Quantitative Finance with Python, Learn to Analyze Financial Markets using Python, Data Science, Machine Learning and Technical Analysis.
Interested in a lucrative and rewarding position in quantitative finance? Are you a professional working in finance or an individual working in Data Science and want to bridge the gap between Finance and Data Science and become a full on quant?
The role of a quantitative analyst in an investment bank, hedge fund, or financial company is an attractive career option for many quantitatively skilled professionals working in finance or other fields like data science, technology or engineering. If this describes you, what you need to move to the next level is a gateway to the quantitative finance knowledge required for this role that builds on the technical foundations you have already mastered.
This course is designed to be exactly such a gateway into the quant world. If you succeed in this course you will become a master of quantitative finance and financial engineering.
This course covers a variety of topics like:
- Stock Markets
- Commodity Market
- Forex Trading
- Technical Analysis
- Financial Derivatives
- Time Value of Money
- Modern Portfolio Theory
- Efficient Market Hypothesis
- Stock Price Prediction using Machine Learning
- Stock Price Prediction using LSTM Neural Networks (Deep Learning)
- Gold Price Prediction using Machine Learning
- Develop and Backtest Trading Strategies in Python
- Technical Indicators like Moving Averages and RSI.
- Algorithmic Trading.
- Advanced Trading Methodologies like Arbitrage and Pair Trading.
- Random Walk Theory.
- Capital Asset Pricing Model.
- Sharpe Ratio.
- Python for Finance.
- Correlation between different stocks and asset classes.
- Candle Stick Charts.
- Working with Financial and OHLC Data for stocks.
- Optimal Position Sizing using Kelly Criterion.
- Diversification and Risk Management.