Statistics and probability for Quantitative finance

Learning by doing! Apply statistics on Trading and quantitative finance. (Forex, crypto, stocks )

What you'll learn:

• 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)
• Compute correlation between assets properly
• Understand the main financial statistics: mean, variance, standard-deviation, skewness, kurtosis, covariance, correlation, ...
• Compute conditional probability to create a strategy with 70% beneficial trades
• Master combinatorial statistics
• Learn the basis of probability: random variables, intersection, union, independency, conditional probability ...
• Learn bayes theorem
• Learn the most used law of probability in finance: Bernoulli, Binomial, Poisson, Uniform, Exponential, Normal,...
• Learn how statistical test works

You already have knowledge in finance and you want to go deeper to monetize and diversify your knowledge?

You already have some trading knowledge and you want to learn about quantitative trading/finance?

You are simply a curious person who wants to get into this subject?

If you answer at least one of these questions, I welcome you to this course. All the applications of the course will be done using Python. However, for beginners in Python, don't panic! There is a FREE python crash course included to master Python.

In this course, you will learn how to use statistics and probability to make your strategies stronger. You will learn the statistical methods used by the quantitative analyst to find the optimal stop loss and take profit and to perform a risk analysis (VaR). You will use the power of conditional probability to increase the beneficial trade to 70%.

Through this example, you will learn and understand a lot of statistic and probability concepts used by portfolio managers and professional traders:

• Descriptive statistics: mean, variance, standard deviation, covariance, correlation, skewness, kurtosis, ...

• Probability: random variable, union, intersection, independence, conditional probability,...

• Hypothesis Test: understand the process, student test, ad-fuller test,...

Why this course and not another?

• This is not a programming course nor a trading course or a statistic course. It is a course in which programming and statistic are used for trading.

• This course is not created by a data scientist but by a degree in mathematics and economics specializing in mathematics applied to finance.

• You can ask questions or read our quantitative finance articles simply by registering on our free Discord forum.

Without forgetting that the course is satisfied or refunded for 30 days. Don't miss an opportunity to improve your knowledge of this fascinating subject.