Quantitative Finance Courses
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- Quantitative Finance Courses
1. CFA® Level 1 (2022) - Complete Quantitative Methods
Deep dive into Quant with the Bestselling CFA® prep course provider | With visual learning + Quizzes
Content:
- Make present value and future value calculations
- Use TVM functions on your calculator
- Use net present value (NPV) and internal rate of return (IRR) for evaluating cash flow streams
2. Algorithmic Trading & Quantitative Analysis Using Python
Build fully automated trading system and Implement quantitative trading strategies using Python
Content:
- Algorithmic trading and quantitative analysis using python
- Carrying out both technical analysis and fundamental analysis programatically
- API trading
3. Financial Derivatives: A Quantitative Finance View
The financial engineering of forwards, futures, swaps, and options, with Python tools for fixed income and options
Content:
- Learn the fundamentals of derivatives at a quantitative level
- Master arbitrage
- the core principle underlying derivatives
- quantitative risk management and quantitative trading
- Use derivatives to control and manage financial risk
4. Quantitative Finance & Algorithmic Trading in Python
Stock Market, Bonds, Markowitz-Portfolio Theory, CAPM, Black-Scholes Model, Value at Risk and Monte-Carlo Simulations
Content:
- Understand stock market fundamentals
- Understand bonds and bond pricing
- Understand the Modern Portfolio Theory and Markowitz model
5. Algorithmic Trading & Time Series Analysis in Python and R
Technical Analysis (SMA and RSI), Time Series Analysis (ARIMA and GRACH), Machine Learning and Mean-Reversion Strategies
Content:
- Understand technical indicators (MA
- EMA or RSI)
- Understand random walk models
- Understand autoregressive models
6. Quantitative Trading Analysis with R
Learn quantitative trading analysis from basic to expert level through a practical course with R statistical software.
Content:
- Read or download S&P 500® Index ETF prices data and perform quantitative trading analysis operations by installing related packages and running script code on RStudio IDE.
- Implement trading strategies based on their category and frequency by defining indicators
- identifying signals they generate and outlining rules that accompany them.
- Explore strategy categories through trend-following indicators such as simple moving averages
- moving averages convergence-divergence and mean-reversion indicators such as Bollinger bands®
- relative strength index
- statistical arbitrage through z-score.
7. Quantitative Finance with R
Learn portfolio optimization, asset pricing, and risk management with R
Content:
- A solid understanding of how to analyze—with a quantitative mindset—the most important financial products such as equities
- derivatives
- and bonds
- Use statistical analysis to find hidden insights into financial data used in financial models and strategies
- Diversify your portfolio with hedging and eliminate unwanted risk during times of market volatility
8. All Weather Investing Via Quantitative Modeling In Excel
Master The Principles of A Resilient Investing Strategy using Stocks & Bonds ETF called Risk Parity Used In Hedge Funds
Content:
- Learn about quantitative Investing & how it is different from conventional methods of investing
- Master the science and art of diversification to build an all-weather portfolio that remains robust under harsh market conditions
- Know the pitfalls of buying and holding a pure stock portfolio
9. Fixed Income Analytics: Pricing and Risk Management
With Python Tools for Bonds and Money Market Instruments
Content:
- The general structure of global bond and money markets
- Pricing
- yield
- accrued interest and day count conventions
- Arbitrage and the time value of money as the core principles underlying security valuation
- and how to use them to price fixed income securities
10. Quantitative Trading Analysis with Python
Learn quantitative trading analysis from basic to expert level through practical course with Python programming language
Content:
- Read or download S&P 500® Index ETF prices data and perform quantitative trading analysis operations by installing related packages and running code on Python PyCharm IDE.
- Implement trading strategies based on their category and frequency by defining indicators
- identifying signals they generate and outlining rules that accompany them.
- Explore strategy categories through trend-following indicators such as simple moving averages
- moving averages convergence-divergence and mean-reversion indicators such as Bollinger bands®
- relative strength index
- statistical arbitrage through z-score.
11. Financial Math Primer for Absolute Beginners - Core Finance
Get the Mathematical Foundation in Finance You've Always Needed. Then Write a Financial Mathematics Proof from Scratch.
Content:
- Finally understand why equations (in and outside of Financial Math) work the way they do.
- Gain a solid command over how to rearrange / manipulate equations algebraically.
- Build the foundation that will empower you to later handle more complex problems in Finance.
12. Backtesting Strategies: Test Trading Strategies Using Python
Find out if your trading strategy will work in real life by testing how it would have worked in the past
Content:
- Calculate risk and return of investment portfolios
- Create graphs and charts using Pandas and Matplotlib
- Apply best practices when working with financial data
13. Financial Modeling - Derivatives Concepts and Applications
Financial Engineering
Content:
- Students will understand how what derivatives are
- how to price them
- and the overall structure and essence of them.
14. Applied Machine Learning with Python (Trading) - 2020
Learn how to use machine learning such as random forest and SVMs to develop quantitative trading strategies in Python
Content:
- Understand how to develop a quantitative trading strategy
- Understand the difference between trading actors in the market and learn about manual and systematic trading strategies
- Learn how to analyse PnL and performance metrics of trading strategies
15. Career in Quantitative Trading and Risk Management
How to start a career in Quantitative Trading and Risk Management
Content:
- Career in Quantitative Trading
- Career in Risk Management
- Industry knowledge
16. Statistics and probability for Quantitative finance
Learning by doing! Apply statistics on Trading and quantitative finance. (Forex, crypto, stocks )
Content:
- Find optimal stop loss & take profit using probability distribution
- Understand Student test and apply it to portfolio management problem
- Use probability distribution to compute the Value at Risk (VaR)
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