It’s been a while since I shared my ideas on market analysis with you and I see that the interest in the subject only increases. In my opinion, it objectively reflects the fact that the information that we receive in these reports is of interest. Especially for those who are trying to understand the true causes behind the price movements in a particular market.
So today I want to move from theory to practice and on the basis of data obtained in the COT report on 18th November 2016 to make a detailed analysis of one of the markets. My goal is to show you how I do in in order for you to be able to use it in your trading tomorrow.
In this report I'm mainly interested in the changes in the two columns marked in green. The first one is the total number of open positions (Open Interest). The second shows the change in the structure of open positions of commercial participants (Commercial) or as I often call them, operators.
Here we can see that during the reporting week of 8th - 15th of November, the total number of open positions changed insignificantly. The amount increased just to 901 contracts. In addition we see that during this time the operators increased their long positions (1882 contract), cut their shorts (-1736 contract) and had a net long position of 36521 contract (39568 - 3047 = 36521). It is also worth noting that the share of long positions of commercial participants to the total volume of open positions is 72,6% (39568 / 54533 * 100 = 72,6) . Now let's open the chart and see how the price changed during this period.
What do we see on the chart?
Here I have outlined 5 trading sessions during which there have been changes in the report and noted the day when this data was published - when we received these data at our disposal.
The price was falling during all five reporting days and finally on November 15, updated the lows of June 2016. For three days after that, while the report was not yet published, the price continued its decline i.e. significant changes during this three-day period did not occur, except that the price didn't drop even lower. On this basis, I conclude that the data presented in the report remains valid.
What relative indicators I use
It's time to compare the data obtained in the report with historical values to assess the strength of their influence on the market. I'm using Timing Charts for it. Here we have the opportunity to compare not only absolute values that are presented in the COT report, but the relative values as well. I am personally convinced that it is much easier to work with relative figures than with absolute.
COT Index
The first relative measure I use is the COT Index. You can see this indicator at the bottom of the picture, just below the changes of net open positions of operators. Despite the fact that visually the two curves are identical, in trade when you need to determine the reference levels, it is easier to operate with relative values, because these values will always be in the same range. This index compares a current net open position with the high and low for the last 26 weeks (six months). You can change the number of weeks involved in the index calculation at your discretion, but I use 26 weeks.
C.O.T. Index = (Current Net Position - Minimum Net Position[Weeks]) / (Maximum Net Position[Weeks] - Minimum Net Position[Weeks])
Let's imagine that this indicator shows 100%. This would mean that currently we have the maximum net long position of operators for the last 26 weeks. Otherwise, if this index shows 0%, this will tell us that operators now have the maximum net shorts over the same period.
Open Interest Percent
Another relative indicator that I use you can find in the report (see picture 1). This percentage of open long or short positions of commercial participants in the total open interest. If the COT index is above 80%, as in our example, I use the following formula:
Open Interest Percent = Commercial Long / Open Interest
If the COT index is below 20%:
Open Interest Percent = Commercial Short / Open Interest
In our case, the COT index is 93,88%, respectively, in the picture below, in addition to the changes of the absolute value of Open Interest I have reflected changes in long position of operators regarding the same value (Comm Long / Open Interest).
We got a coefficient of 0.73 after rounding or 73%. This means that in the total open long positions 54533 contract, 73% or 39568 contracts constitute a long position of operators and only the remaining 27% distributed among other groups. At the same time, if we look at the total volume of short positions the same 54533 of the contract, the operators keep only 3047 contracts or 5.6% of the total. I hope you have not lost the thread of my logical thinking and understand what I mean.
Conclusion
Currently, the operators hold almost the maximum net long position of 93,88% over the last 26 weeks. In addition to this, the share of long positions of operators to the total volume of open interest is 73% and continues to grow. Increasing this share it increases the probability that the price will reverse.
If we look at the history of changes of this indicator, we can see that the price changed its direction when the value was smaller.
For this market, I believe the conditions will be met if the COT Index is above 80% or below 20%, while Open Interest Percent is greater than 60% or 50%, respectively. For other markets, generally, the control values of the first indicator remain the same 80% and 20%, while the second one may vary from market to market. It is easy to identify them, just by looking at the history and determining for which values of Open Interest Percent there was a change of trend.
This does not mean that after the value reach these targets, I will immediately open a trade. As I said before, the conditions discussed here are only one out of three points to be checked when opening a trade. Therefore, only after meeting these criteria do I start to use the technical analysis tools solely in order to enter the market.
It’s been a while since I shared my ideas on market analysis with you and I see that the interest in the subject only increases. In my opinion, it objectively reflects the fact that the information that we receive in these reports is of interest. Especially for those who are trying to understand the true causes behind the price movements in a particular market.
So today I want to move from theory to practice and on the basis of data obtained in the COT report on 18th November 2016 to make a detailed analysis of one of the markets. My goal is to show you how I do in in order for you to be able to use it in your trading tomorrow.
In this report I'm mainly interested in the changes in the two columns marked in green. The first one is the total number of open positions (Open Interest). The second shows the change in the structure of open positions of commercial participants (Commercial) or as I often call them, operators.
Here we can see that during the reporting week of 8th - 15th of November, the total number of open positions changed insignificantly. The amount increased just to 901 contracts. In addition we see that during this time the operators increased their long positions (1882 contract), cut their shorts (-1736 contract) and had a net long position of 36521 contract (39568 - 3047 = 36521). It is also worth noting that the share of long positions of commercial participants to the total volume of open positions is 72,6% (39568 / 54533 * 100 = 72,6) . Now let's open the chart and see how the price changed during this period.
What do we see on the chart?
Here I have outlined 5 trading sessions during which there have been changes in the report and noted the day when this data was published - when we received these data at our disposal.
The price was falling during all five reporting days and finally on November 15, updated the lows of June 2016. For three days after that, while the report was not yet published, the price continued its decline i.e. significant changes during this three-day period did not occur, except that the price didn't drop even lower. On this basis, I conclude that the data presented in the report remains valid.
What relative indicators I use
It's time to compare the data obtained in the report with historical values to assess the strength of their influence on the market. I'm using Timing Charts for it. Here we have the opportunity to compare not only absolute values that are presented in the COT report, but the relative values as well. I am personally convinced that it is much easier to work with relative figures than with absolute.
COT Index
The first relative measure I use is the COT Index. You can see this indicator at the bottom of the picture, just below the changes of net open positions of operators. Despite the fact that visually the two curves are identical, in trade when you need to determine the reference levels, it is easier to operate with relative values, because these values will always be in the same range. This index compares a current net open position with the high and low for the last 26 weeks (six months). You can change the number of weeks involved in the index calculation at your discretion, but I use 26 weeks.
C.O.T. Index = (Current Net Position - Minimum Net Position[Weeks]) / (Maximum Net Position[Weeks] - Minimum Net Position[Weeks])
Let's imagine that this indicator shows 100%. This would mean that currently we have the maximum net long position of operators for the last 26 weeks. Otherwise, if this index shows 0%, this will tell us that operators now have the maximum net shorts over the same period.
Open Interest Percent
Another relative indicator that I use you can find in the report (see picture 1). This percentage of open long or short positions of commercial participants in the total open interest. If the COT index is above 80%, as in our example, I use the following formula:
Open Interest Percent = Commercial Long / Open Interest
If the COT index is below 20%:
Open Interest Percent = Commercial Short / Open Interest
In our case, the COT index is 93,88%, respectively, in the picture below, in addition to the changes of the absolute value of Open Interest I have reflected changes in long position of operators regarding the same value (Comm Long / Open Interest).
We got a coefficient of 0.73 after rounding or 73%. This means that in the total open long positions 54533 contract, 73% or 39568 contracts constitute a long position of operators and only the remaining 27% distributed among other groups. At the same time, if we look at the total volume of short positions the same 54533 of the contract, the operators keep only 3047 contracts or 5.6% of the total. I hope you have not lost the thread of my logical thinking and understand what I mean.
Conclusion
Currently, the operators hold almost the maximum net long position of 93,88% over the last 26 weeks. In addition to this, the share of long positions of operators to the total volume of open interest is 73% and continues to grow. Increasing this share it increases the probability that the price will reverse.
If we look at the history of changes of this indicator, we can see that the price changed its direction when the value was smaller.
For this market, I believe the conditions will be met if the COT Index is above 80% or below 20%, while Open Interest Percent is greater than 60% or 50%, respectively. For other markets, generally, the control values of the first indicator remain the same 80% and 20%, while the second one may vary from market to market. It is easy to identify them, just by looking at the history and determining for which values of Open Interest Percent there was a change of trend.
This does not mean that after the value reach these targets, I will immediately open a trade. As I said before, the conditions discussed here are only one out of three points to be checked when opening a trade. Therefore, only after meeting these criteria do I start to use the technical analysis tools solely in order to enter the market.
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FMLS:24 | Shaping the Next Era of Financial Evolution
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FM's Andrea Badiola Mateos at LSEG's Cyprus event
FM's Andrea Badiola Mateos at LSEG's Cyprus event
FM's Andrea Badiola Mateos at LSEG's Cyprus event
FM's Andrea Badiola Mateos at LSEG's Cyprus event
FM's Andrea Badiola Mateos at LSEG's Cyprus event
FM's Andrea Badiola Mateos at LSEG's Cyprus event
FM's Andrea Badiola Mateos at speaking in a panel discussion at LSEG's Cyprus event
FM's Andrea Badiola Mateos at speaking in a panel discussion at LSEG's Cyprus event
FM's Andrea Badiola Mateos at speaking in a panel discussion at LSEG's Cyprus event
FM's Andrea Badiola Mateos at speaking in a panel discussion at LSEG's Cyprus event
FM's Andrea Badiola Mateos at speaking in a panel discussion at LSEG's Cyprus event
FM's Andrea Badiola Mateos at speaking in a panel discussion at LSEG's Cyprus event
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The Role of PAMM, MAM & Copy Trading in Business Growth Strategies | Webinar
The Role of PAMM, MAM & Copy Trading in Business Growth Strategies | Webinar
The Role of PAMM, MAM & Copy Trading in Business Growth Strategies | Webinar
The copy trading market is projected to double in size, growing from $2.2 billion to $4 billion by the end of this decade. In light of this, brokers and financial institutions are increasingly adopting PAMM, MAM, and Copy Trading solutions to scale operations and drive profitability. In this insightful webinar, Sergey Ryzhavin, Product Owner at B2COPY, outlines the advanced features of the B2COPY platform, showcasing how it enhances Copy Trading, PAMM, and MAM performance. Sergey also explores strategies for using these tools to attract new clients, improve customer engagement, and create additional revenue streams.
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The copy trading market is projected to double in size, growing from $2.2 billion to $4 billion by the end of this decade. In light of this, brokers and financial institutions are increasingly adopting PAMM, MAM, and Copy Trading solutions to scale operations and drive profitability. In this insightful webinar, Sergey Ryzhavin, Product Owner at B2COPY, outlines the advanced features of the B2COPY platform, showcasing how it enhances Copy Trading, PAMM, and MAM performance. Sergey also explores strategies for using these tools to attract new clients, improve customer engagement, and create additional revenue streams.
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The copy trading market is projected to double in size, growing from $2.2 billion to $4 billion by the end of this decade. In light of this, brokers and financial institutions are increasingly adopting PAMM, MAM, and Copy Trading solutions to scale operations and drive profitability. In this insightful webinar, Sergey Ryzhavin, Product Owner at B2COPY, outlines the advanced features of the B2COPY platform, showcasing how it enhances Copy Trading, PAMM, and MAM performance. Sergey also explores strategies for using these tools to attract new clients, improve customer engagement, and create additional revenue streams.
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The copy trading market is projected to double in size, growing from $2.2 billion to $4 billion by the end of this decade. In light of this, brokers and financial institutions are increasingly adopting PAMM, MAM, and Copy Trading solutions to scale operations and drive profitability. In this insightful webinar, Sergey Ryzhavin, Product Owner at B2COPY, outlines the advanced features of the B2COPY platform, showcasing how it enhances Copy Trading, PAMM, and MAM performance. Sergey also explores strategies for using these tools to attract new clients, improve customer engagement, and create additional revenue streams.
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The copy trading market is projected to double in size, growing from $2.2 billion to $4 billion by the end of this decade. In light of this, brokers and financial institutions are increasingly adopting PAMM, MAM, and Copy Trading solutions to scale operations and drive profitability. In this insightful webinar, Sergey Ryzhavin, Product Owner at B2COPY, outlines the advanced features of the B2COPY platform, showcasing how it enhances Copy Trading, PAMM, and MAM performance. Sergey also explores strategies for using these tools to attract new clients, improve customer engagement, and create additional revenue streams.
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The copy trading market is projected to double in size, growing from $2.2 billion to $4 billion by the end of this decade. In light of this, brokers and financial institutions are increasingly adopting PAMM, MAM, and Copy Trading solutions to scale operations and drive profitability. In this insightful webinar, Sergey Ryzhavin, Product Owner at B2COPY, outlines the advanced features of the B2COPY platform, showcasing how it enhances Copy Trading, PAMM, and MAM performance. Sergey also explores strategies for using these tools to attract new clients, improve customer engagement, and create additional revenue streams.
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Join us at FMLS:24 to connect with global institutional brokers. Secure your spot today! #fmls24
Join us at FMLS:24 to connect with global institutional brokers. Secure your spot today! #fmls24
Join us at FMLS:24 to connect with global institutional brokers. Secure your spot today! #fmls24
Join us at FMLS:24 to connect with global institutional brokers. Secure your spot today! #fmls24
Join us at FMLS:24 to connect with global institutional brokers. Secure your spot today! #fmls24
Join us at FMLS:24 to connect with global institutional brokers. Secure your spot today! #fmls24