Holczer Balazs – Quantitative Finance & Algorithmic Trading Masterclass

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Original price was: $29.00.Current price is: $14.00.

This Quantitative Finance & Algorithmic Trading Masterclass is about stock market fundamentals: how to use higher mathematics and quantitative approaches in order to eliminate the risk. First of all you have to consider the basics models: Markowitz-model is useful to eliminate risk by including more stock in a portfolio.

Purchase this course you will earn 14 Points worth of $1.40!
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Buy Holczer Balazs – Quantitative Finance & Algorithmic Trading Masterclass Course at GBesy. We actively participate in Groupbuys and are committed to sharing knowledge with a wider audience. Rest assured, the quality of our courses matches that of the original sale page. If you prefer, you can also buy directly from the sale page at the full price (the SALEPAGE link is directly provided in the post).

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Holczer Balazs – Quantitative Finance & Algorithmic Trading Masterclass

Holczer Balazs - Quantitative Finance & Algorithmic Trading Masterclass

Archive: https://archive.is/NMzsb

This Quantitative Finance & Algorithmic Trading Masterclass is about stock market fundamentals: how to use higher mathematics and quantitative approaches in order to eliminate the risk. First of all you have to consider the basics models: Markowitz-model is useful to eliminate risk by including more stock in a portfolio. CAPM model can measure the so-called market risk. Black-Scholes model can eliminate all the risk by combining options with underlying stocks. So these are the fundamental theories behind quantitative finance.
The next step is to use time series analysis. There are lots of bad models but combining ARIMA model with GARCH model is working quite fine. You will implement a concrete trading strategy from scratch in R and test it on historical data. Sure you will like it!
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Unlock your full potential with Holczer Balazs – Quantitative Finance & Algorithmic Trading Masterclass courses. our courses are designed to help you excel.

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