What is Cointegration? | Statistical Arbitrage Trading Strategy | Quantra Course
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In this video, we will discuss cointegration.
To understand cointegration, it is essential to first understand the concept of stationarity. A stationary time series is the one whose statistical parameters such as mean and variance do not change over time.
Consider two price series, A and B. If the linear combination or spread of A and B stationary then the two price series A and B are said to be cointegrated with each other.
To intuitively understand the concept of cointegration, consider this example of a drunk man walking with his unleashed pet dog. The drunkard and his dog are good examples of random walks as both seem to be roaming around in a seemingly aimless manner. The paths of the drunk man and the dog can be referred to as “non-stationary” or “random walks”. However, assume that the dog and the drunk man stay connected to each other using their hearing and smelling senses, then the distance between them is bounded and doesn’t increase indefinitely. Loosely speaking, we can say that the distance between the two paths is stationary and hence, the paths of the drunk and his dog can be considered as co-integrated.
In the context of trading, if the spread between two assets is stationary that is, if the spread stays around the mean, then the prices are said to be co-integrated.
On the other hand, “Correlated” commodities are those whose prices move in the same direction but whose spread may not be stationary.
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/
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Видео What is Cointegration? | Statistical Arbitrage Trading Strategy | Quantra Course канала Quantra
In this video, we will discuss cointegration.
To understand cointegration, it is essential to first understand the concept of stationarity. A stationary time series is the one whose statistical parameters such as mean and variance do not change over time.
Consider two price series, A and B. If the linear combination or spread of A and B stationary then the two price series A and B are said to be cointegrated with each other.
To intuitively understand the concept of cointegration, consider this example of a drunk man walking with his unleashed pet dog. The drunkard and his dog are good examples of random walks as both seem to be roaming around in a seemingly aimless manner. The paths of the drunk man and the dog can be referred to as “non-stationary” or “random walks”. However, assume that the dog and the drunk man stay connected to each other using their hearing and smelling senses, then the distance between them is bounded and doesn’t increase indefinitely. Loosely speaking, we can say that the distance between the two paths is stationary and hence, the paths of the drunk and his dog can be considered as co-integrated.
In the context of trading, if the spread between two assets is stationary that is, if the spread stays around the mean, then the prices are said to be co-integrated.
On the other hand, “Correlated” commodities are those whose prices move in the same direction but whose spread may not be stationary.
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
Видео What is Cointegration? | Statistical Arbitrage Trading Strategy | Quantra Course канала Quantra
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17 мая 2022 г. 19:15:01
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