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| Name | Cointegration | Mean Reversion Strategies | Quantra course | Dr. Ernest P. Chan |
| Video Uploader | Video From Quantra |
| Upload Date | This Video Uploaded At 22-12-2021 04:31:31 |
| Video Discription | Start for Free: https://quantra.quantinsti.com/course/python-mean-reversion-strategies-ernest-chan Welcome to this video lecture. In this, you will learn about cointegration. As stated in the previous section, most financial price series are not stationary. But, fortunately, we are not confined to trading those “prefabricated” financial price series. We can create a portfolio of two price series so that the market value of this portfolio is stationary. If so, then, the individual price series are called to be cointegrated with each other. An example of a portfolio of possibly cointegrated stocks is the spread between gold ETF (GLD) and 1.63 * gold miners ETF (GDX). The new series “GLD - 1.63 * GDX” is stationary and gives us an opportunity to create a mean reverting strategy. We go long the spread, that is, buy 1 share of GLD and sell 1.63 shares of GDX. On the other hand, we go short the spread, that is, sell 1 share of GLD and buy 1.63 shares of GDX. This is commonly known as a “pairs trading” strategy. However, the same concept of cointegration and stationarity of spread can be extended to three or more assets as well. Just because a set of two price series is cointegrating does not mean that any random linear combination of them will form a stationary portfolio. Most of them have a specific combination which forms a stationary portfolio and this combination is called the hedge ratio. In next unit, we will explore more about hedge ratio and how to calculate it. Before we move on to next unit, let us understand the difference between correlation and cointegration. Correlation between two or more price series refers to the correlations of their returns over some time horizon such as daily, hourly, weekly or monthly. For example, in the graphs here stocks A and B are correlated but not cointegrated. If stock A goes down then stock B also goes down and if stock A goes up then stock B also goes up. However, the spread between stocks A and B is not stationary. Cointegration is concerned with whether two price series diverge over long term. For example, in the case of stock A vs stock C: The spread between stock A and stock C goes from zero to negative and back to zero. Then, the spread goes to positive and back to zero. Since the spread is repeatedly coming back to zero we understand that the stocks A and C are cointegrated. However, stock A and C move in both opposite and same directions at different times. Thus, stocks A and C are far from correlated. Quantra is an online education portal that specializes in Algorithmic and Quantitative trading. Quantra offers various bite-sized, self-paced and interactive courses that are perfect for busy professionals, seeking implementable knowledge in this domain. Find more info on - https://quantra.quantinsti.com/ Like us on Facebook: https://www.facebook.com/goquantra/ Follow us on Twitter: https://twitter.com/GoQuantra |
| Category | Education |
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