The Equilibrium, a key to success!

First results as a liquidity trader



Hello dear subscribers,


For almost a year now I have been dealing very extensively with the stock market data that I use exclusively for my trading in Forex. At first, like most future traders, I concentrated on the volume, but found that the big players primarily absorb the volume with their limit orders in order to collect the required number of bid and ask. The big players used the volume, in the form of market orders, only to keep the price within a range or to push the price in their direction in order to fill their limit orders with compressed volumes (stops of retail traders). In addition, they began to make massive amounts of liquidity and volume available to themselves when there was relatively little volume on the market. You can also find some posts about this in this blog.

Experiment own liquidity continues!

Overall, the decisive factor is in the area of limit orders, since most traders ignore them. For this reason, in the past few weeks I have concentrated exclusively on the decisive liquidity (limit orders) that come into the market unnoticed in the form of iceberg orders. I initially invested many hours on the side to put together an individual strategy.

I recommend you first look at the following articles.

A completely new market view

Volume versus liquidity

Why volume trading doesn't work

The Truth of successful Liquidity Traders

The truth about the volume profile



As I mentioned in many articles, it is crucial to find out why a bullish or bearish candle is created. A green, bullish candle arises because the euro is bought or the dollar is sold. A red, bearish candle arises because the euro is sold or the dollar is bought. When a big player pushes the price down and the stops of retail traders trigger a chain reaction by triggering further stops, this bearish candle has arisen because the euro was primarily sold. If this retail sale of euro by retail traders is now intercepted by the buy limit orders of the big players, this is a clear indication of an upward trend in the medium term. In addition to concentrating on limit orders, identifying cumulative market orders, open interest, the cumulative delta of limit orders, and reading out the algorithms of the big players with different tones, I tried to create a setup that made sense for me.



The daily range has tripled in the past 20 days and volatility has increased five-fold. This initially prevented me from starting my test run. After the open gap in the forex closed on Thursday, I expected a small drop in the daily range and volatility for Friday. So I started my first experiment on Friday to find out if my setup had a profitable chance.



In the past I traded up and down the range in the Equilibrium. With the future data I have now concentrated on the smaller outbreaks that usually take place before a stophunting. At first it was difficult as a scalper to find the right entries, my plan was to use the best 20 trades of the day to generate a profitable trade. I only traded 18 trades because I still lacked some information, which I then corrected immediately. The experiment got off to a good start and I created an evaluation.



Point A
Overall, I made 18 trades in 9 hours from 09:00 CET to 18:00 CET. I lost 3 trades and won 15 trades. This is initially a win ratio of over 83%.

Point B
Overall, I won € 464 and lost € 53, leaving a net € 411. In this case the win ratio was over 88%.

Point C
I paid my broker a spread of € 108 for these 18 trades, which I also had to earn, because I don't have to pay a commission. The spread was a bit higher than usual, normaly I pay € 72. That would have increased my profit again.

The profit factor was 8.72 since I won € 464.16 and lost 53.23 at the same time. I can be very satisfied with this value.

My first stop loss was 2.7 pip, which I reduced to 2 pip after my first loss. Since I traded the small breakouts, the price should move in my direction immediately after I started, so I am considering reducing the stop loss to 1.5 - 1 pip in the future.

Point D
The drawdown was initially very small because I traded with relatively little Lot. This drawdown will increase significantly in the future. With an account size of € 18,000 and a risk of 1.5 pip with 10 lots, the drawdown would increase to 2.5%, with the same profit ratio. The future risk per trade would then be 0.83% and could be increased to 1.7% in exceptional situations. The return of 2.28% is based on the fact that I was very cautious at first. This could increase drastically if the number of lots is increased.

Point E
What I was particularly pleased about is the fact that I won more long trades than short trades, since I was much more successful with short trades in the past. Maybe also because the short trades run about 30-40% faster than the long trades. But let's take a closer look at the analysis.

Point F
With 7 short trades, I was able to win € 129.81 in a total of 96 seconds, which is a profit of € 1.35 per second. With 8 long trades, I was able to win € 334.35 in a total of 258 seconds, which is a profit of € 1.30 per second. Although I won more on the long side than on the short side, the short side is still more efficient. I will keep an eye on that. In the long range I lose 0.73 € per second while on the short side I only lose 0.17 €. This is also an argument for the short area. The longest trade I made was the short loss of 142 seconds. This is once again proof of the principle of hope. I just waited too long and hoped that the trade would develop in my favor. Typical human behavior.

Point G
Overall, I spent 541 seconds in the market with the 18 trades, which is an average of 30 seconds per trade. Of a total of 9 hours (32,400 seconds) I only used 1.67% of the time to trade in the market. That means there is still enough potential for interesting trade entries.

Point H
The net profit was 410.93 that achieved in 9 minutes, that is a profit of € 45.66 per minute and a very good hourly wage. By increasing the number of lots, this profit can be increased significantly in 9 minutes, with a maximum risk of 0.83% per trade. In this experiment I tried to filter out the best signals for me. One would first have to check whether further signals reduce the profit rate. If that were the case, the risk would have to be increased to 1.7%. This would make a profit 20 times as high as in this experiment.

However, one would have to expect significantly lower volatility and range in the future, which would realistically enable a profit 6 times as high as in this experiment. However, it is questionable whether this high probability of winning can be maintained in the future. The best times in EURUSD are from 07:00 CET to 11:30 CET and from 14:00 CET to 19:30 CET. That is 10 hours to identify optimal trading signals. Part of my future experiments will be to find out if I can trade profitably with less qualitative trading signals. This will result in the future strategy. Either I use further trade signals to keep the risk low or I increase the risk to 1.7% per trade to optimize profits.

Conclusion:

The result is initially positive, but should not be overestimated as it could also be a coincidence. At the same time, this result is also confirmation that the experiment will be followed up. The more data is collected, the more precise a statement will be about my approach.

What did I do differently in this experiment than before?

In principle, nothing, since much of my trading is still based on intuition and experience. I don't sit in front of my screen and watch for a signal that tells me to go long or short. It is a series of different information that I intuitively combine from my 8 screens into one story and make an immediate trading decision. In the past 10 years I have done this a few thousand times in the Equilibrium and today I am able to use this experience. A Setup is an individual thing, even if I described my approach exactly, the result for other traders would still be different. You have to compare that with a setup of a racing car. If a racing driver were to drive with his colleague's setup, this could possibly lead to a bad accident. In this blog you will find different ideas to create your own setup. No one else can do this work for you. Successful trading does not work by waiting for intersecting Moving Averages who tell you: Entry or Exit. Successful trading is a hell of a challenge. I work with complicated algorithms and extremely well-resolved and filtered stock market data, but I still lose regularly.

A subscriber on our blog put it so nicely, I would like to quote his words.

In the DAX, I trade in the M1 with very short-term trades to cut out a few points. Why do I achieve a hit rate of 75% in good phases? (By "good phase" I mean: if I can suppress the gambling instinct, that is to say I am maximally disciplined). The fact is that I somehow now see what - probably - is about to happen. Of course not just intuition and gut feeling, but also based on rational considerations (and a lot of screen time in recent years). But I like to compare it to driving on the motorway: Why do I know that the car in the right lane will probably change to the left lane (although it is not flashing)?

I think he put it in a nutshell.

It is precisely this intuition, the gut feeling and a rational approach that will bring the long-term success you want. For that you have to be ready to work hard (screentime, screentime and again screentime). I am very proud that this blog brings together so many traders who take their work very seriously. That will take us all one step further.

Many thanks to all subscribers who make this blog so successful.

I wish you a relaxing weekend

Lovely wishes
Michael

Who is our biggest competitor in trading?



Hello dear subscribers,


The Forex market generates over $ 6 trillion in sales every day, including over $ 2 trillion, in the EURUSD. However, only about 1/1000 of this turnover is actually exchanged for money in one day. If a lot of $ 100,000 is used, a stop of 10 pip is worth about $ 100, this $ 100 was calculated per lot in this example.



The big players win around $ 133 million in EURUSD every day, 2/3 of which they take from retail traders and 1/3 from institutional traders.



In our assumption, we assume that 100 big players, 10,000 institutional traders and 1 million retail traders trade in EURUSD every day. That is a total of 1,010,100 trading participants per day.

Point A
Since the big players operate with a win rate of around 90%, ten big players lose around $ 166 million in one day. 6,000 institutional traders lose a total of $ 133 million and 900,000 retail traders lose a total of $ 100 million. That means 906,010 trading participants lose a total of $ 400 million.

Point B
90 big players win $ 300 million, 4000 institutional traders win $ 90 million and 100,000 retail traders win $ 10 million. A total of 104,090 trading participants win $ 400 million a day. Of course, you have to take into account that the profits and losses change permanently for all trading participants. Every dollar that is lost benefits another trading participant, so that the balance is balanced at all times. If someone loses money, it is not gone, but someone else is happy about it. Mostly, unfortunately, the big players.

Point C
At the end of the day, the balance should look like this. The big players win $ 133 million by taking $ 43.3 million from institutional traders and $ 90 million from retail traders.

Point D
This means that 906,010 trading participants lose an average of $ 441 per day and 104,090 trading participants gain an average of $ 3843. Since almost 90% of all trading participants lose in the EURUSD, the overall chance is 1:10. If you look at these results, you might think at first glance that the big players are our biggest competitors. But is that really true?

First of all, we have to realize that a market can only move if there are different opinions and therefore different market executions. If there are 100 traders in a market and everyone takes a short position, nothing will happen. Only when some traders start building a long position will the market move. Next we have to think about which market participant is able to move the market.

Big players are definitely the largest players with the most money. They are able to move the market the most. This is followed by the institutional traders who can move the market in medium strength. In the end, there are the retail traders who would only be able to move the market if a few 1000 traders opened short or long positions at the same time. Since this rarely happens, retail traders are hardly able to move the market more. However, retail traders have one thing in common, and these are their stop positions, which are very close to each other.



Let's look at a classic example. At first there was a stronger downward movement from point A to B. There was a small equilibrium, then suddenly there was a strong movement to point C. The blue lines mark the entrances of retail traders. Few of the retail traders entered before this strong upward movement, but the most took a long position in the area of Point C. They placed their stops at stop 1. After the course ran from point D to point E, most stops were placed at point stop 2. As the price went higher, some traders shifted their stop 1 to stop 2. We can now clearly see, that the big players triggered exactly these stops and then pushed the price up.

Why did the big players push the course down from Point E? There are two reasons for this. First and foremost, big players need volume to absorb with their limit orders. They knew exactly that there were many stops by retail traders at Stop 2. By now pushing the price down, you could make cheap purchases at stop 1 and stop 2. At the same time, you pushed the long traders out of the market. This means that the big players are primarily focused on the stops of retail traders, because at this point they always find a high volume that they can take up with their limit orders.

Now we come back to our question: Are the big players our biggest competitors? I would answer this question with a clear no at first, because the big players help us to push the course up or down and at the same time are responsible for the fact that we have any chance of winning. In my eyes, the mass of retail traders is a much bigger competitor for us. In many forums, retail traders gather against the big players. The bad big player is responsible for retail traders always losing. So you have to join forces because together you are strong and have a chance against the big players.

But the opposite is the case. Precisely because the retail traders exchange ideas so strongly and even recommend concrete entrances and exits, many beginners are motivated to follow this information. Typical tenets such as: “Always stop below the last low” create more frustration than benefit. This false information creates a herd instinct that makes it easy for the big player to stop some 1000 traders in one fell swoop. In this case, out of 1,000 white sheep, it would be better to actually be the only black sheep. But you have to be ready to do the opposite of the crowd. Many traders sit in front of their screens and first look at what other traders are predicting about a particular currency pair. Let us assume that the beginner expects a downward movement. Now there are 20 retail traders who also expect a downward movement, then the beginner will feel confirmed and will look for short positions. If 20 retail traders anticipate an upward move, the beginner will be unsure and will likely not enter the downward move. Just get a picture for yourself and see whats happens if a price goes up sharply. You will find that in this case, most retail traders have taken short positions. This means that most retail traders' statements about a possible price trend are incorrect. If we do know that, I wonder why we still look at what opinions many retail traders have about a particular currency pair.

There are even more extreme examples, some look for certain retail traders and see how often their predictions have actually come true. If this rate is high, they will orientate themselve according to their statements in the future. Then they could also do copy trading.

Over 90% of statements made by retail traders are factually wrong, so I strongly recommend that you rely solely on yourself. The only way to win in this market is to understand exactly how big players work. The big players are the only power that can significantly influence these markets. Of course, institutional traders also have the opportunity to move markets, but we must never forget that 85% of the Forex market will be controlled by twelve banks. For this very reason, the focus must be exclusively on the big players. If you want to be successful in this market, you should take a closer look at Stophunting. The prices basically always zigzag up and down because the big players regularly need liquidity to push a price up or down. For this reason the Stophunting takes place permanently.

Of course, a competitor is someone who can do something better than yourself. From this point of view, a big player could be described as a bigger competitor than the retail trader. But it is absolutely not wise to team up with retail traders who lose in 90% of the cases. It would be wiser to team up with a big player, but it will rarely succeed. Therefore, in the end there is only the possibility to find out what a big player does differently than the majority of retail traders. If you want to analyze your competition, you first have to put yourself in your situation and see the world through your eyes. In this blog you will find a lot of information about different approaches of the big players and how to identify them using stock market data.

Through constant comparisons of competitive situations, people find their social position and orient themselves in their environment. We retail traders always want to understand and classify everything and the same applies to our own role. Through competition, we learn to understand where we stand and how others differ in a positive or negative way. This is sometimes very tiring and strains our nerves, but competition is useful and sometimes even necessary. If we manage to see each other's advantage as an opportunity, we will be able to change ourselves. Then the idea of competition can provide us with a motivation boost. However, if we do not take a critical look at ourselves at the same time, there may well be competition. And in this fight there are usually two losers. However, we did not start in this market for to lose, we want to win. To win, we have to use the best as role models. And the best trainers in the world are the twelve banks that control 85% of the Forex market. For me, the big players are not competitors, but the best coaches in the world. However, you do not have the peculiarity of explaining to us how you act and proceed. We have to find that out ourselves with great effort. But one thing is certain: once you understand the strategy of the big players, you will be successful in this market and could live very well from it in the next few years. So my recommendation to you, focus only on the big players.

In my last post, I described with concrete figures how such an approach can pay off. Maybe that will help change future priorities.

First results as a liquidity trader

I will of course continue this experiment and inform you about it regularly.

I wish you a nice Sunday and a successful trading week

best regards
Michael

Iceberg orders of the big players



Hello dear subscribers,


I have been working intensively on tick charts and stock market data for a long time now. As I have already written in many reports, the entry and exit of the big players primarily takes place via limit orders. First, in a range ask or bid will collected, in the form of cumulative limit orders. Accumulated limit orders will also be used for the exit. These cumulative limit orders are called iceberg orders because they barely be identified in the market.

Of course, the big players also use the market orders to keep the price within a range during their collection campaigns. Market orders are also required to start stops or initiate a breakout. These market orders are accumulated through algorithms in the market to hide the real intentions. A 300 lot order is divided into small orders that are placed on the market within a 1/1000 second. The cumulative market orders are relatively easy to identify and display in the chart.

A completely new market view




Here we see cumulative market orders that I have filtered according to a certain system in order to be able to display them. The cumulative market orders include both the big players and the institutional traders. We can assume with a high probability that the retail traders are not included in these market orders. In the next step I will try to distinguish the big players from the institutional traders in the area of the cumulative market orders. These market orders that we see here are used to keep the price within a range, for stophunting, as well as for the start of the breakouts. I created the representation in a volume overview.



The same overview in a delta display. The advantage of this view is that ask and bid have been resolve to create a delta. This removes the price regions that are not relevant and gives a more precise overview of where the cumulative market orders were used.


Big players get in and out almost only with iceberg orders

How does an iceberg order come about? First, a big player pushes the course into a price region where as many stops as possible are suspected. There, limit orders prepared by the algorithms are already waiting for absorption. In the DOM there are initially no abnormalities, you can see an average of 80 lot limit orders at each price level. The price reaches the first stops that come into the market as market orders and are absorbed by the limit orders of the big player. Interestingly, 200 lots are now absorbed at one price level, although only 80 lot limit orders were visible in the DOM. The process is relatively simple, the algorithms ensure that new limit orders are always added at a price level in order to intercept the triggered stops. Now there is a chain reaction, the stops push the price further and thus trigger further stops, which are also absorbed by the iceberg orders, which are waiting at different price levels. The big player has to make sure that the absorption does not stop at the price and thus stops the chain reaction. However, this can often not be avoided, in which case further market orders from the big player must be placed in order to start the chain reaction again.

In principle, you could easily identify the iceberg orders with good software. To do this, you have to compare the visible number of limit orders with the actual number of cumulative market orders. If there were 80 lot limit orders on one price level but 300 lot cumulative market orders were absorbed, it is an iceberg order. A trader only sees the 80 lot limit orders, but not that in this case the lot has been replenished by the algorithms. For this reason, iceberg orders are difficult to identify. But that is crucial, because after all you can see what the big players are up to in the medium term. Even if you can identify iceberg orders with spoofing in the DOM, the trader lacks an overview of exactly where it took place in the chart. Another crucial point is the fact that iceberg orders are constantly entering the market. It is therefore crucial to display these iceberg orders in the chart to create derivatives from it.

So we know: The iceberg orders are primarily used for the entry and exit of big players. In order to make the iceberg orders visible in the chart, I initially concentrated on a certain number of cumulative market orders. These cumulative market orders come into the market exclusively through triggered stops and are simultaneously taken up by the limit orders. With this strategy, I managed to make iceberg orders visible in a chart for the first time.



Here I tried to show the iceberg orders in a volume chart. Of course, a volume chart is not optimal, since ask and bid are displayed together. But the main thing here is to find out in which areas the iceberg orders come into the market. It should be noted that the iceberg orders are usually generated in a high volume. And that is also logical, because when stops are triggered, it is usually a high volume. Red zones within a bull candle and green zones within a bear candle often show an exit from the position. At the same time, you can also display the collection of counterpositions to initiate a turnaround. In this picture you can see that very nicely.



I get a much better overview with a delta chart, where I have also made the iceberg orders visible. With this representation, I first filter out the unimportant deltas that are not relevant for the entry or exit of a big player. Although I don't recognize the volume with it, as we have already determined, most iceberg orders are generated in a high volume range anyway. This means that I have filtered out the information that is most important to me at a glance. The next step will be to determine the exact entries and exits of the big players. It will certainly not be easy, but it is possible.



Here we see the display of all limit orders in the delta during the same period. Now we will compare the total limit orders with the iceberg orders.



The limit orders total are on the left, the filtered iceberg orders are on the right.

Point A
When the price rose sharply, we can already see that the big players have started to get out of the position and at the same time collect bids to push the price down again.

Point B and C
Here we see a clear willingness to push the price down sharply.

Point D
Here too, there is clear confirmation that the price will continue to move lower.

Point E
This is a peculiarity, because the big players have made themselves available liquidity in the area. Then the course was pushed down.

Point F
First the big player got out of his short position and bought a lot of limit buy orders. These strong buy limit orders cannot be seen in the limit delta Total. After that, the price was pushed up and the big player was able to close his still open long position, where he made himself available liquidity.

We recognize that the only way to predict future price trends with a high degree of probability is to be found only in the area of iceberg orders. First of all, I filtered the iceberg orders exclusively from price levels that absorbed a certain number of cumulative market orders. In the future it will be a matter of optimizing the filter settings in order to achieve a better display. This will enable us to obtain a unique market overview in the future. At the same time, we will take a closer look at the heat map to improve the filter settings there in the future. Since the big players increasingly work with their own liquidity in order to initiate trend reversals more quickly, this presentation is an essential factor for the identification of limit orders.

In my last posts I showed you that I concentrate exclusively on the limit order. Oddly enough, the market orders move the market, but the limit orders determine where the market is going in the long term. For this reason, I can only recommend everyone to refrain from volume trading and to develop into a liquidity trader. The way there is a bit more complex, but the results are also much more efficient.

I hope that I could give you a little insight into liquidity trading, which we will continue to deal with in the future.

I wish you a successful trading day

best regards
Michael

Thank you, always interesting.
Point E is a problem how could we avoid it ?

Big players own liquidity


Hello rosalieone,


Thank you for your kind compliment, I am most pleased that the information helps you and you work with it. I would like to answer your question.

First of all, we cannot prevent the big players from providing themselves with liquidity in order to save time for tedious collecting in the equilibrium. As it looks, this approach has become established among the big players and we will often have to deal with it in the future. It is crucial how you identify this strategy and what measures you derive from it.

In the example presented under point E, a big player has absorbed a large number of sell market orders simultaneously with his buy limit orders. Then he pushed the price down and sold his sell position (exit from the dollar). At the same time, he started collecting buy limit orders on the low and has now pushed the price up. Then he got out of his Europosition and closed the Europosition he acquired at Point E. The reason the big player provided himself with liquidity was that he was unable to buy enough dollars from Point E. To clearly identify this procedure, you need a heatmap.



Here is an example in a heat map. At point A, the big player absorbs his own buy market orders with his own sell limit orders and then pushes the price down. He now has two options. He tries to get out of his euro position with a little loss in the equilibrium and then pushes the price down. Or he not leaves the euro position, pushes the price down, gets out of the dollar and pushes the position back up to close it. The risk here is no greater than if he had laboriously collected positions in the equilibrium.

I wrote a few articles about this.

Own liquidity for the big players

On February 19, shortly before the price in the EURUSD went up 700 pip again, I consciously noticed this. Usually the big players wanted to close the open gap there, they had already collected strong sell limits, but found that too many traders were short. They initially sold their short positions to retail traders and at the same time secured themselves liquidity in order to push the price higher. Since then, I've been observing with other traders, this procedure. First of all, it was an experiment for the big players that absolutely paid off in the end result. Since then, we have seen increased campaigns where the big players make their own liquidity available. For us this is always an excellent start with an absolute guarantee of profit. In my opinion, this approach is already an integral part of the big player strategy. The advantage is still on the side of the big players, since very few know about it. Actually, there would be much better strategies for the big players, I don’t understand why they’re not more creative.

I recommend that you take a closer look at this “own liquidity” approach. The frequency of the strategy is new and very few suspect what exactly is going on. For those who identify this strategy, it means a quick and safe win.

I hope that I could help you.

best regards
Michael

The current market situation



Hello dear subscribers,




In the last 4 trading days, the daily range in EURUSD has declined somewhat and volatility has subsided somewhat.



Apparently the Dax and Dow are also uphill again. It is normal for financial markets to run up again and again for a few days in the course of a crash, because many traders and investors sense the opportunity to buy shares of established companies at low prices. The hope is that they will be the first to benefit from an economic recovery. Dead cat bounce, say the US stock marketers, when the market recovers in the short term after a long phase of falling prices. Most of the time it goes down, after this short high. The term comes from the English saying: Even a dead cat will bounce if it is dropped from high enough!

Almost a week ago I published a diagram about the current situation in the Corona crisis. Now let's take a look at what changed 1 week later.



We are now close to 440,000 infected people and the death rate has risen to 4.5%. This rate is between 0.5 -9.9%. Over 25% have already been cured and have produced antibodies. That gives a little hope.



The number of infected people has almost doubled in the last 7 days. Every day, almost 30,000 people are newly infected worldwide. One person dies every minute from the Corona Virus, but at the same time there are a large number of recovered patients in the individual countries.



Point A
In Germany we have one of the best health systems in the world. Germany was laughed at for many years because we had so many hospitals. With 28,000 intensive care beds, there are 34 ventilation places per 100,000 inhabitants, in many European countries the number is 3-5. However, we also pay very high health insurance contributions for this. The capacity of the intensive care units is to be increased again by 10,000 within the next 12 months. This shows what the German state expects in the future in the area of the corona crisis. Although we are on the brink of an outbreak, Germany has taken Corona patients from Italy and France. This shows how important it is to help each other. If the crisis worsened, the whole world would have to make their free intensive care beds available to everyone. I'm curious to see how people will behave in this crisis.

Point B
On March 10, 2020, a large German newspaper, in collaboration with some virologists, made an extreme projection, which many laughed at. On March 10th we had 1218 infected and for the 24.03.2020 a four-fold increase to 4,872 infected persons was forecast. The actual number was on March 24th. in 31,370 infected people. Although I believe that the number of unreported cases is significantly higher. The value from 07.04.2020 we can no longer reach because we already have more than 36,000 infected.

Aid from central banks and governments has helped in the short term to prevent panic from the collapse of the economy and capital markets. The US Congress has agreed to put together a $ 2 trillion stimulus package, which the stock exchange has benevolently registered. Of course, this could not prevent production in almost all branches of the world from coming to a standstill. Such a situation is only known from times of war.

Everyone wishes that we could start all activities again after Easter. But that seems to remain an unfulfillable wish. The World Financial Center New York City is extremely badly affected, with almost 16,000 people infected. The situation in the city will not improve in the next few days and that will also leave its mark on the New York Stock Exchange, which is the model for many stock exchanges around the world.

I believe that the current situation is just the calm before the storm. The fact that everything is calm at the moment is only because the tornado is just above us. In my eyes, it is still too early to give the all-clear and return to normal. Some virologists believe that the total population of the earth must be 60-70 percent infected so that enough antibodies can be formed to defeat the virus. We currently have house arrest in Europe to curb the spread, but as long as there is no vaccine or medication, the virus will spread sooner or later. Many people will still die, many companies will go bankrupt, but this may bring the world closer together.

I am convinced that we will defeat the virus, but until then the world will stand still. I just hope that in the end we'll learn our lessons and change some things that will benefit the world and future generations.

Lovely wishes
Michael

m15 in block 0.9
marked blocks are big players for me
players were very active today

Big players


Hello kette,

I see that you also work with professional stock market data that you have translated by good software. In addition, you program your own indicators that advance you. Absolutely great.



Here's another illustration from yesterday. The limit orders were represented as delta and refer to a filtered representation of the iceberg orders. Yesterday there was again an increase in the volume of “own liquidity”. The crucial thing about displaying any chart is that the trader gets a trading advantage from it. And your approach definitely fulfills this requirement.

Focusing on the big players is a logical approach, as they influence and manipulate the market in their favor. Those who follow this approach will generate more trading advantages than other market participants.

Lovely wishes
Michael

The money robot


Hello dear subscribers,


An interesting film documentation about algorithms in exchange trading was published 2 days ago by ARTE.

Time is money: In automated stock exchange trading, those who have the fastest data network do the best business. It goes around a millionth of a second. Computers trade in computers, only committed to their algorithms. People have long since got out and left the field to the far more efficient money robots. An uncontrollable financial market has emerged in which bets are placed on crises and investments are no longer a real factor. It all started in the gaming paradise of Las Vegas, where young physicists in the mid-1970s tried to outwit the bank with probability calculations. Their algorithms turned roulette and blackjack into predictable operations - and were successfully transferred to the financial market. Automated exchange trading is now a multi-billion dollar business. It is no longer the investment itself that leads to profit, but the multiple purchase and resale. Tiny margins result in huge profits from large order volumes - but also almost unimaginable losses. When prices plummeted worldwide in February 2018, no one had an explanation for it: within a few minutes, billions of dollars were lost. There was almost a new global economic crisis. Experts now agree that it was money robots that caused the collapse of exchange trading.



French, Americans and Germans have their say in the report, which were then translated into German by a spokesman. In YouTube, however, you have the advantage that you can display subtitles in your language under Settings.

First of all I ask you to look at this documentation of 90 minutes in the next few days. It will open your eyes a bit, what is happening in the markets and why most traders are losing. The report is also easy to understand for laypersons who have not yet dealt with algorithms. It describes very clearly the power of big players and high-frequency traders and why even stock market regulators cannot do anything about it.

If you have seen this report, at first glance you will believe that you cannot defend yourself against this procedure and that every smaller retail trader is absolutely without chance. But that is a mistake. It is possible to come up against these algorithms because these algorithms always work on the same principle, since they are executed by machines. Of course, with an RSI, MACD and moving average, you can't get against these algorithms, but you can identify them with appropriate software and make them visible. If you follow my blog and are interested in this information, I will give you concrete information in our new project No. 11: “Algorithms of the Big Players”, to beat these algorithms with a high probability.

Therefore, first watch this video because it gives you a basic understanding of how big players and high-frequency traders work. In the next few days we will then start our new project and go into detail about the different options.

Here is the documentation: The money robot



I look forward to another great collaboration with you, thank you all for the contributions and questions you have made so far, and I am sure that we will take another step forward in the coming months.

Lovely wishes
Michael

Can't watch it in the UK.

Youtube videos


Hello lemercenaire,

Due to the GEMA agreement, YouTube videos may still be blocked. Under certain circumstances, this blockade can be removed. Take a look on the Internet at: "Youtube countries lock", there you will find some information. Just make sure that this is also legally permissible, because violations of this kind can cause considerable costs. This may also have something to do with Brexit.

I hope that I could help you

Lovely wishes
Michael

Could use a VPN but yeah, thanks. Don't think it has much of anything to do with Brexit.

Hi Michael

I am really happy to be part even a little of your blog how important and useful information you translate in such easy and understandable way for beginners and advanced traders.

I am really focus in developing and go deeper into coding skills, I am currently learning and studying a lot, several programs languages and I am so happy and amazing with all that, I love study and learn new things and go deeper to master such skills.

Really and deep congratulations to you and yours efforts to share and make it easy as it is possible to all here understand.

I am a big admirer of your work, all my deeply respect to you my friend.

Cheers
DC

On the trail of the algorithms

[quote=Dcrs;12838754]{quote} Hi Michael I am really happy to be part even a little of your blog how important and useful information you translate in such easy and understandable way for beginners and advanced traders.


Hello Dcrs,

I am also a small part of these blogs, because success always consists of many small individual parts that add up to something big. To be successful, you have to make sure that you keep it. By listening you keep 20%, by seeing 30%, by hearing and seeing 50%, by retelling or explaining 70% and the highest rate of 90% can only be achieved if you do it yourself.

When I completed my Oracle Java Master within 2,000 hours over a year ago, this concentration on it took a lot of time. It is a special art to do many things at the same time. This is comparable to a plate spinner, that turns 10 plates on 10 bars at the same time and makes sure that no plate falls off. I keep my fingers crossed for you that you can manage this challenge.

In any case, programming languages are a little help to better understand the quants and algorithms on the stock exchange. But we also have to be aware that it takes at least 10 years to be a professional in a certain area. And at the latest here you have to decide, programmers or traders. A combination of physicists, mathematicians, programmers and traders results in the optimal mix for developing complex financial instruments. In addition, they need a very complex technology,, that is directly connected to the foreign exchange with microwaves. These are all things that we retail traders can never achieve.

But if we act creatively, we don't need all of these things, because ultimately the decisive factor is how a result comes about. And we will only deal with these results and, at the same time, do without the previously complex activities to achieve this particular result. Any algorithm can be easily cracked once you have found a way to make it visible.

Therefore I would like to ask all subscribers once again to read through my last post and watch the video posted there. We will build on that.

The money robot

Thank you for admiring my work, I think it is much more important that you succeed in identifying the algorithms of the big players and that your chance of winning increases drastically. We are really lucky that the big players are sometimes so amateurish that some traders can see exactly what they are up to.
However, this has only been possible thanks to the new technology. We will talk about this in more detail in the next few weeks.

I wish you a successful trading week

best regards
Michael

Tks Michael for your view and kind words.

About the video I tried to see was not able in my country have do manage it, but it is not a problem.

I perfect understand your view about many, tasks at the same time and etc...

Fortunately the technology/security/coding etc...
Is kind of the family blood, since I am the youngest chield with more then 34y old, I still remember my big brother when he started into those areas before I was even 5y old.

He is more then graduate in several areas and has so much knowledge in so many areas like it is hard so see often.

I take this as advantage for me and for have a lot a bases for it.

About financial markets I am at my 8 year.

I will look into the video and come back if I'll be abe to give some help.

Cheers thanks again Michael

Big player algorithms


Hello dear traders,

In the next few weeks, we want to use our new project 11 to identify the algorithms of the big players in order to generate trading advantages. If you are interested in this project, please start by watching the video I have posted. This gives you some basic information that is important for our project.

The money robot

I have been dealing with these algorithms for some time and a few weeks ago I created a project screen for our upcoming project to identify these algorithms. First of all I would like to introduce you to the individual modules. Then you could see this project screen in action in a video.



Point A
We see a heat map here. The green and red lines are limit orders, which were filtered differently in a seconds chart depending on the size. These limit orders are initially placed by the big players in different sizes using algorithms in a waiting position in the DOM in order to absorb the market orders depending on the market situation. As soon as retail traders trigger stops in the market, this creates cumulative market orders that are absorbed by the limit orders of the big players. The algorithms ensure that initially only a certain number of limit orders are in the waiting position in the DOM and that new limit orders are always added if necessary. These are the so-called iceberg orders, the size of which is very difficult to determine. The green and red circles are cumulative market orders and show, on the one hand, the triggered stops and, on the other hand, the situation when a big player uses market orders to push the market in his direction. This makes it possible to determine immediately if a big player is making liquidity available to take up his market orders placed on the market, simultaneously with his own limit orders.

This situation has been very common since February 19. Usually this happens when there is little liquidity in the market, on Friday I identified 21 situations where big players made their own liquidity available. On the left side you can see my limit delta of the day, on the right side the current limit orders in the waiting position in the DOM. The green and red lines below measure the speed of purchases and sales within the candle, divided by bid and ask. This information is another decisive factor that we will talk about in the next few weeks. A large number of algorithms were already used in this presentation to identify the limit orders and market orders. The different calculations in the software require an enormous amount of memory, in very volatile phases only the program for calculating the algorithms occupies up to 16 GB of ram memory. An MT4, on the other hand, only requires about 50 MB of RAM.

Point B
A filtered footprint chart that hides a predetermined number of imbalances. The buy limit orders are on the left, the sell limit orders are on the right. The blue fields represent a certain number of limit orders that came into the market. This means that the display focuses on the limit orders that are price-sensitive. On the right is the DOM and below it the speed of the candle, divided into bid and ask in the 30 second chart. Below that we see the delta of market orders.

Point C
Here we see the sell market orders that have been filtered in a specific sequence. On the left we see the labeling for a possible pushing of the price by the big players and next to it we only see cumulative sell market orders. The colored segments show the impact of the big players through stophunting or by pushing the price down. The individual market orders are also displayed in different tones. Since a lot of tones come in during volatile phases, you have to make sure that these tones can also be displayed in the millisecond range. For this you need certain frequencies that can be distinguished in a quick succession and that have a short call duration. This is a kind of third dimension in trading, which is an invaluable advantage for me because I can perceive the incoming, different market orders acoustically. This has significantly improved my response time again.

Point D
Here we see the buy market orders that have been filtered in a specific sequence. On the right we see the marking for a possible push of the price on the part of the big players and next to it we only see cumulative buy market orders. The colored segments show the impact of the big players through stophunting or by pushing the price upwards. In my other charts, there is a precise definition of different market and limit orders, which also show the exact number of the respective lot and the time in milliseconds.

Point E
This is a special market profile. Only a certain number of cumulative sell and buy market orders are calculated, which should identify the price pushing of a big player. The individual market orders of retail traders are not recorded because this would make it difficult to identify the big players. The interaction of the limit order in the DOM with the cumulative market orders is very interesting.

Point F
Here I have inserted a chart from the Forex market in the M1 for an overview. The spread display of bid and ask is important. As a candle, I use the Bionic candle that I developed, which gives me faster information than all conventional candle shapes. You can find information and indicators on the Bionic candle in the complete project no.2 within my blog. The project starts here:

Project number two

Point G
A special algorithm works in the 1 Range X Chart. First of all I colored the respective candle strength with different accumulated market orders. Different factors such as speed, volatility, pullbacks and the time calculate a possible turning point which, if it appears, is not deleted. However, this is only a rough guide, which also tells me about acoustically when it comes to such a reversal point.

Point H
Here we see the "open interest", which are all open long positions in the market that are not calculated according to size of lot but according to transactions. Since the big players work almost exclusively with cumulative market orders anyway, this presentation is very interesting. Possible stops that are triggered often distort the optimal display, but as a rough guide this is a real help. However, the information is only available from the Russian market, since it is unfortunately not available from the American stock exchange.

Point I
The cumulative delta is a very interesting representation because it shows bid and ask cumulatively over a day. Triggered stops can be identified immediately and there are amazing resistance zones in the cumulative delta that work very well. Below we see the individually resolved delta. The combination of open interest with the cumulative delta is an excellent way to grasp the current market situation very quickly.

Point J
Here is a special speed analysis of a candle in a 1 second chart. Again, the movements between bid and ask within a candle are differentiated from each other. This shows very quickly how the retail traders are positioned and how the big players react to them.

Point K
In addition to the total volume, the delta of the sell limit orders and the delta of the buy limit orders were shown graphically in a limit profile. In my latest charts, I filtered this delta to show the iceberg orders. This will hide all irrelevant limit orders and you can concentrate on the decisive limit orders. On the right we see the limit orders in the DOM again and on the left the delta of the limit orders from the day.

First of all, this is just a small part of our new project to identify the possible algorithms of the big players. First I created a video for you so that you can see the different representations live on the stock exchange market. At this point the price was in an upward movement.



At first glance, the chart seems absolutely confusing and opaque. But we have to keep in mind that this is raw stock market data that has been adjusted by software according to my needs. In the past few days, my algorithm experiment has had a win rate of over 80% and a maximum drawdown of 0.85%. The profit factor was 4. It is crucial that you can see exactly what is happening in the market from your chart views. And each trader has to make these settings individually. In addition, I still work with pure candle charts in the MT4 to get an overview in Stophunting. You will also receive specific information on this blog.

Our new project is about the identification of big player algorithms. There are many different ways to use algorithms, particularly interesting is the way big players use their algorithms in retail. We will talk about this in great detail next week. Algorithms can be described as a kind of Morse code that shoots trading orders into the market in a certain sequence. It should be clear that you first have to recognize these Morse codes. After that, it is possible to filter and translate the Morse code. In the end, this translation must be associated with a current market situation in order to generate market advantages. This is a big challenge at first, but identification is easier than you think. However, you need appropriate software and stock market data, which should not cost more than $ 50 a month depending on online research.

Important note:

I work with stock market data and a special prop software that I chose from countless hours of Internet research. I have already described these modules in detail, but I do not want to advertise them because I only earn my money by trading. The software and stock market data I selected only correspond to my personal needs and are definitely not the ultimate. Since I work with these modules, I can of course only refer to them. When I do that, I ask that you do not take it as advertising, and I also avoid giving the names of the companies permanently. I recommend everyone who wants to buy stock market data or a suitable software to get detailed information on the Internet first. Do not listen to stupid advertising and recommendations, form your own opinion and test free of charge, different options. The data has to help you, so you have to invest a lot of time to find the best. And in the end, the best thing is always what you have the most success with. This is comparable to looking for a car, cell phone, a telephone tariff or a good electricity provider. To find the best price-performance ratio, you first have to invest a lot of time. If you buy too cheap or if you listen to wrong recommendations, you end up buying twice. One point, however, should be kept in mind: You trade hard-saved money and lose it over the years. If you want to be successful in the trader profession, you should invest in the right place. This can be in hardware, software, internet, but also in the area of health and nutrition. You have it in your own hands.

I wish you a great weekend

best regards
Michael

Experiment limit orders and algorithms


Hello dear subscribers,


on May 21st I published my first result in the experiment as a liquidity trader.

First results as a liquidity trader

At first the numbers looked very promising, I expected the values to deteriorate significantly in the future. My statement:

The result is initially positive, but should not be overestimated as it could also be a coincidence. At the same time, this result is also confirmation that the experiment will be pursued further. The more data is collected, the more precise a statement will be about my approach.



So I continued this experiment for 3 more days and made further trades based on the liquidity and the identification of algorithms. I worked with the screen I created for it, which provided me with the necessary information. I have this screen in preparation for our new project: "The Algorithms of Big Players", described in my last post:

Big player algorithms

My goal was to do 20 trades a day, in the first experiment I only had 18 trades. In another 3 days I came to a total of 85 trades, whereby the quotas, as I had already suspected, deteriorated somewhat. Let us first take a closer look at the overall result of these 4 days.



First I continued where I left off and forgot to set a stop loss at Point A. Within a few seconds there was an extreme breakout that took me € 120 deep. I managed to close the trade manually and was annoyed with my stupidity. With my normal stop loss the breakout would have been costs € 20, we see how important a stop can be for scalpers. Usually my software automatically set a stop loss when I start with the trade, I probably had accidentally deactivated the function. At first this loss ruined my quotas a bit, but I was confident that this experiment could still be successful. What annoys me most is when the average losses are higher than the average profits, that's a crucial point for a scalper. Let's look at the evaluation of these 85 trades.



Point A
Overall, I made 85 trades in 4 days. I lost 15 trades and won 70 trades. This is initially a win ratio of over 82%. But that doesn't say much at first.

Point B
Overall, I won € 1,594 and lost € 393, net remained € 1,200. In this case the profit ratio was over 75%.

Point C
I paid my broker a spread of € 418 for these 85 trades, they I also had to won, because I don't have to pay a commission. The spread was a bit higher than usual, normally I usually pay € 320. That would have increased my profit again. The profit factor was 4.05 because I won € 1594 and lost € 393 at the same time. One can still be very satisfied with this value.

Point D
The drawdown increased to 0.85% due to my high loss trade, but was still within the framework. Still, smaller drawdowns are preferred. The expected payoff was € 14.13 per trade, there is still significant upside potential.

Point E
What I was particularly pleased about is the fact that I won more long trades than short trades again, since I was much more successful with short trades in the past. Maybe also because the short trades run about 30-40% faster than the long trades.

Point F
Overall, I spent 2481 seconds in the market with the 85 trades, which is an average of 29 seconds per trade. Out of 36 hours, I only used 1.89% of the time to trade in the market. That means there is still enough potential for interesting trade entries.

Point G
The net profit was 1200 € which was achieved in 41 minutes, that is a profit of 29.28 € per minute and a good hourly wage.



Since I usually always work with a stop, I have now calculated what it would have looked like if the stop had been in the market. That would have led to a significant improvement in the quotas. In this case, the average losses would have been offset by the average profits. However, the goal should be that the losses are smaller on average than the profits. By reducing the stop to 1.5 pip, the risk-reward ratio should be at least 1: 1. Usually my risk-reward ratio is also higher, but then the profit ratio is reduced at the same time.



Here we see the last two days, the win rate was over 80% and the average winning trades were larger than the losing trades. Here I extended my stop once because I thought I could see from the algorithms that the course was going back. Typical human failure, in the principle of hope. That once again cost me quotas. Nevertheless, the profit factor was 5 and the drawdown was 0.22%. No matter which side you look at it from, there are clear weaknesses that I have to work on. But it is crucial that I know exactly what weaknesses I have and how I can fix them. The problem with many traders is that there is no one who tells them what they need to change. How should a trader change something if he doesn't know what needs to be changed? Everyone can easily carry out this evaluation themselves in the MT4, of course you can also use online providers for this, but I reject this for data protection reasons.

Here is a link from mql5.com, where you can get all the information for free, how you can read your data yourself and what the individual odds mean.

Advanced Analysis of a Trading Account

https://www.mql5.com/en/articles/1383

On this side, you can also change the language!

You should definitely deal with these data, numbers and facts, because this evaluation shows you the truth every day. With the Expected Payoff you can extrapolate future earnings. When you reach an expected payoff of $ 14, you know that after 20 trades a day, you made $ 280. After deducting taxes, $ 200 net remains. With 20 trading days, that's $ 4,000 in net income.

In addition, I recommend that you use 2 accounts with your broker. I have an MT5 account where I can park my funds and transfer them to my MT4 account within seconds if necessary. If a kind of franc shock occurs in EURUSD during these times, as a professional trader with a leverage of 1: 400, I am only liable with my account deposit and cannot suffer any losses beyond that. So if I only trade with 10 lots, I can park my unnecessary money in the MT5 and thus secure my remaining trading account.

Conclusion:

A high win rate is initially no guarantee of winnings, the overall evaluation is always decisive. Overall, the result is positive, but with the identification of the algorithms I will be able to run the trades longer. With this strategy it is possible to identify the decisive smaller breakouts even faster and at the same time to recognize the stop zones of the retail traders with the key candle. Then you have a possible goal up to which the big players push the price. You can then let the trade run longer. Starting a Stophunting is also an interesting movement that is quick and effective. Returns are very rare here and you can act with small stops. My goal is to increase the expected payoff in a healthy ratio while maintaining the same risk. My current risk is 0.1% per trade and could be increased to 1.5% with 20 lots. The drawdown should also be in a healthy area.

This results in different strategies, which I will try out this year. The goal is to develop a strategy that enables an optimal risk-reward ratio. It is nice to win 8 out of 10 trades, but if I drastically increase the expected payoff with a 60% chance of winning without worsening my risk, I will take this path. However, this will depend on which new strategies result from the identification of the algorithms. A decisive factor for me is the net profit per minute in relation to the profit factor, the higher this value, the shorter I am in the market. The shorter I am in the market, the more opportunities there are for further trades. The algorithms are therefore a good tool for executing high-profit trades in very short-term sequences. With this information, I am able to clearly predict the future for a few seconds. So far it was 30 seconds that I correctly predicted in over 80% of the cases.

As soon as the optimal strategy and setup have been found, it is all about concrete entry and exit criteria. The number of lots can then be increased according to the risk structure. So there is an exciting time ahead of us, I believe that the identification of the algorithms is the right way to take a little profit from the big players. As long as only a few manage to do this, the big players will not notice anything and will stick to their strategies, some of which are easy to understand. A very high probability of winning can currently be achieved if the big players provide themselves with liquidity. I hope that the big players will push this strategy even further. Algorithms have a decisive advantage, they are not reprogrammed every day, so they are a reliable indicator for those who have decrypted them. The big players will only change their algorithms if their winnings change drastically. I'm looking forward to our new project: Big Player Algorithms.

I wish you a nice Sunday

best regards
Michael

Hallo Michael.thanks for your great work.tell us about your equipment-CPU,RAM...

Workstation equipment

Hello hefer,

First of all, thank you for your kind compliment. I work with 2 Dell workstations, each with a processing speed of an Intel Core i9-9900K. Ram is 64 GB and two Samsung SSDs also ensure fast data conversion. One Dell workstation operates 5 screens, which I use special software that filters stock market data according to my specifications, the second workstation operates 3 screens with the data from the Forex market. I use additional a ventilation on my CPU to keep the heat below 60 degrees at full load. As graphics cards I use Nvidia GeForce to support the up to 55 inch 4K screens. Internet access runs over a fast fiber optic cable to reduce ping times. However, you don't need such equipment at the beginning, a PC with two or three screens is sufficient. Since I use my setup to decode highly complex algorithms, to program, write on my blog and also use the Internet, I need a little more screen space. However, this is only recommended if you can afford this purchase from your profits. 8 screens can confuse a beginner more than helping him. I only get information on my screens about a single currency pair, the EURUSD in the Forex and Future markets. The advantage is only in the area of time, because I can display all decisive chart views without having to switch constantly. It is a luxury that is not absolutely necessary, but the different information has often saved me from extreme losses. Since I sit in front of these screens for 10-12 hours a day, I also want to feel comfortable in my workplace. And that is a crucial point for me to be successful as a trader.

I wish you a nice weekend

best regards
Michael

Big player algorithms


Hello dear subscribers,

Tomorrow we will start with our 11th project: The Big Player Algorithms. At first glance, the topic appears to be very complicated and opaque. The opposite is true, however, as 100% of the time most big players only use algorithms to 11%. First and foremost to hide the number of their orders. The big player has only two options in the market, he can move the market in his direction with market orders or he can stop the market with his limit orders. In both cases, standardized algorithms are used that are relatively easy to identify. The algorithms are relatively complex to program, which is why they are not updated regularly. This gives us a certain level of security and consistency in the identification of the algorithms.

How can we benefit from the identification of big player algorithms?

First of all, we are able to differentiate whether the big players with their limit orders absorb the market orders in order to collect a certain number of ask or bid. Or whether they use market orders to push the market in their direction to bring their previously collected limit orders to profit. The algorithms also help us to find out whether they are buying dollars or selling the euro and whether they are selling the dollar or buying the euro. This is crucial information because a bearish candle is created when you buy the dollar or sell the euro.

When the dollar is bought, a bearish candle is often the starting point for further bearish candles. If the euro is sold, it means that the big player is getting out of its long position. At this moment, he hasn't had a chance to pick up the dollar yet, so you might be less likely to expect a stronger downward move, but would have to assume a sideways move first. However, this always depends on the different information that we receive from the stock market data. The stock market is all about information and the more correct information we have that fits into an overall picture, the higher our probability of winning. And that's exactly what our next project will be about.

I wish you a successful start to trading tomorrow.

best regards
Michael