage risk. You’ll then apply what you’ve learned to answer questions commonly faced by financial firms, such as whether or not to approve a loan or a credit card request, using machine learning and financial techniques. Along the way, you’ll also create GARCH models and get hands-on with real datasets that feature Microsoft stocks, historical foreign exchange rates, and cryptocurrency data.
Applied Finance Trainee Responsibilities:
- Week 1 & 2: Series of Training Modules (Training Period)
- Week 3 : Project Assigned
- Week 4: Project Report to be submitted
Applied Finance Trainee Requirements:
- Bachelor’s degree holder or pursuing.
- Proficiency with computers, especially MS Office.
- High level of accountability and motivation.
- Strong Interpersonal, time and project management, presentation, leadership, and communication skills.
- Creativity and ability to delegate responsibilities.
- Receptiveness to feedback and adaptability.
- Willingness to meet deadlines.