General questions
Trading Hero portfolios are sets of trading robots that trade different strategies and currency pairs 24 hours a day, 5 days a week.
The approach of distributing investments across different trading assets allows you to diversify your risks and not depend on one currency pair.
The approach of distributing investments across different trading assets allows you to diversify your risks and not depend on one currency pair.
Robots trade on AUD/NZD, AUD/CAD, AUD/USD, GBP/CAD, GBP/USD, EUR/GBP, NZD/CAD, and USD/CAD currency pairs.
It is for these instruments that we managed to find the most effective parameters that allow portfolios to receive annual profits (according to testing on historical quotes for 16 years).
It is for these instruments that we managed to find the most effective parameters that allow portfolios to receive annual profits (according to testing on historical quotes for 16 years).
Trading is fully automated, which excludes the influence of the "human factor" and the assumption of trading errors as a result of a subjective assessment of the market situation.
In addition, robots do not sleep, do not get sick, do not have fear, do not show greed, do not get tired, do not miss trades, and fully adhere to the trading strategy.
In addition, robots do not sleep, do not get sick, do not have fear, do not show greed, do not get tired, do not miss trades, and fully adhere to the trading strategy.
The strategy is based on one of the basic properties of the market: price correction (return to previous levels) after a unidirectional impulse or trend wave.
With local impulses or intra-week trend movements, the balance of buyers or sellers changes, and at a certain moment the market becomes "overbought" or "oversold".
If the market drops by a certain number of points, the robot opens buy deals because the current price is more profitable than the previous one, and the likelihood that intraday traders will buy more actively increases.
This approach works in intraday and intraweek trading, but sometimes chains of trades can be active in the market for a couple of weeks.
If the price moves in the direction of an open deal, the robot closes it with a profit; if it goes against it, it averages the position, opening new deals at a better price in order to close them with a profit or, in rare cases of non-corrective movements, at a stop loss.
With local impulses or intra-week trend movements, the balance of buyers or sellers changes, and at a certain moment the market becomes "overbought" or "oversold".
If the market drops by a certain number of points, the robot opens buy deals because the current price is more profitable than the previous one, and the likelihood that intraday traders will buy more actively increases.
This approach works in intraday and intraweek trading, but sometimes chains of trades can be active in the market for a couple of weeks.
If the price moves in the direction of an open deal, the robot closes it with a profit; if it goes against it, it averages the position, opening new deals at a better price in order to close them with a profit or, in rare cases of non-corrective movements, at a stop loss.
This is one of the money management methods that provides for the fractional opening of a position.
For example, you can immediately invest $1000, or you can divide this investment into 10 parts of $100 or into 5 parts of $50, $100, $150, $250, and $450.
In this case, you start trading with a minimum volume and gradually gain a position if the market goes against you.
In this way, your biggest investments will be made at the most favorable prices, and when the market turns, you will quickly cover the losses of the first trades and bring the overall position into profit.
Considering that the currency markets have a corridor nature without strong trends, unlike the stock or cryptocurrency markets, this strategy can be used to trade both for buying and selling equally effectively and safely.
Keep in mind that when the risk limit of $1000 is reached, you will have to close all positions with a stop loss.
If you use one strategy, then the risk in this case will be 100%.
But if you use 10 strategies, the risk for each is reduced to 10%; if you use 50 strategies, the risk is up to 2%, which is comparable to classical money management.
Therefore, the averaging method works effectively over a long distance only if a stop loss is used and as part of a portfolio of different robots that trade on different currency pairs and timeframes.
For example, you can immediately invest $1000, or you can divide this investment into 10 parts of $100 or into 5 parts of $50, $100, $150, $250, and $450.
In this case, you start trading with a minimum volume and gradually gain a position if the market goes against you.
In this way, your biggest investments will be made at the most favorable prices, and when the market turns, you will quickly cover the losses of the first trades and bring the overall position into profit.
Considering that the currency markets have a corridor nature without strong trends, unlike the stock or cryptocurrency markets, this strategy can be used to trade both for buying and selling equally effectively and safely.
Keep in mind that when the risk limit of $1000 is reached, you will have to close all positions with a stop loss.
If you use one strategy, then the risk in this case will be 100%.
But if you use 10 strategies, the risk for each is reduced to 10%; if you use 50 strategies, the risk is up to 2%, which is comparable to classical money management.
Therefore, the averaging method works effectively over a long distance only if a stop loss is used and as part of a portfolio of different robots that trade on different currency pairs and timeframes.
The main advantage of our robots over classical averaging strategies is that the distance between orders changes dynamically, depending on market volatility.
That is, if the market is growing impulsively, the grid of orders can stretch to enter the market at a better price and gain a position more moderately.
The second advantage is that we use different distances between orders and are not tied to price marks; we analyze the percentage price change.
This allows you to get stable results in different years, even if the asset has changed in value by 30–50%.
The third advantage is that the multipliers in different robots are different, from 1.4 to 2.2, which makes it possible for the more conservative robots to stay in the market longer with a moderate load on capital and for the more aggressive robots to close positions faster due to the high multiplier and not stretch the grid.
The fourth advantage is that robots trade on different currency pairs at the same time, reducing the burden on capital.
Also, the use of several robots allows you to use stop-loss and severely limit risks, while many classic grids risk all capital.
That is, if the market is growing impulsively, the grid of orders can stretch to enter the market at a better price and gain a position more moderately.
The second advantage is that we use different distances between orders and are not tied to price marks; we analyze the percentage price change.
This allows you to get stable results in different years, even if the asset has changed in value by 30–50%.
The third advantage is that the multipliers in different robots are different, from 1.4 to 2.2, which makes it possible for the more conservative robots to stay in the market longer with a moderate load on capital and for the more aggressive robots to close positions faster due to the high multiplier and not stretch the grid.
The fourth advantage is that robots trade on different currency pairs at the same time, reducing the burden on capital.
Also, the use of several robots allows you to use stop-loss and severely limit risks, while many classic grids risk all capital.
Yes, the system has parameters for automatically closing the chain of trades with profit or loss at certain levels.
They are in hidden mode; that is, they are stored in the robot itself and not set as orders in the terminal.
As soon as the robot reaches the specified values, it closes the deal on the market.
The size of the stop loss for the robot is equal to its share in the portfolio.
Thus, the more robots in the portfolio, the smaller the stop-loss share for the total capital.
For example, in a portfolio with 10 robots, the risk per robot will be 100% /10 = 10%, and in a portfolio with 20 robots, it will be 100% /20 = 5%, that is, half as much.
In large portfolios with 50 robots, the risk per robot is 2%.
They are in hidden mode; that is, they are stored in the robot itself and not set as orders in the terminal.
As soon as the robot reaches the specified values, it closes the deal on the market.
The size of the stop loss for the robot is equal to its share in the portfolio.
Thus, the more robots in the portfolio, the smaller the stop-loss share for the total capital.
For example, in a portfolio with 10 robots, the risk per robot will be 100% /10 = 10%, and in a portfolio with 20 robots, it will be 100% /20 = 5%, that is, half as much.
In large portfolios with 50 robots, the risk per robot is 2%.
Locking is the opening of an opposite order of the same volume if the initial trade is at a floating loss.
No, the system does not use "locks" in trading.
We do not freeze floating losses in the hope of getting out of them someday.
In this case, there is a stop-loss.
No, the system does not use "locks" in trading.
We do not freeze floating losses in the hope of getting out of them someday.
In this case, there is a stop-loss.
Macroeconomic statistics are not taken into account since local waves of growth and decline within the day and week, regardless of the presence of a trend.
Therefore, robots have the same chances of earning in the presence of both a trend and a corridor market movement.
If the market moves in the direction of the deal after the news is published, the robot will close the deal with a profit.
If not, it will average positions until the chain of trades is closed with a profit or a stop loss is received.
Since it is impossible to predict the direction and strength of the movement in advance, and sometimes the market grows on negative news or decreases on positive news, the robot trades according to the technical situation on the currency pair.
All tests of robots were carried out ignoring macroeconomic statistics.
That is, robots traded during the changing cycles of raising and lowering interest rates, record high inflation, and low GDP in different countries and proved their effectiveness.
Therefore, robots have the same chances of earning in the presence of both a trend and a corridor market movement.
If the market moves in the direction of the deal after the news is published, the robot will close the deal with a profit.
If not, it will average positions until the chain of trades is closed with a profit or a stop loss is received.
Since it is impossible to predict the direction and strength of the movement in advance, and sometimes the market grows on negative news or decreases on positive news, the robot trades according to the technical situation on the currency pair.
All tests of robots were carried out ignoring macroeconomic statistics.
That is, robots traded during the changing cycles of raising and lowering interest rates, record high inflation, and low GDP in different countries and proved their effectiveness.
There are several scenarios for stopping trading:
1. Seasonal: from December 16, robots switch to the mode of closing deals and close only already open chains; new ones do not start.
Trading resumes on January 5th. This is due to increased volatility during the New Year's holidays.
Historically, there have been more losses than profits during these periods.
2. Planned global economic events—for example, Brexit in 2016 with a known voting date.
At the same time, trading on all pairs with the GBP stopped one week before the event and resumed a week after the vote.
3. Force majeure events: the beginning of a full-scale war between Russia and Ukraine in February 2022; in this case, trade stopped for a month.
4. Emergence of extreme volatility: situations when a currency pair deviates from the average daily volatility five or more times per day (trading was stopped from March 3 to April 20, 2020, during the spread of the COVID-19 pandemic).
Also, trades were not held from October 7 to November 1, 2008, at the height of the global financial crisis.
Important: in such cases, transactions can be closed with the current result, even negative, to ensure the safety of the entire deposit.
Trading resumes on January 5th. This is due to increased volatility during the New Year's holidays.
Historically, there have been more losses than profits during these periods.
2. Planned global economic events—for example, Brexit in 2016 with a known voting date.
At the same time, trading on all pairs with the GBP stopped one week before the event and resumed a week after the vote.
3. Force majeure events: the beginning of a full-scale war between Russia and Ukraine in February 2022; in this case, trade stopped for a month.
4. Emergence of extreme volatility: situations when a currency pair deviates from the average daily volatility five or more times per day (trading was stopped from March 3 to April 20, 2020, during the spread of the COVID-19 pandemic).
Also, trades were not held from October 7 to November 1, 2008, at the height of the global financial crisis.
Important: in such cases, transactions can be closed with the current result, even negative, to ensure the safety of the entire deposit.
Yes, you can view the monitoring accounts of different portfolios on the MyFxBook
Different portfolios were launched at different times, and robots received more stop-loss in some portfolios than in others.
Since we do not know in advance which of the robots will receive Stop losses when, it makes sense to invest in as many robots as possible in order to reduce the share and risk for each individual strategy in the portfolio.
Since we do not know in advance which of the robots will receive Stop losses when, it makes sense to invest in as many robots as possible in order to reduce the share and risk for each individual strategy in the portfolio.
Testing strategies and creating portfolios
All portfolios have been tested on 16 years of historical quotes and show profitability every year since 2008
Individual robots in portfolios may have had unprofitable years in the past, but their losses are covered by the profits of other robots.
Individual robots in portfolios may have had unprofitable years in the past, but their losses are covered by the profits of other robots.
To test strategies, we use our own software that downloads tick quotes from one of the major investment banks and converts their format for testing in MetaTrader.
This allows you to achieve maximum accuracy in the simulation by using several million ticks (minimum price changes) per year.
By comparison, the standard quotes available in MetaTrader contain no more than a few hundred thousand ticks.
Because of this, the Strategy Tester artificially creates ticks based on the Open, High, Low, and close parameters of the minimum available timeframe.
This reduces the accuracy of the results and, as a rule, leads to the fact that in tests on history, the results can be positive, but in real trading, they are negative.
In our case, the coincidence between the results of historical tests and actual traded accounts is about 90%.
A 100% match cannot be achieved due to differences in quotes between different brokers as well as spread widening and slippage in the execution of transactions on real accounts, which cannot be simulated.
This allows you to achieve maximum accuracy in the simulation by using several million ticks (minimum price changes) per year.
By comparison, the standard quotes available in MetaTrader contain no more than a few hundred thousand ticks.
Because of this, the Strategy Tester artificially creates ticks based on the Open, High, Low, and close parameters of the minimum available timeframe.
This reduces the accuracy of the results and, as a rule, leads to the fact that in tests on history, the results can be positive, but in real trading, they are negative.
In our case, the coincidence between the results of historical tests and actual traded accounts is about 90%.
A 100% match cannot be achieved due to differences in quotes between different brokers as well as spread widening and slippage in the execution of transactions on real accounts, which cannot be simulated.
Profitability and risks of portfolios
The maximum profitability of portfolios with a x1 multiplier was achieved in 2009 and amounted to 100–150%, depending on the portfolio.
The average annual profitability is 70%.
In portfolios starting at $100,000, we can use the multiplier of x1,5 / x2; since the risks for each robot are small, this allows us to double the profitability.
The average annual profitability is 70%.
In portfolios starting at $100,000, we can use the multiplier of x1,5 / x2; since the risks for each robot are small, this allows us to double the profitability.
The maximum risk depends on the number of robots in the portfolio; the more there are, the lower it is.
For example, for a portfolio of 5,000, the maximum drawdown, taking into account open and closed positions, was 42% in 2008.
Despite this, the portfolio returned 114% that year.
This is the maximum drawdown of all portfolios, which we recorded with a multiplier of 1 on tests over 16 years.
The average annual drawdown is 24% of the capital.
Theoretically, the drawdown can be greater than the historical maximum if an event occurs on the market that exceeds 2008 in terms of volatility.
But over the past 16 years, neither the COVID-19 pandemic nor other events have approached the magnitude of the 2008 crisis.
Therefore, the probability of exceeding or even reaching the maximum historical drawdown is low.
In any case, we recommend that you use only risk capital in stock trading.
If you use a multiplier in trading—increase trading lots by x1,5 / x2 or more times—your maximum risk can be 100%, and to maintain the margin level, you must have a margin of funds to add to the account and cover the risk of closing positions due to a lack of funds (Margin Call).
For example, for a portfolio of 5,000, the maximum drawdown, taking into account open and closed positions, was 42% in 2008.
Despite this, the portfolio returned 114% that year.
This is the maximum drawdown of all portfolios, which we recorded with a multiplier of 1 on tests over 16 years.
The average annual drawdown is 24% of the capital.
Theoretically, the drawdown can be greater than the historical maximum if an event occurs on the market that exceeds 2008 in terms of volatility.
But over the past 16 years, neither the COVID-19 pandemic nor other events have approached the magnitude of the 2008 crisis.
Therefore, the probability of exceeding or even reaching the maximum historical drawdown is low.
In any case, we recommend that you use only risk capital in stock trading.
If you use a multiplier in trading—increase trading lots by x1,5 / x2 or more times—your maximum risk can be 100%, and to maintain the margin level, you must have a margin of funds to add to the account and cover the risk of closing positions due to a lack of funds (Margin Call).
The risk depends on the multiplier and the number of robots in the portfolio.
The more capital, the more robots in the portfolio, and the less load on each robot.
For example, if you have a portfolio of $5,000 and 7 robots, the average risk per robot would be $5,000/7 = $715, i.e., 14.3%.
If you use a portfolio of $20,000 with 18 robots, your risk will be $1111 per robot, but in terms of capital, it will be 5.6%.
Thus, in large portfolios, the risk per robot in dollars will increase, but in percentage it will decrease.
In other words, 1 portfolio of $20,000 is safer than 4 portfolios of $5,000, since the risk per bot is lower.
But sometimes reverse situations happen, when one of the robots can get a stop loss in a portfolio of $20,000 but is not present in a portfolio of $5,000.
Then a portfolio of $5,000 will be more profitable than a portfolio of $20,000 at the moment.
But if we consider the long-term perspective, then a $20,000 portfolio will be more reliable and recover a drawdown faster since its risk per robot is almost three times lower.
The more capital, the more robots in the portfolio, and the less load on each robot.
For example, if you have a portfolio of $5,000 and 7 robots, the average risk per robot would be $5,000/7 = $715, i.e., 14.3%.
If you use a portfolio of $20,000 with 18 robots, your risk will be $1111 per robot, but in terms of capital, it will be 5.6%.
Thus, in large portfolios, the risk per robot in dollars will increase, but in percentage it will decrease.
In other words, 1 portfolio of $20,000 is safer than 4 portfolios of $5,000, since the risk per bot is lower.
But sometimes reverse situations happen, when one of the robots can get a stop loss in a portfolio of $20,000 but is not present in a portfolio of $5,000.
Then a portfolio of $5,000 will be more profitable than a portfolio of $20,000 at the moment.
But if we consider the long-term perspective, then a $20,000 portfolio will be more reliable and recover a drawdown faster since its risk per robot is almost three times lower.
Movement of funds and payment for services
Yes, you can withdraw funds at any time; they are in your account and under your full control.
If you would like to withdraw funds, please notify us in advance so that we can put the robots into trade closing mode and correctly stop trading without incurring unplanned losses.
If you plan to withdraw part of the capital, also notify us, and we will change the number of robots in your portfolio so that it corresponds to the current capital and does not increase the risks.
If you would like to withdraw funds, please notify us in advance so that we can put the robots into trade closing mode and correctly stop trading without incurring unplanned losses.
If you plan to withdraw part of the capital, also notify us, and we will change the number of robots in your portfolio so that it corresponds to the current capital and does not increase the risks.
Yes, you can add funds at any time.
Let us know when the funds are in the account, and we will add new robots to increase the profitability of your portfolio.
Let us know when the funds are in the account, and we will add new robots to increase the profitability of your portfolio.
Yes, we charge a certain percentage of the profits we bring to you.
The calculation takes place once a month, based on the results of trading.
There are no prepayments.
You can find details on the conditions for each portfolio in your personal account https://tradinghero.org/profile/portfolio/
The calculation takes place once a month, based on the results of trading.
There are no prepayments.
You can find details on the conditions for each portfolio in your personal account https://tradinghero.org/profile/portfolio/
Upon receiving a loss for the settlement period, we first restore the capital with the help of the robots to the previous level without charging a commission, after which we continue the calculations in the standard manner.
Until the losses are fully recovered, the commission is not charged.
Until the losses are fully recovered, the commission is not charged.
After the end of the settlement period, you will receive an email with the trading result and the amount to be transferred to the specified crypto wallet.
After making the payment, you need to send a screenshot with the payment by return letter, Telegram, or WhatsApp to your personal manager.
After making the payment, you need to send a screenshot with the payment by return letter, Telegram, or WhatsApp to your personal manager.
Affiliate program
Yes, you can get 20% of our earnings from direct referral clients.
You can open an affiliate account with your broker and receive commissions from transactions that our robots make on the account of the client you referred.
On average, robots spend on spreads 15–25% of the base capital per year; if your broker pays you 50% of the spreads, you can earn an additional 7.5%–12.5% per year.
If your client trades with a x2 multiplier, this will be 15–25% guaranteed income per year from the capital of the attracted client.
On average, robots spend on spreads 15–25% of the base capital per year; if your broker pays you 50% of the spreads, you can earn an additional 7.5%–12.5% per year.
If your client trades with a x2 multiplier, this will be 15–25% guaranteed income per year from the capital of the attracted client.