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תוכן מסופק על ידי Raimund Bauer. כל תוכן הפודקאסטים כולל פרקים, גרפיקה ותיאורי פודקאסטים מועלים ומסופקים ישירות על ידי Raimund Bauer או שותף פלטפורמת הפודקאסט שלהם. אם אתה מאמין שמישהו משתמש ביצירה שלך המוגנת בזכויות יוצרים ללא רשותך, אתה יכול לעקוב אחר התהליך המתואר כאן https://he.player.fm/legal.
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MQL5 TUTORIAL – HOW TO TRAIN AND SCALE A WORKING REAL WORLD TRADING SYSTEM

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Manage episode 380466663 series 1376757
תוכן מסופק על ידי Raimund Bauer. כל תוכן הפודקאסטים כולל פרקים, גרפיקה ותיאורי פודקאסטים מועלים ומסופקים ישירות על ידי Raimund Bauer או שותף פלטפורמת הפודקאסט שלהם. אם אתה מאמין שמישהו משתמש ביצירה שלך המוגנת בזכויות יוצרים ללא רשותך, אתה יכול לעקוב אחר התהליך המתואר כאן https://he.player.fm/legal.
MQL5 TUTORIAL – HOW TO TRAIN AND SCALE A WORKING REAL WORLD TRADING SYSTEM

  1. Introduction to Real World Trading System (00:00 – 00:14)
    • Introduction to the robot trading system used by the presenter.
    • Overview of the system’s performance and purpose.
  2. Analyzing Trading System Performance (00:14 – 00:29)
    • Detailed look at the trading system’s results and trades.
    • Discussion on the balance and equity of the system.
  3. Understanding Trade Impact and Emotions (00:29 – 01:06)
    • Exploring the emotional impact of trade results.
    • Difference between small and large losses.
  4. Trade History Analysis (01:06 – 01:20)
    • Examination of the system’s trade history, including profits and losses.
  5. System Strategy and Position Series (01:20 – 01:39)
    • Description of the trading strategy using position series.
    • Explanation of closing positions at once.
  6. Decision Making in Trading (01:39 – 02:14)
    • Criteria for deciding between single or multiple positions.
    • Rules-based approach to trading decisions.
  7. Trend Analysis with Moving Averages (02:14 – 02:31)
    • Using simple moving averages to identify market trends.
    • Explanation of downtrend indicators.
  8. Trading With and Against Trends (02:31 – 02:58)
    • Strategies for trading with the trend and handling corrections.
    • Examples of trades that didn’t work out and why.
  9. Analyzing Correction Phases and Trends (02:58 – 03:29)
    • Understanding correction phases in stable trends.
    • Strategies for closing positions profitably.
  10. Future Decision Making in Trading (03:29 – 03:47)
    • Challenges in predicting future market movements.
    • Importance of decision making in trading.
  11. Using FXBlue for Detailed Statistics (03:47 – 04:17)
    • Utilizing FXBlue for better trading statistics.
    • Accessing detailed system performance data.
  12. System Performance and Statistics Overview (04:17 – 04:53)
    • Comprehensive review of the trading system’s performance.
    • Analysis of winners, losers, and total trades.
  13. Trade Analysis and Currency Focus (04:53 – 05:10)
    • Breakdown of trade types and currency pairs used.
    • Emphasis on trading in a downtrend.
  14. Scaling Up the Trading System (05:10 – 05:28)
    • Considering increasing the trading volume.
    • Evaluating the system’s readiness for scaling.
  15. Average Trade Duration and Profitability (05:28 – 06:05)
    • Analysis of average trade duration and profitability.
    • Importance of balancing profitable trades with losses.
  16. Understanding Trading Costs and Spreads (06:05 – 06:36)
    • Discussion on swap fees and spread costs in trading.
    • Impact of broker charges on trading profitability.
  17. Market Trend Analysis and Moving Averages (06:36 – 07:04)
    • Using moving averages to analyze market trends.
    • Indicators of trend changes and their implications.
  18. Automating Trading Logic with MQL5 (07:04 – 07:33)
    • Simplifying trading decisions through automation.
    • Using MQL5 for implementing trading strategies.
  19. Backtesting and Real-Time Testing (07:33 – 08:04)
    • Importance of backtesting and real-time demo account testing.
    • Evaluating system performance in different market phases.
  20. Scaling Up and Risk Management (08:04 – 08:21)
    • Strategies for scaling up the trading system.
    • Adjusting risk percentage and position size.
  21. Training and Analyzing Trading Systems (08:21 – 08:51)
    • Training a system for real-world conditions.
    • Using external tools for performance analysis.
  22. Conclusion and Future Plans (08:51 – 09:22)
    • Summary of the video and insights on scaling up the system.
    • Invitation to analyze detailed stats on the website.

In this video we are going to talk about one of my real world examples. This is the robot trading system which actually use myself and one of my premium course members wanted to know how something like this works. So let’s have a look at the details. Well, if you have a look at the robot trading system, you can see this is Version 2023 from June. Right now we have the 20 first of October and here we have results and trades all in all we made a profit of 159 dollars and if we look at the overall view here we see that the balance currently is almost equal to the equity which means we only one open trade that is currently and open loss of 99 cents. So what is actually the difference between this trade and one that would be an open loss of 99 dollars? The difference is emotional because it’s not actually the number here that counts if a system is working or not, it’s what the difference means for us. So let’s have a look at the history and here we see that we have losses and we have profits, so not every trade was a success, but all in all the system result is stable, at least right now. If we zoom into the system, we can see these lines here which look like a fan and each of those is a series of positions that we have opened. And at this point here all positions have been closed at once. Let’s zoom in a little more and you will also see parts where we don’t see a fan, for example like here. And these are simple positions that made a profit without the need to start a series. So how do we decide if we just take one position or if we want to open multiple positions? Well in my case I have rules. And currently we are in a down trend, and we can see that because we have two simple moving averages here is for 1100 candles and the other one is for a thousand candles. And a long as the green one is below the red one, we have a downtrend and that looks pretty stable right now. And you can see that the last trades that we made have been sell trades, so we have been trading with the trend. But still we have some positions that didn’t work out. How was that possible? Well that’s because even in a stable trend we have some corrections. That’s when we open a position like here and then suddenly in a correction the price goes up. And if you take a closer look, this is the case for all these fans here. The price went down, than we made a trade here. Suddenly a correction happened and it went against us. But actually we have been able to still close all the positions from here to there in a profit at this point here. Because finally the short time trend again started to go with the main trend and the price went down. While it is easy to see what happened after it happened, it’s often a big problem for people to make a decision what they should do in the future! Well this this is the account number here. So let’s see if we can get more statistics about what happened. And I’m using FXBlue for this, because it providers better statistics than we get from the MetaTrader. In my case it’s in German because I’m from Germany. You can get a lot of details about how the system works. And you don’t have to log in to see them, just open this website here.

And in my case I want to open the stats. There we are, I have started the system 128 days ago with the deposit of 10.000 Dollars. This is the total profit, here we have some withdrawals and this is the net profit. We have winners and losers and all in all we made 382 trades and that resulted in a net profit of 153 Dollars. In a graph chart it looks like this here. We have some more statistics. The Euro US Dollar was the only currency that I used to trade. We have 73 buy trades and 309 sell trades. And that makes sense because currently we have that downtrend here. And if we take a closer look, we had 14 winning weeks and zero losing weeks and a that point, it might make sense to turn up the volume and to scale up the system. Now, let’s go back to the statement here and somewhere down here it says the average trade duration is 33 hours and the average profit is $ 1,78, while the average loss is $ 2.16. So if we are able to make more profitable trades than we make loses, the system is going to be profitable. But this is only true, if we not have to high costs. We have this swap collumn here and for longer trade durations you can expect that you need to pay swap fees, like here. These are costs and the other thing is that when you open a position here you might always see a little loss, because of the social spread. Your broker is charging money, so whenever you open a position like I did here, the first thing that you will see is that the profit is negative. And that the price where you bought or sold something is different from what you see on the chart, because that is how your broker makes money with every trade that you make. Now let’s change the zoom level here and we see that currently it looks like the current price is getting near to the small average price here and when the price level crosses the two small moving averages here, that would mean that the stable trend is broken. And when the two small moving averages cross, this could mean that the trend is broken and the next thing that we would expect to see is an up trend. Which is what happened here.

The trend was broken, here is the cross over and here is the up trend. Then we had another cross over here and now it’s a down trend. So the logic behind all these decisions here is pretty simple and it can be automated by using MQL5. So basically, there is nothing magical behind it. It’s all pure probability and to make up rules about when to do what, we do a lot of back tasting and that means we do thousands of automated trades with data from the past to see how our system would have behaved in other market phases. Then we tried on a demo account in real time. Then we scale up or system to see if it actually works. And once everything is working as expected, you can press the F7 button and increase risk percentage, or the multiplier for the positionsize. And if you do, but you would have bigger positions and more positions and that’s how we scale up. That was basically how we setup a probability based trading system that works under real conditions. And in this video you have learned how to train your own system to work under real conditions and how you can use external tools like a FXBLUE to analyze if it actually works. If you are interested to see more details you can just go to this website and analyse all the stats. This system is still in the training stage, but so far the results have been very promising, so think I’m going to scale it up.

That’s it for this video. I say thank you for watching and I will see you in the next one.

The post MQL5 TUTORIAL – HOW TO TRAIN AND SCALE A WORKING REAL WORLD TRADING SYSTEM appeared first on MQL5 Tutorial.

  continue reading

27 פרקים

Artwork
iconשתפו
 
Manage episode 380466663 series 1376757
תוכן מסופק על ידי Raimund Bauer. כל תוכן הפודקאסטים כולל פרקים, גרפיקה ותיאורי פודקאסטים מועלים ומסופקים ישירות על ידי Raimund Bauer או שותף פלטפורמת הפודקאסט שלהם. אם אתה מאמין שמישהו משתמש ביצירה שלך המוגנת בזכויות יוצרים ללא רשותך, אתה יכול לעקוב אחר התהליך המתואר כאן https://he.player.fm/legal.
MQL5 TUTORIAL – HOW TO TRAIN AND SCALE A WORKING REAL WORLD TRADING SYSTEM

  1. Introduction to Real World Trading System (00:00 – 00:14)
    • Introduction to the robot trading system used by the presenter.
    • Overview of the system’s performance and purpose.
  2. Analyzing Trading System Performance (00:14 – 00:29)
    • Detailed look at the trading system’s results and trades.
    • Discussion on the balance and equity of the system.
  3. Understanding Trade Impact and Emotions (00:29 – 01:06)
    • Exploring the emotional impact of trade results.
    • Difference between small and large losses.
  4. Trade History Analysis (01:06 – 01:20)
    • Examination of the system’s trade history, including profits and losses.
  5. System Strategy and Position Series (01:20 – 01:39)
    • Description of the trading strategy using position series.
    • Explanation of closing positions at once.
  6. Decision Making in Trading (01:39 – 02:14)
    • Criteria for deciding between single or multiple positions.
    • Rules-based approach to trading decisions.
  7. Trend Analysis with Moving Averages (02:14 – 02:31)
    • Using simple moving averages to identify market trends.
    • Explanation of downtrend indicators.
  8. Trading With and Against Trends (02:31 – 02:58)
    • Strategies for trading with the trend and handling corrections.
    • Examples of trades that didn’t work out and why.
  9. Analyzing Correction Phases and Trends (02:58 – 03:29)
    • Understanding correction phases in stable trends.
    • Strategies for closing positions profitably.
  10. Future Decision Making in Trading (03:29 – 03:47)
    • Challenges in predicting future market movements.
    • Importance of decision making in trading.
  11. Using FXBlue for Detailed Statistics (03:47 – 04:17)
    • Utilizing FXBlue for better trading statistics.
    • Accessing detailed system performance data.
  12. System Performance and Statistics Overview (04:17 – 04:53)
    • Comprehensive review of the trading system’s performance.
    • Analysis of winners, losers, and total trades.
  13. Trade Analysis and Currency Focus (04:53 – 05:10)
    • Breakdown of trade types and currency pairs used.
    • Emphasis on trading in a downtrend.
  14. Scaling Up the Trading System (05:10 – 05:28)
    • Considering increasing the trading volume.
    • Evaluating the system’s readiness for scaling.
  15. Average Trade Duration and Profitability (05:28 – 06:05)
    • Analysis of average trade duration and profitability.
    • Importance of balancing profitable trades with losses.
  16. Understanding Trading Costs and Spreads (06:05 – 06:36)
    • Discussion on swap fees and spread costs in trading.
    • Impact of broker charges on trading profitability.
  17. Market Trend Analysis and Moving Averages (06:36 – 07:04)
    • Using moving averages to analyze market trends.
    • Indicators of trend changes and their implications.
  18. Automating Trading Logic with MQL5 (07:04 – 07:33)
    • Simplifying trading decisions through automation.
    • Using MQL5 for implementing trading strategies.
  19. Backtesting and Real-Time Testing (07:33 – 08:04)
    • Importance of backtesting and real-time demo account testing.
    • Evaluating system performance in different market phases.
  20. Scaling Up and Risk Management (08:04 – 08:21)
    • Strategies for scaling up the trading system.
    • Adjusting risk percentage and position size.
  21. Training and Analyzing Trading Systems (08:21 – 08:51)
    • Training a system for real-world conditions.
    • Using external tools for performance analysis.
  22. Conclusion and Future Plans (08:51 – 09:22)
    • Summary of the video and insights on scaling up the system.
    • Invitation to analyze detailed stats on the website.

In this video we are going to talk about one of my real world examples. This is the robot trading system which actually use myself and one of my premium course members wanted to know how something like this works. So let’s have a look at the details. Well, if you have a look at the robot trading system, you can see this is Version 2023 from June. Right now we have the 20 first of October and here we have results and trades all in all we made a profit of 159 dollars and if we look at the overall view here we see that the balance currently is almost equal to the equity which means we only one open trade that is currently and open loss of 99 cents. So what is actually the difference between this trade and one that would be an open loss of 99 dollars? The difference is emotional because it’s not actually the number here that counts if a system is working or not, it’s what the difference means for us. So let’s have a look at the history and here we see that we have losses and we have profits, so not every trade was a success, but all in all the system result is stable, at least right now. If we zoom into the system, we can see these lines here which look like a fan and each of those is a series of positions that we have opened. And at this point here all positions have been closed at once. Let’s zoom in a little more and you will also see parts where we don’t see a fan, for example like here. And these are simple positions that made a profit without the need to start a series. So how do we decide if we just take one position or if we want to open multiple positions? Well in my case I have rules. And currently we are in a down trend, and we can see that because we have two simple moving averages here is for 1100 candles and the other one is for a thousand candles. And a long as the green one is below the red one, we have a downtrend and that looks pretty stable right now. And you can see that the last trades that we made have been sell trades, so we have been trading with the trend. But still we have some positions that didn’t work out. How was that possible? Well that’s because even in a stable trend we have some corrections. That’s when we open a position like here and then suddenly in a correction the price goes up. And if you take a closer look, this is the case for all these fans here. The price went down, than we made a trade here. Suddenly a correction happened and it went against us. But actually we have been able to still close all the positions from here to there in a profit at this point here. Because finally the short time trend again started to go with the main trend and the price went down. While it is easy to see what happened after it happened, it’s often a big problem for people to make a decision what they should do in the future! Well this this is the account number here. So let’s see if we can get more statistics about what happened. And I’m using FXBlue for this, because it providers better statistics than we get from the MetaTrader. In my case it’s in German because I’m from Germany. You can get a lot of details about how the system works. And you don’t have to log in to see them, just open this website here.

And in my case I want to open the stats. There we are, I have started the system 128 days ago with the deposit of 10.000 Dollars. This is the total profit, here we have some withdrawals and this is the net profit. We have winners and losers and all in all we made 382 trades and that resulted in a net profit of 153 Dollars. In a graph chart it looks like this here. We have some more statistics. The Euro US Dollar was the only currency that I used to trade. We have 73 buy trades and 309 sell trades. And that makes sense because currently we have that downtrend here. And if we take a closer look, we had 14 winning weeks and zero losing weeks and a that point, it might make sense to turn up the volume and to scale up the system. Now, let’s go back to the statement here and somewhere down here it says the average trade duration is 33 hours and the average profit is $ 1,78, while the average loss is $ 2.16. So if we are able to make more profitable trades than we make loses, the system is going to be profitable. But this is only true, if we not have to high costs. We have this swap collumn here and for longer trade durations you can expect that you need to pay swap fees, like here. These are costs and the other thing is that when you open a position here you might always see a little loss, because of the social spread. Your broker is charging money, so whenever you open a position like I did here, the first thing that you will see is that the profit is negative. And that the price where you bought or sold something is different from what you see on the chart, because that is how your broker makes money with every trade that you make. Now let’s change the zoom level here and we see that currently it looks like the current price is getting near to the small average price here and when the price level crosses the two small moving averages here, that would mean that the stable trend is broken. And when the two small moving averages cross, this could mean that the trend is broken and the next thing that we would expect to see is an up trend. Which is what happened here.

The trend was broken, here is the cross over and here is the up trend. Then we had another cross over here and now it’s a down trend. So the logic behind all these decisions here is pretty simple and it can be automated by using MQL5. So basically, there is nothing magical behind it. It’s all pure probability and to make up rules about when to do what, we do a lot of back tasting and that means we do thousands of automated trades with data from the past to see how our system would have behaved in other market phases. Then we tried on a demo account in real time. Then we scale up or system to see if it actually works. And once everything is working as expected, you can press the F7 button and increase risk percentage, or the multiplier for the positionsize. And if you do, but you would have bigger positions and more positions and that’s how we scale up. That was basically how we setup a probability based trading system that works under real conditions. And in this video you have learned how to train your own system to work under real conditions and how you can use external tools like a FXBLUE to analyze if it actually works. If you are interested to see more details you can just go to this website and analyse all the stats. This system is still in the training stage, but so far the results have been very promising, so think I’m going to scale it up.

That’s it for this video. I say thank you for watching and I will see you in the next one.

The post MQL5 TUTORIAL – HOW TO TRAIN AND SCALE A WORKING REAL WORLD TRADING SYSTEM appeared first on MQL5 Tutorial.

  continue reading

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