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.
Sky Links Capital Adds LBMA Gold Fixing, Options and Weekend Trading
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FM Daily Brief – 9 June 2026
FM Daily Brief – 9 June 2026
FM Daily Brief – 9 June 2026
FM Daily Brief – 9 June 2026
Today’s Tuesday, the 9th of June 2026, and these are our main stories: eToro’s customer assets climbed back above $20 billion, Prop trading model in prediction markets, and Leverate launched a new AI assistant for brokers and traders.
Today’s Tuesday, the 9th of June 2026, and these are our main stories: eToro’s customer assets climbed back above $20 billion, Prop trading model in prediction markets, and Leverate launched a new AI assistant for brokers and traders.
Today’s Tuesday, the 9th of June 2026, and these are our main stories: eToro’s customer assets climbed back above $20 billion, Prop trading model in prediction markets, and Leverate launched a new AI assistant for brokers and traders.
Today’s Tuesday, the 9th of June 2026, and these are our main stories: eToro’s customer assets climbed back above $20 billion, Prop trading model in prediction markets, and Leverate launched a new AI assistant for brokers and traders.
War Stories: Lessons from 20 Years in Markets (the pain, the pitfalls and the profits)
War Stories: Lessons from 20 Years in Markets (the pain, the pitfalls and the profits)
War Stories: Lessons from 20 Years in Markets (the pain, the pitfalls and the profits)
War Stories: Lessons from 20 Years in Markets (the pain, the pitfalls and the profits)
War Stories: Lessons from 20 Years in Markets (the pain, the pitfalls and the profits)
War Stories: Lessons from 20 Years in Markets (the pain, the pitfalls and the profits)
The trades that taught me the most aren't the ones that worked. They're the ones that didn't — or the ones I almost caught and didn't have the nerve to ride. In this session, I'll tell you about the Brexit miss, the SNB shocker that nearly handed me a 5400% return, the BoJ surprise that punched me in the gut, and a few wins along the way. Each story carries a lesson, but the lessons aren't the point. Everyone who trades long enough collects a portfolio of moments like these; what separates the people who stay in the game is what they do with them.
The trades that taught me the most aren't the ones that worked. They're the ones that didn't — or the ones I almost caught and didn't have the nerve to ride. In this session, I'll tell you about the Brexit miss, the SNB shocker that nearly handed me a 5400% return, the BoJ surprise that punched me in the gut, and a few wins along the way. Each story carries a lesson, but the lessons aren't the point. Everyone who trades long enough collects a portfolio of moments like these; what separates the people who stay in the game is what they do with them.
The trades that taught me the most aren't the ones that worked. They're the ones that didn't — or the ones I almost caught and didn't have the nerve to ride. In this session, I'll tell you about the Brexit miss, the SNB shocker that nearly handed me a 5400% return, the BoJ surprise that punched me in the gut, and a few wins along the way. Each story carries a lesson, but the lessons aren't the point. Everyone who trades long enough collects a portfolio of moments like these; what separates the people who stay in the game is what they do with them.
The trades that taught me the most aren't the ones that worked. They're the ones that didn't — or the ones I almost caught and didn't have the nerve to ride. In this session, I'll tell you about the Brexit miss, the SNB shocker that nearly handed me a 5400% return, the BoJ surprise that punched me in the gut, and a few wins along the way. Each story carries a lesson, but the lessons aren't the point. Everyone who trades long enough collects a portfolio of moments like these; what separates the people who stay in the game is what they do with them.
The trades that taught me the most aren't the ones that worked. They're the ones that didn't — or the ones I almost caught and didn't have the nerve to ride. In this session, I'll tell you about the Brexit miss, the SNB shocker that nearly handed me a 5400% return, the BoJ surprise that punched me in the gut, and a few wins along the way. Each story carries a lesson, but the lessons aren't the point. Everyone who trades long enough collects a portfolio of moments like these; what separates the people who stay in the game is what they do with them.
The trades that taught me the most aren't the ones that worked. They're the ones that didn't — or the ones I almost caught and didn't have the nerve to ride. In this session, I'll tell you about the Brexit miss, the SNB shocker that nearly handed me a 5400% return, the BoJ surprise that punched me in the gut, and a few wins along the way. Each story carries a lesson, but the lessons aren't the point. Everyone who trades long enough collects a portfolio of moments like these; what separates the people who stay in the game is what they do with them.
The Engine and the Fuel: How AI & Data Drives African Future
The Engine and the Fuel: How AI & Data Drives African Future
The Engine and the Fuel: How AI & Data Drives African Future
The Engine and the Fuel: How AI & Data Drives African Future
The Engine and the Fuel: How AI & Data Drives African Future
The Engine and the Fuel: How AI & Data Drives African Future
If AI is the engine, data is the fuel. Without quality, accessible data, AI cannot work well; and without the right mindset, data remains just numbers instead of insight. In this session, leading experts will explore how AI and data are democratizing opportunities for businesses and personal growth. Discover practical ways to make AI accessible today, anticipate its transformative impact on African markets, and learn actionable steps to prepare for what's next. Let's talk about:
-How AI and data drive business efficiency and innovation in trading and fintech
-AI tools to elevate trading or business strategies
-How to access and maximise the power of data and AI
-Emerging AI and data trends in Africa and their economic ripple effects
If AI is the engine, data is the fuel. Without quality, accessible data, AI cannot work well; and without the right mindset, data remains just numbers instead of insight. In this session, leading experts will explore how AI and data are democratizing opportunities for businesses and personal growth. Discover practical ways to make AI accessible today, anticipate its transformative impact on African markets, and learn actionable steps to prepare for what's next. Let's talk about:
-How AI and data drive business efficiency and innovation in trading and fintech
-AI tools to elevate trading or business strategies
-How to access and maximise the power of data and AI
-Emerging AI and data trends in Africa and their economic ripple effects
If AI is the engine, data is the fuel. Without quality, accessible data, AI cannot work well; and without the right mindset, data remains just numbers instead of insight. In this session, leading experts will explore how AI and data are democratizing opportunities for businesses and personal growth. Discover practical ways to make AI accessible today, anticipate its transformative impact on African markets, and learn actionable steps to prepare for what's next. Let's talk about:
-How AI and data drive business efficiency and innovation in trading and fintech
-AI tools to elevate trading or business strategies
-How to access and maximise the power of data and AI
-Emerging AI and data trends in Africa and their economic ripple effects
If AI is the engine, data is the fuel. Without quality, accessible data, AI cannot work well; and without the right mindset, data remains just numbers instead of insight. In this session, leading experts will explore how AI and data are democratizing opportunities for businesses and personal growth. Discover practical ways to make AI accessible today, anticipate its transformative impact on African markets, and learn actionable steps to prepare for what's next. Let's talk about:
-How AI and data drive business efficiency and innovation in trading and fintech
-AI tools to elevate trading or business strategies
-How to access and maximise the power of data and AI
-Emerging AI and data trends in Africa and their economic ripple effects
If AI is the engine, data is the fuel. Without quality, accessible data, AI cannot work well; and without the right mindset, data remains just numbers instead of insight. In this session, leading experts will explore how AI and data are democratizing opportunities for businesses and personal growth. Discover practical ways to make AI accessible today, anticipate its transformative impact on African markets, and learn actionable steps to prepare for what's next. Let's talk about:
-How AI and data drive business efficiency and innovation in trading and fintech
-AI tools to elevate trading or business strategies
-How to access and maximise the power of data and AI
-Emerging AI and data trends in Africa and their economic ripple effects
If AI is the engine, data is the fuel. Without quality, accessible data, AI cannot work well; and without the right mindset, data remains just numbers instead of insight. In this session, leading experts will explore how AI and data are democratizing opportunities for businesses and personal growth. Discover practical ways to make AI accessible today, anticipate its transformative impact on African markets, and learn actionable steps to prepare for what's next. Let's talk about:
-How AI and data drive business efficiency and innovation in trading and fintech
-AI tools to elevate trading or business strategies
-How to access and maximise the power of data and AI
-Emerging AI and data trends in Africa and their economic ripple effects
Inside My Best Trade with Jimmy Moyaha
Inside My Best Trade with Jimmy Moyaha
Inside My Best Trade with Jimmy Moyaha
Inside My Best Trade with Jimmy Moyaha
Inside My Best Trade with Jimmy Moyaha
Inside My Best Trade with Jimmy Moyaha
Most market post-mortems describe what happened to prices. Few describe what happened in the trading room while the position was open: the entry conviction, the moments that tested it, and the exit decision that closed the book.
This session brings one seasoned trader to the stage for an unfiltered account of the position that still defines how they think about markets.
Attendees will walk away with:
-A first-hand account of how a conviction trade is built, from thesis and entry through position management and exit
-Understanding of what turns a market observation into a live position, and what holds it when conditions shift
-Insight into how timing, execution quality, and market structure shaped the final result
-Perspective on what the trade revealed about edge, risk tolerance, and when to hold through a position moving against you
-Clarity on what separates a well-built trade from a well-timed one
Most market post-mortems describe what happened to prices. Few describe what happened in the trading room while the position was open: the entry conviction, the moments that tested it, and the exit decision that closed the book.
This session brings one seasoned trader to the stage for an unfiltered account of the position that still defines how they think about markets.
Attendees will walk away with:
-A first-hand account of how a conviction trade is built, from thesis and entry through position management and exit
-Understanding of what turns a market observation into a live position, and what holds it when conditions shift
-Insight into how timing, execution quality, and market structure shaped the final result
-Perspective on what the trade revealed about edge, risk tolerance, and when to hold through a position moving against you
-Clarity on what separates a well-built trade from a well-timed one
Most market post-mortems describe what happened to prices. Few describe what happened in the trading room while the position was open: the entry conviction, the moments that tested it, and the exit decision that closed the book.
This session brings one seasoned trader to the stage for an unfiltered account of the position that still defines how they think about markets.
Attendees will walk away with:
-A first-hand account of how a conviction trade is built, from thesis and entry through position management and exit
-Understanding of what turns a market observation into a live position, and what holds it when conditions shift
-Insight into how timing, execution quality, and market structure shaped the final result
-Perspective on what the trade revealed about edge, risk tolerance, and when to hold through a position moving against you
-Clarity on what separates a well-built trade from a well-timed one
Most market post-mortems describe what happened to prices. Few describe what happened in the trading room while the position was open: the entry conviction, the moments that tested it, and the exit decision that closed the book.
This session brings one seasoned trader to the stage for an unfiltered account of the position that still defines how they think about markets.
Attendees will walk away with:
-A first-hand account of how a conviction trade is built, from thesis and entry through position management and exit
-Understanding of what turns a market observation into a live position, and what holds it when conditions shift
-Insight into how timing, execution quality, and market structure shaped the final result
-Perspective on what the trade revealed about edge, risk tolerance, and when to hold through a position moving against you
-Clarity on what separates a well-built trade from a well-timed one
Most market post-mortems describe what happened to prices. Few describe what happened in the trading room while the position was open: the entry conviction, the moments that tested it, and the exit decision that closed the book.
This session brings one seasoned trader to the stage for an unfiltered account of the position that still defines how they think about markets.
Attendees will walk away with:
-A first-hand account of how a conviction trade is built, from thesis and entry through position management and exit
-Understanding of what turns a market observation into a live position, and what holds it when conditions shift
-Insight into how timing, execution quality, and market structure shaped the final result
-Perspective on what the trade revealed about edge, risk tolerance, and when to hold through a position moving against you
-Clarity on what separates a well-built trade from a well-timed one
Most market post-mortems describe what happened to prices. Few describe what happened in the trading room while the position was open: the entry conviction, the moments that tested it, and the exit decision that closed the book.
This session brings one seasoned trader to the stage for an unfiltered account of the position that still defines how they think about markets.
Attendees will walk away with:
-A first-hand account of how a conviction trade is built, from thesis and entry through position management and exit
-Understanding of what turns a market observation into a live position, and what holds it when conditions shift
-Insight into how timing, execution quality, and market structure shaped the final result
-Perspective on what the trade revealed about edge, risk tolerance, and when to hold through a position moving against you
-Clarity on what separates a well-built trade from a well-timed one
Agentic Inequality: Democratizing Financial Access Through AI & Blockchain
Agentic Inequality: Democratizing Financial Access Through AI & Blockchain
Agentic Inequality: Democratizing Financial Access Through AI & Blockchain
Agentic Inequality: Democratizing Financial Access Through AI & Blockchain
Agentic Inequality: Democratizing Financial Access Through AI & Blockchain
Agentic Inequality: Democratizing Financial Access Through AI & Blockchain
As crypto and CFD trading continue to expand across Africa, access to advanced tools and market insights remains uneven. This session explores how AI and blockchain can bridge that gap by empowering informal traders and underserved communities to participate more effectively in digital financial markets. The discussion will focus on practical applications of technology to improve accessibility, education, and investment outcomes in both formal and informal sectors.
In this discussion, we will explore:
-The role of AI in democratizing access to trading tools, insights, and strategy development
-How crypto and blockchain can enable broader participation beyond traditional financial systems
-Addressing access barriers: infrastructure, education, and affordability in underserved communities
-Opportunities for brokers and platforms to tap into the informal trading economy
As crypto and CFD trading continue to expand across Africa, access to advanced tools and market insights remains uneven. This session explores how AI and blockchain can bridge that gap by empowering informal traders and underserved communities to participate more effectively in digital financial markets. The discussion will focus on practical applications of technology to improve accessibility, education, and investment outcomes in both formal and informal sectors.
In this discussion, we will explore:
-The role of AI in democratizing access to trading tools, insights, and strategy development
-How crypto and blockchain can enable broader participation beyond traditional financial systems
-Addressing access barriers: infrastructure, education, and affordability in underserved communities
-Opportunities for brokers and platforms to tap into the informal trading economy
As crypto and CFD trading continue to expand across Africa, access to advanced tools and market insights remains uneven. This session explores how AI and blockchain can bridge that gap by empowering informal traders and underserved communities to participate more effectively in digital financial markets. The discussion will focus on practical applications of technology to improve accessibility, education, and investment outcomes in both formal and informal sectors.
In this discussion, we will explore:
-The role of AI in democratizing access to trading tools, insights, and strategy development
-How crypto and blockchain can enable broader participation beyond traditional financial systems
-Addressing access barriers: infrastructure, education, and affordability in underserved communities
-Opportunities for brokers and platforms to tap into the informal trading economy
As crypto and CFD trading continue to expand across Africa, access to advanced tools and market insights remains uneven. This session explores how AI and blockchain can bridge that gap by empowering informal traders and underserved communities to participate more effectively in digital financial markets. The discussion will focus on practical applications of technology to improve accessibility, education, and investment outcomes in both formal and informal sectors.
In this discussion, we will explore:
-The role of AI in democratizing access to trading tools, insights, and strategy development
-How crypto and blockchain can enable broader participation beyond traditional financial systems
-Addressing access barriers: infrastructure, education, and affordability in underserved communities
-Opportunities for brokers and platforms to tap into the informal trading economy
As crypto and CFD trading continue to expand across Africa, access to advanced tools and market insights remains uneven. This session explores how AI and blockchain can bridge that gap by empowering informal traders and underserved communities to participate more effectively in digital financial markets. The discussion will focus on practical applications of technology to improve accessibility, education, and investment outcomes in both formal and informal sectors.
In this discussion, we will explore:
-The role of AI in democratizing access to trading tools, insights, and strategy development
-How crypto and blockchain can enable broader participation beyond traditional financial systems
-Addressing access barriers: infrastructure, education, and affordability in underserved communities
-Opportunities for brokers and platforms to tap into the informal trading economy
As crypto and CFD trading continue to expand across Africa, access to advanced tools and market insights remains uneven. This session explores how AI and blockchain can bridge that gap by empowering informal traders and underserved communities to participate more effectively in digital financial markets. The discussion will focus on practical applications of technology to improve accessibility, education, and investment outcomes in both formal and informal sectors.
In this discussion, we will explore:
-The role of AI in democratizing access to trading tools, insights, and strategy development
-How crypto and blockchain can enable broader participation beyond traditional financial systems
-Addressing access barriers: infrastructure, education, and affordability in underserved communities
-Opportunities for brokers and platforms to tap into the informal trading economy