Correlation analysis and how it can improve your trading
What is correlation analysis?
Correlation analysis is a statistical method used to investigate the relationship between two or more assets. It is commonly employed to understand how changes in one asset are associated with changes in another asset. The goal is to determine whether a relationship exists and, if so, the direction and strength of that relationship.
Types of correlation analysis
Positive Correlation: When two or more assets move in the same direction, they are said to have a positive correlation. For example, if Asset A(GBP) and Asset B(EUR) have a positive correlation of, it means that when the price of Asset A increases, the price of Asset B also tends to increase, and vice versa.
Negative Correlation: When two or more assets move in opposite directions, they are said to have a negative correlation. For example, if Asset C(USD) and Asset D(GBP) have a negative correlation of -0.6, it means that when the price of Asset C increases, the price of Asset D tends to decrease, and vice versa.
What can I do with this information?
When looking at correlation analysis you need to make sure you are making use of higher timeframe such as 1W, 1D, H4 and 1H anything below this specific timeframe may be subjected to errors, on these timeframes we would be looking for specific things which include:
You would be comparing swing highs on these two asset classes this implied that if GBP makes a higher high, we expect DXY to make a lower low at a key institutional point i.e. (order block, FVG, liquidity pools or equilibrium)
A failure to make a lower low is what is we would refer to as a crack in correlation or a divergence
What is a divergence?
Divergence refers to a situation where the correlation between two or more assets or variables changes over time. In other words, the strength or direction of the relationship between the variables is not consistent and exhibits variations over different periods.
Divergence in correlation can occur due to various factors, including changes in market conditions, economic trends, and external events. It is crucial for traders and investors to be aware of such changes and regularly monitor correlations between assets in their portfolios. Relying solely on historical correlations without considering the potential for divergence can lead to unexpected and undesirable outcomes.
To adapt to changing correlations, traders and investors may need to adjust their portfolio allocation and risk management strategies. Proper diversification, risk analysis, and ongoing research are essential components of managing a portfolio in light of correlation divergence.
Conclusion once a divergence is found on any of the institutional reference point mentioned above this acts as a confluence to your analysis confirming institutional sponsorship
Hope u found this insightful see you next week
Correlation analysis is widely used in various fields, such as economics, finance, social sciences, and medical research, to gain insights into the connections between different variables. However, it is essential to remember that correlation does not imply causation, and further research is often required to establish causative relationships between variables.
Correlation analysis is a statistical method used to investigate the relationship between two or more assets. It is commonly employed to understand how changes in one asset are associated with changes in another asset. The goal is to determine whether a relationship exists and, if so, the direction and strength of that relationship.
Types of correlation analysis
Positive Correlation: When two or more assets move in the same direction, they are said to have a positive correlation. For example, if Asset A(GBP) and Asset B(EUR) have a positive correlation of, it means that when the price of Asset A increases, the price of Asset B also tends to increase, and vice versa.
Negative Correlation: When two or more assets move in opposite directions, they are said to have a negative correlation. For example, if Asset C(USD) and Asset D(GBP) have a negative correlation of -0.6, it means that when the price of Asset C increases, the price of Asset D tends to decrease, and vice versa.
What can I do with this information?
When looking at correlation analysis you need to make sure you are making use of higher timeframe such as 1W, 1D, H4 and 1H anything below this specific timeframe may be subjected to errors, on these timeframes we would be looking for specific things which include:
- Order block
- Fair value gaps
- Liquidity pools and equilibrium
You would be comparing swing highs on these two asset classes this implied that if GBP makes a higher high, we expect DXY to make a lower low at a key institutional point i.e. (order block, FVG, liquidity pools or equilibrium)
A failure to make a lower low is what is we would refer to as a crack in correlation or a divergence
What is a divergence?
Divergence refers to a situation where the correlation between two or more assets or variables changes over time. In other words, the strength or direction of the relationship between the variables is not consistent and exhibits variations over different periods.
Divergence in correlation can occur due to various factors, including changes in market conditions, economic trends, and external events. It is crucial for traders and investors to be aware of such changes and regularly monitor correlations between assets in their portfolios. Relying solely on historical correlations without considering the potential for divergence can lead to unexpected and undesirable outcomes.
To adapt to changing correlations, traders and investors may need to adjust their portfolio allocation and risk management strategies. Proper diversification, risk analysis, and ongoing research are essential components of managing a portfolio in light of correlation divergence.
Conclusion once a divergence is found on any of the institutional reference point mentioned above this acts as a confluence to your analysis confirming institutional sponsorship
Hope u found this insightful see you next week
Correlation analysis is widely used in various fields, such as economics, finance, social sciences, and medical research, to gain insights into the connections between different variables. However, it is essential to remember that correlation does not imply causation, and further research is often required to establish causative relationships between variables.
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