Welcome to the first Darwinex Tutorial, explained in simple and easy-to-follow terms.

To find out more about this platform, its history, and our opinions, check out our Darwinex Review.

In this article, on the other hand, we want to show you how this platform works and its features, so you may:

  • Understand how Darwins are analysed, and what that data means, in simple terms
  • Understand how to find the best Darwins
  • Understand how to create the best Darwin portfolio, based on your needs

The best way to follow along this tutorial is by having a Darwinex account open on another tab, to better observe and interact with the platform. This can be easily done with virtual accounts as well, so register a demo account on Darwinex now (61% of retail CFD accounts lose money).

(Do you want to discover other platforms like Darwinex, for example eToro, NAGA, ZuluTrade? Check out our Top 10 of the best Social Trading networks.)

Darwinex Tutorial – Complete Darwinex Guide for beginners

I suggest you get a nice cup of tea and take all the time you need to read this post top to bottom.

However, right below you can find an index you can use to jump to the section you find most interesting.

1. How to look for Darwins: Pre-set Filters and Explore Section

1.1 – Top Invested
1.2 – Good Scores
1.3 – Return>50%
1.4 – On Fire
1.5 – Trending
1.6 – Promising
1.7 – Latest

2. All Darwins Section

2.1 – Manage Filter

3. How to analyse Darwins: Analysis Panel

3.1 – Darwinex Score: What is it and how does it work
3.2 – Sec. Return/Risk
3.3 – Sec. Asset & Timeframes
3.4 – Sec. Investable Attributes
3.5 – Sec. Divergence
3.6 – Sec. Correlation
3.7 – Sec. Underlaying Strategy

4. TUTORIAL: How to choose the best Darwins

Ready? Let’s go!

darwinex guide tutorial

Darwinex Pre-set Filters and Explore Section

The Darwinex Explore section is the first of many interesting sections we will be checking out. The purpose of this segment is to provide immediate visibility of specific Darwin categories.

This page is full of content, and it should be scrolled through, top to bottom, to better appreciate all its sections.

Here, Darwinex highlights the list of its pre-set search filters, and the Darwin who better represent each category. It’s also possible to find some training materials which, as we already mentioned in the Darwinex Review, are very well done and useful.

Darwinex offers 8 different filters:

  • Top Invested
  • Good Scores
  • Return > 50%
  • On Fire
  • Trending
  • Promising
  • Latest
  • Community

By filters, we mean the automatic methods Darwinex employs to group together Darwins who show one or more shared operating features.

Later, we’ll see the details of each category, for you to:

  1. Understand the most important operating features of the several Darwin groups
  2. Understand the categorization methods employed by Darwinex
  3. Understand which category works best for you

Clicking on the name of each filter will access the dedicated section, inside which, on the top left, the graphic layout can be modified, switching from details to frames view.

It’s also possible to sort the Darwins shown for a specific filter by several different parameters, such as investors capital, investors, returns, etc…

– Research Filter: Top invested

Darwinex research filter Top invested

In Top Invested you can find the most traded Darwins, i.e. those who have received the most investors.

The higher the number of investors (the number, not the counter value of how much has been invested) who keep a specific Darwin in their portfolio, the higher the position in this ranking. As a matter of fact, a Darwin might easily have a higher investment capital, with a lower number of investors.

At InvenstinGoal, we believe this to be a particularly useful filter to perform a professional analysis. The only element we can take advantage of is the wisdom of the crowd. Be careful however, just because something works for others doesn’t mean it will work for you too!

– Research Filter: Good scores

Darwinex research filter Good scores

Within this category, you’ll find Darwins who have a Darwinex Score (D-Score) value above 50.

As we’ll later see, the Darwinex Score is a value assigned by Darwinex (61% of retail CFD accounts lose money) to each Darwin, which analyses 11 over 12 Attributes (the Capacity is the only value not considered for this global assessment). The higher the Darwinex Score, the higher the position in this ranking.

Overall, we don’t particularly love synthetic automatic assessments, but we must admit the Attributes calculation is good.

Therefore, we believe the Good Scores can be a great filter to identify good Darwins.

– Research Filter: Return>50%

Darwinex research filter Return 50

The Return >50% is interesting only at a first glance.

Here, you can find all Darwins who have turned a profit higher than 50% since the beginning of their operations on Darwinex. Obviously, the higher the profit the higher the position in this ranking.

As we mentioned, while this data is certainly interesting, it is a bit less deserving as it doesn’t consider time. The position in this ranking doesn’t consider the number of weeks necessary to achieve this result, which is a fundamental parameter to really understand the potentiality of a Darwin. For instance, an average return, achieved in a brief amount of time could be a good sign, if however, a Darwin accomplishes exceedingly high returns in the same amount of time it might be a sign of excessive risk.

Another felt shortcoming of this filter is the absence of the Drawdown, the risk to which a capital has been exposed to obtain that result.

Therefore, we believe the Return > 50% can be interesting, but the Darwins found through this filter should still be carefully analysed.

– Research Filter: On fire

Darwinex research filter On fire

To find the “hottest” Darwins, we can use the On Fire filter, which displays those who have achieved performances with the best Risk/Return ratio over the last 3 months.

This is a great filter, unfortunately however it only considers the last 3 months, so providing for a deeper analysis would have been better.

– Research Filter: Trending

alt="Darwinex research filter Trending"

Use the Trending parameter if you want to find the 20 most popular Darwins among the investors over the last month.

This filter is strictly related to popularity, a feature which, as we explained earlier, we don’t consider to be too important, particularly in the earlier phases of the analysis.

– Research Filter: Promising

Darwinex research filter Promising

The Promising filter is interesting, as it provides visibility to investors who have shown they can be valuable traders from the start, as they have achieved interesting performances, but have not been on Darwinex long enough to be popular yet.

This filter is suitable for anyone willing to take on some more risks, adding to their portfolio Darwins which don’t have a long operating history.

– Research Filter: Latest

Darwinex research filter Latest

Latest is the last filter. Within this, you can find, sorted by performance, all new Darwins entries for the last week.

This isn’t particularly useful for investors. Its only purpose is to “introduce” the entry of new traders within the Darwinex community (61% of retail CFD accounts lose money). Even if a trader has just registered to Darwinex, it’s possible to migrate one’s own Track Record from the previous broker, allowing even the most recent Darwins to have more than respectable operating histories.

All Darwins section on Darwinex for research

Darwinex research filter Latest 2

While Explore enters an area where Darwins are grouped by shared features, through the All Darwins section (61% of retail CFD accounts lose money) on Darwinex users can see the complete Darwins list on Darwinex, without any pre-set filter whatsoever.

Darwins are sorted by default based on their Return values (calcolated over the last two years), but as in the last section, it is possible to sort them according to other parameters (Investors capital, investors, return, Drawdown, D-Score).

The graphic layout of this area is the same as the previous one, you can either use a detailed view or a frame view.

The most interesting aspect of the All Darwins section is the possibility to set one or more research filters, to find the most suitable Darwin for your investor profile.

Manage filter function

Manage filter

Through the Manage Filter function you can set a customised research to find the Darwins who better suit your needs.

darwinex Manage filters

The filters are the same we have discussed in the Explore section, with the addition of the Community Darwins element.

Selecting the “+ MANAGE FILTERS” function a pop-up window will appear, containing the complete Darwinex filter list (Top Invested, Good Scores, Return>50%, On Fire, Trending, Promising, Latest, Community Darwins).

Within this pop-up users can select more than one element, flagging the corresponding check-boxes. Finding the Darwin who better suits your portfolio concept and investment goals will be much easier using these filters.

Darwin Analysis Section

Once you have found the Darwins you believe to be more interesting, the best thing to do next is to try and acquire a deeper understanding of their operating features, to figure out if they can really be suitable for your needs and if they would be a good addition to your investment portfolio.

Darwinex (61% of retail CFD accounts lose money)  grants you a wide array of interesting and useful indicators, which can be all found in the technical sheet of every single Darwin profile.

Top Section

darwin analysis 1

In the topmost section of the sheet, you can find all the personal data of the Darwin:

  • The trader’s complete name, to which a unique 3 upper case letters code is associated, inside a coloured circle
  • The strategy’s name
  • The user name of the trader’s profile behind the strategy. As the image shows, if a trader has other strategies or Darwins, a +1 will figure next to the user name. Hovering with the pointer over the +1 will open a window showing the other Darwin managed by the trader.

darwin analysis 1-2

The image shows that the trader registered in Darwinex with the user name “finbou” manages two Darwins: THA and FEG.

  • Right below this is a text field used by the trader to provide information about the investment strategy of his Darwin.
  • On the far right is the Darwin’s value. This is an important element to assess its performance. All Darwins start with a value of 100 and follow returns (100 + Return Since Inception), so higher values mean that a Darwin has turned profits, whereas values lower than 100 means the Darwin is at loss.
  • The “Trade” button, next to the Darwin’s value, allows you to purchase it.

Lower Section

darwin analysis 2

This second area, right below the previous one, shows many details regarding the Darwin.

On the top left is the Darwinex Score. Since this is the most important value, the next chapter is dedicated entirely to its analysis. Let’s see all other values first.

Return (since inception): States the profit made since the Darwin started operating on Darwinex. While this is certainly an interesting value, unfortunately it can’t be compared to other Darwins, as not all Darwins exist on Darwinex at the same time. So, upon similar returns, this value is higher for Darwins who’ve been operating longer on Darwinex, as they’ve had more time to increment returns. This score doesn’t match the Darwin’s Value as the latter starts from a value of 100, whereas Return begins at 0.

Drawdown (since inception): Like the last value, the Drawdown analysis is performed on the complete history of the Darwin. This case however analyses drops in performance. The drawdown indicates the loss recorded at the worst operating moment. This value, together with volatility, provides important information regarding the risk profile of the Darwin, offering the chance to understand whether this can be suitable for your portfolio and your risk propensity.

Return/Risk (since inception): Another important element to assess the efficiency of a strategy is the risk-returns evaluation. This piece of data represents the ratio between the average return value (positions closed with profits) and the average risk value (positions closed with losses). A value close to 1 indicates a substantial balance between risks and results achieved by the strategy; this balance tips towards returns in case the value is higher than 1, and towards risks if lower. The Return/Risk, combined with the percentage of operations closed with profits is one of the most important elements when assessing the strategy of a trader.

Target Risk (VaR 95%/month): This parameter is widely used to identify the potential risk of an investment. For the Target Risk evaluation, Darwinex analyses the history of operations performed by the trader and, thanks to the support of statistical analysis models, it establishes a future volatility which can be statistically expected with a 95% reliability. Simply put, this means that if the Target Risk is 10%, purchasing that Darwin, an investor can expect a potential profit or loss which does not exceed the 10% of his investment on a monthly basis. This will statistically happen 95 times out of 100, the other 5 times this value can be disregarded, determining higher positive or negative oscillations (knowing how much higher would be impossible). As a rule of thumb, higher Target Risk values are suitable for investors willing to take on more risks to achieve higher profits.

Trader’s Equity: The balance of the trader’s account now (combined with the average VaR evaluated at the time of the analysis).

Investors: The Investors parameter is one of those used to assess the popularity of a Darwin. It details how many traders have that asset in their portfolio, and the capital counter value (obtained by summing the investments made by the individual investors on the Darwin).

Darwinia Allocation: the amount that Darwinex has allocated to the particular Darwin in the DarwinIA Trading Challenge, a contest where Darwinex “invests” 4.000.000€ every 6 months on 48 of the best Darwins, awarding them with 20% of the achieved profits, with High WaterMark clauses.

Monthly divergence & Latency: This parameter highlights the Darwin’s latency and divergence, two important values ​​to be admitted to the DarwiniA contest. Both will be explained later in more detail.

Filters: Displays the search categories (seen earlier) under which the Darwin belongs. Clicking one will open the specific filter page.

Darwinex Score: What it is and How it works

Also known as the D-Score, it is the “vote” of merit assigned by Darwinex to each Darwin (61% of retail CFD accounts lose money). The Darwinex Score is obtained by weighing the results of the 12 Attributes used by Darwinex to analyse each individual Darwin.

The value of the 12 attributes ranges from 0 to 10. The higher the score, the better the judgement.

Here they are.

– Darwinex Score: Experience (EX)

Experience determines the reliability of the strategy, i.e. whether the operating history is sufficient for a true evaluation of the Darwin’s effectiveness. The D-Score is heavily penalized by low Experience scores.

An Experience score of 10 roughly corresponds to one year of continuous market trading.

The time factor is very important for determining the Experience value, but it is also conditioned by the intensity of the trader’s activity. Darwinex has decided to scan time through D-Periods, which correspond to approximately one month of trading each (22 days of open markets). To “earn” a D-Period, a trader must meet the following two conditions:

  • At least 15 days of Trading (days when positions were opened to buy, sell or for partial sale)
  • At least 18 representative decisions, measured by D-Leverage and Duration (i.e. Leverage and Duration).

The goal of these conditions is to collect data more intelligently, rewarding Darwins not just according to time. Let’s say a Darwin has been working for over two years, only trading, however, one operation every 6 months, every position lasting just one day. Two years are a long time, but the number of performed transactions is far from being sufficient to statistically establish whether the Darwin’s strategy is any good. So, to determine if a Darwin has provided enough data to be appropriately evaluated, Darwinex has opted for a complex but rather effective algorithm, which considers the duration of the Darwin, but most importantly the quantity, leverage and duration of the trades.

The Experience Attribute can only increase. Experience values ​​of 10 indicate that the data Darwinex has is more than enough to establish the validity of the strategy.

It goes without saying that, depending on the type of the trader’s operations (frequent or scarce), the operating history might have to be longer, to get a score of 10.

– Darwinex Score: Market Correlation (Mc)

The market correlation, indicates how much the Darwin’s operating results depend on the performance of the underlying assets (the purchased assets). In other words, this value highlights how much the operating result of a Darwin is related to the oscillations of the underlying assets.

The higher the score, the more the Darwin is disconnected from the asset, meaning that the trader is able, with his strategy, to earn both when the underlying asset earns and loses value.

– Darwinex Score: Risk Stability (Rs)

This value assesses the stability of the strategy, the persistence of the Darwin’s behaviour over time (whether the fluctuations in time have always been contained). High Risk Stability scores denote a VaR of about 10% (a somewhat contained volatility).

– Darwinex Score: Risk Adjustment (Ra)

This indicator evaluates how often Darwinex’s Automatic Risk Management system works to reduce the risk of strategy. Higher scores mean Darwinex must intervene less to modulate the risk.

– Darwinex Score: Open Strategy (Os)

Darwinex tests the validity of the strategy through this value, simulating multiple opened positions before and after (as input timing) the ones opened by the trader. High Open Strategy values ​​indicate a good entry timing by the trader, which shows that the inputs he provided were executed at the best possible time.

– Darwinex Score: Close Strategy (Cs)

The Close Strategy, applies the same logic of the Open Strategy for the exit timing of positions. With this attribute, Darwinex means to evaluate whether the trader’s closing strategy can be improved. The two indicators combined can give you an insight into how the trader’s strategy can be improved.

– Darwinex Score: Positive Return Consistency (R+)

This value indicates whether there is a predetermined pattern to close operations, that is, if the trades are closed following a solid and systematic logic. A high Positive Return Consistency value ​tends to indicate that the trader, in his strategy, always has a plan and never relies on chance.

– Darwinex Score: Negative Return Consistency (R-)

This value has the same function of the Positive Return Consistency, but considers the operations closed with losses. The higher the Negative Return Consistency is, the more clearly the trader implements logical management and loss reduction, which is among the most important elements for investment success.

– Darwinex Score: Duration Consistency (Dc)

This attribute tries to assess whether the trader uses time strategies for closing his trades. In other words, if the trades are of the same duration, the trader has a precise timing strategy, and the Dc score will be higher.

– Darwinex Score: Loss Aversion (La)

Comparing the amount of profits in relation to the extent of the losses is important to understand the trader’s ability to cut losses and to make profits run. Loss Aversion focuses precisely on this aspect. High scores identify a trader with the ability to let profits run, and at the same time quickly cut losses when operations do not go in the right direction. In other words, higher scores identify trading strategies with a good risk/returns profile.

– Darwinex Score: Performance (Pf)

To generate the Performance attribute, Darwinex compares the returns of the trader’s strategy to those of 10,000 Monte Carlo simulations using the same risks, assets, and durations. The higher the score, the more it means that the trader’s strategy has been able to beat random simulations.

– Darwinex Score: Capacity (Cp)

For this value, Darwinex monitors and reports the performance of the Darwin as the number of investors increases. High Capacity values ​​indicate that the increase of investors does not lead to a performance decline of the Darwin.

Darwin Analysis Section: Return/Risk

Within this Darwinex section, all the Darwin’s risk and performance elements are analyzed (61% of retail CFD accounts lose money).

– Darwin Return

Darwin Return

The area dedicated to the Darwin’s Returns offers, on the top right, the option to set the time of analysis, choosing from the available history: the last two years, the last year, semester, quarter, month, week, and day. Once the period has been set, the graph and other indicators will be updated accordingly.

Darwin Return’s central and foremost element is the graph showing the returns of the Darwin (the percentages are on the Y axis and the days are on the X axis). This chart allows you to properly see the progress of the profits as well as the amount and entity of the Drawdowns, all useful elements to understand whether you like how the Darwin profits.

The Migration Date is the date on which the trader has “brought” his operating history, produced with another broker, to the Darwinex platform.

Below the chart is a practical table, showing the returns of the Darwin split by year and month.

– Performance Statistics

Performace StatisticsTo the right of the chart, under Performance Statistics, is some quick fruition data, already partly seen in the previous upper section:

  • Return: Darwin’s performance as percentage;
  • Max Drawdown: The percentage of loss in the worst operating moment;
  • % Winning day: Percent of days closed with profits;
  • % Winning week: The percentage of weeks closed with profits.

– Return Distribution Daily & Return Distribution Weekly

Return Distribution Daily Weekly

The histogram chart counts the number of days (Daily) or weeks (Weekly) when the trader has reached a certain level of profit or loss, divided by columns.

Each profit/loss range is a graph bar, the higher the bar, the greater the number of days or weeks the performance is within that range.

Hovering with the mouse pointer on an individual bar will display the amount of days and the performance range which is currently represented.

As for the red bars, the fewer the better, and if any, the most central ones would be best. For green bars instead, as a rule, the higher the bars are going right, the better.

– Risk Statistics

The Risk Statistics are to the right of the two charts we have just seen:

  • Average daily return: Percentage of daily average returns;
  • Average weekly return: Average weekly returns rate;
  • Worst day: Percentage of maximum loss in the worst day;
  • Worst week: Percentage of maximum loss in the worst week;
  • Worst month: Percentage of maximum loss in the worst month;
  • Average D-Leverage: As the name implies, the average D-Leverage;
  • Max D-Leverage: The maximum amount of D-Leverage.

The data in this table also refers to the selected time frame for the analysis.

Darwin Analysis Section: Asset & TimeFrames

Asset & TimeFrames studies the assets on which the trader works and the timeframes when he/she usually operates.

As in the previous section, Asset & Time Frames allows users to set an analysis period (top right) that will affect all the extrapolated data.

– Trading Time Distribuition

Trading Time Distribution

Trading Time Distribution displays a nice histogram chart that indicates the percentage of trades executed per time frame. Each bar represents one hour, so the chart is made up of 24 bars.

Placing the mouse pointer over the bar, users can see the percentage of trades made during that particular time frame. This way users can understand when the trader is more active.

– Daily Performance

Daily Performance

Daily Performance shows a histogram representation as well, but in this case the bars are 5, as the trading days during the week.

The height of the bar represents the amount of trades executed on that specific day of the week. If the bar is green it means that most of the operations have been closed with profits, red on the contrary means most operations where closed with prevailing losses.

Hovering with the mouse pointer on the bar will show the details, for that day, how many trades were opened, how many were closed with profits, how many were closes with losses, and the achieved performance percentage.

– Asset Allocation

Asset Allocation

The Asset Allocation section shows, through a pie chart, the variety of assets traded by the trader. The larger the size of the slice, the more the asset has been traded.

When the pie slice is red, it means that the % of closed operations with profits for that asset is lower than 50%.

Don’t be frightened right away seeing a preponderance of red slices: a profitable trader can close many transactions with losses, what matters is the volume of the losses compared to the profits. In other words, many small losses can be offset and overcome by a few big profits.

Hovering the mouse pointer over the pie slice, users can get an indication of the type of asset, the amount of transactions made, the percentage of the volume of trades over the total operations, the average duration of the transactions, and the percentage of positions closed with profits.

– Max. Positive/Negative excursion per trade, including open trades

Max Positive Negative excursion per trade

This chart is very interesting. The Y axis shows the percentage of trade excursion, while the X axis shows the performed trades.

For every single trade (even the ones that are still open), users can see the maximum and minimum excursion %. Hovering the mouse pointer on each individual bar, users can see the date and time when the trade was opened, its asset, the minimum and maximum oscillation rate, and the percentage of profit or loss upon the closure of the position.

In other words, it is a useful graph to visually understand the risk/return levels of the trade, and whether the trader tends to close his operations upon the maximum achieved oscillations. For instance, if a trade reaches a 5% maximum gain, but then is closed at only 0.1% profit, it means that the trader couldn’t protect the profits he had generated.

– Duration vs Profit (pips) of the last 100 already closed trades

Duration vs Profit

This graph, pays attention to the relationship between the duration of operations and the pip profit of the last 100 trades. At the top right you can set the date from which the analysis should start.

The Y axis represents the duration of the operations, and the X axis represents the returns in pip per trade. Red dots positioned to the left of the 0 represent transactions closed with losses, green dots represent trades closed with profits. Positioning the mouse pointer on a single dot, users can see the date and time when the operation was performed, its returns in pips, duration (days, hours, minutes and seconds), its volatility (VaR) and the leverage which has been used.

Ideally, we would rather see red dots low on the graph and close to zero, meaning the trader quickly closes trades going in the wrong direction, with few losses, while green dots should be on the top right, which would mean the trader lets lucrative trades run on for a while.

Darwin Analysis Section: Investable Attributes

The Investable Attributes section is dedicated to the analysis of all the Darwinex attributes (61% of retail CFD accounts lose money).

As previously mentioned, Darwinex objectively analyses several elements of a trader’s strategy, assigning them scores. The elements considered are called Attributes, and the scores assigned to each one range from 0 to 10. Their sum, appropriately weighed, determines the D-Score.

Let’s analyse them one by one.

– Darwinex Score

Darwinex Score chart

As explained in the previous chapter, the Darwinex Score is the synthetic score Darwinex attributes to each Darwin. It is obtained by adding and adequately weighing the values ​​of the individual Attributes.

The Darwinex Score is interesting as it sums up Darwinex judgment on the trader’s strategy and on the individual Darwin. At the top right the analysis period can be selected, while on the bottom, through a linear chart, users can see the Darwin’s evolution for the selected period.

At the right of the chart is a table displaying the values ​​of the individual Attributes. Positioning the mouse pointer over a precise point in the chart, the table will show its D-Score detection date, its score, and the values ​​of the individual Attributes that determined it.

This section is both interesting and useful as it allows users to see the progress of the Darwinex Score, understanding if its evolution has been regular or whether it has spiked either up or down. Obviously, a certain attention must be turned to falling peaks, so users should try and see what happened and why Darwinex has penalized the trader’s strategy so much.

In this regard, one or more attributes can be selected from the table on the right, to see them represented in the chart along with the D-Score. The individual values can then be compared to the overall score, to better understand what was the element that caused any significant spike.

Darwinex Score chart 2

Darwinex Score chart 3

– Spider Chart: D-Score

Spider Chart D-Score

Below is a D-score in a spider chart.

This type of representation is useful to better understand what Attributes should be improved. By positioning the pointer over the individual Attibute, a description of the same will be shown on the right.

– Experience

Experience d-scores

Darwinex uses the Experience Attribute to judge whether the history and the transactions made by the trader are sufficient to adequately describe the strategy, therefore providing the chance to correctly asses the operating scenarios of the Darwin.

The analysis period for Experience is pre-set to the last 12 D-Periods (if present).

By positioning the mouse pointer over any point in the graph you will see the date, returns percentage for the strategy, and the D-Period value.

Experience d-scores tableThe table on the right, on the other hand, shows the following statistical data:

  • Trading Days: The amount of days trades were made in within the analysis period.
  • Representative trading decisions: The amount of representative decisions, which make up one of the two criteria to determine the increase of the D-Period, which in turn defines the increase of Experience.
  • Average Days per D-period: How many days an average D-Period is made of. As mentioned earlier, this value tends to change depending on the trader’s strategy (depending on the average volume of operations).
  • Total D-Periods: This value can amount to 12 at most.
  • Date of attributes’ first analysis: The date from which the Experience analysis begins.
  • Evolution of Score: The maximum and minimum value of Experience, together with the graphic representation of its performance. Since the Experience value can only improve, and since Darwinex always reports the last 12 D-Periods, it is possible to find Darwins with a flat line in this section and an Experience Value of 10. This is because they have reached a year of operating activity for a while.

– Market Correlation

Market Correlation d-scores

The Market Correlation section analyses how the Trader’s results have been affected by the market’s performance. In the upper right users can select the analysis period per D-Periods, specifically 3-6-12 periods. Darwinex’s analysis is performed on each asset used by the trader and returns interesting information.

Each asset has a form that provides the following information:

  • Correlation: identifies the degree of correlation of the trader’s strategy with the asset. The closer this value is to 1, the greater the correlation, this will negatively affect the judgement of Market Correlation. If, however, the correlation is closer to 0, the situation will be the contrary.
  • Correlation weight: Points out how much the asset “weighs”, in percentage, compared to all others in the final judgement of Market Correlation.
  • Market Direction: Highlights the amount of open and long transactions, both as a percentage of the total and as an absolute value. This is represented with an intuitive pie chart.
  • Time Opened: This graph measures the time spent on the analysed asset market against all the other financial instruments on which the trader operates, distinguishing between long and short transactions. Time Opened is useful to understand what was the operational standing on the single asset over the total, and therefore helps to determine which assets are most important to the Darwin’s strategy.
  • Exposure (risk) opened: Identifies the extent of risk exposure when opening positions. A distinction is made between long and short operations here as well.

Market Correlation d-scores tableTo the right of the charts is the usual statistical table, which in this case addresses Market Correlation:

  • Total Correlation Factor: Determined by the average correlations per each asset;
  • Asset with highest correlation: Locates the asset, among those traded by the trader, where the operations are more closely related to the market’s trend.
  • All assets’ summary Total positions: A summary of the operations involved in the analysis with the total number of analysed operations.
  • Long positions: Total number of analysed long positions;
  • Short positions: Total number of analysed short positions;
  • Risk exposure (long): Risk exposure for long positions; (max or average risk?)
  • Risk exposure (short): Risk exposure for short positions;
  • % out of the market: The average time percentage the trader has remained out of markets, i.e. with no open positions on the market;
  • Evolution of Score: The evolution of the Market Correlation score, focusing on the minimum and maximum values, and the progress over time, represented as a small linear chart.

A constant progress of the chart shows a good strategy consistency.

– Risk Stability

Risk Stability d-scores

We have widely talked about what the VaR is, how it gives us an indication of the strategy’s risk factor and, consequently, how we can expect returns and losses from the strategy itself.

In this section, through a linear chart, we can see the evolution of the Darwin’s Monthly VaR.

Once the analysis period of reference has been set at the top right, an orange line, running within a corridor delimited by two white lines will appear. The orange line shows the evolution of the VaR, while the two white lines are its maximum and minimum values. By positioning the mouse at any point of this line, you will get the Var, Maximum Var, and Minimum Var values for each specific date.

The elements highlighted by the chart are:

  • The VaR’s performance: Linear VaRs are preferred, with light and gentle variations over time.
  • VaR values: In addition to a gentle and regular progress over time, it is also important to assess the VaR’s values. Values under 10% mean the operations tend to be quite safe.
  • VaR Corridor: The last element to check for is the breadth of the corridor, the narrower it is, the more we can be sure the strategy is controlled and lacks spikes.

Risk Stability d-scores tableTo the right of the chart is the statistical section of Risk Stability, which reports the following data:

  • Min. monthly VaR: Minimum VaR, considering the analysis period;
  • Max. monthly VaR: Maximum VaR, still considering the analyses period of reference;
  • Worst month: The VaR of the worst month;
  • Average VaR change in a month: The average change in the VaR on a monthy basis;
  • Evolution of Score: The evolution of the score for the Risk Stability attribute (still for the period of reference), along with the lowest and the highest score, and the historical evolution represented through a mini chart.

– Risk Adjustment

Risk Adjustment d-scores

This section is a graphic representation of how many times Darwinex has had to intervene on the trader’s strategy to limit its risk.

The Risk Adjustment analysis is made by placing all the Darwin’s trades within a chart, with the D-Leverage values ​​on the Y axis, and the duration on the X axis. Each dot represents one or more positions opened at the same time.

Darwinex intervenes when the D-Leverage and duration values ​​deviate negatively from the trader’s operating average. Basically, if Darwinex notices that, based on the trader’s operating history, something unusual is happening, it will intervene, blocking any excess.

The dot is therefore green if Darwinex has not intervened to adjust risk, as the trader’s behaviour was in line with his normal strategy, whereas it will be red in case Darwinex has intervened to mitigate risk.

Each dot contains information regarding the date and time of the position, its duration, the D-Leverage value assessed by Darwinex, the Risk Adjustment percentage (if any), and how many trades where opened simultaneously for that operation; finally, the positive or negative return in %.

From the dot density in an area of the chart can give away the trader’s style (long or short duration, D-Leverage entity).

Risk Stability d-scores tableThe statistics table on the right contains the following:

  • % Position adjusted: This indicator highlights the percentage of operations which have required an intervention from Darwinex to adjust risk to a normal level.
  • % Exposure closed: This parameter highlights the percentage of excess market exposure that had to be closed.
  • Monthly VaR in period: The VaR oscillation for the period of reference
  • Evolution of Score: The classic notation of how the attribute score has moved, considering the minimum and maximum value for the period of reference and its evolution from a graphical point of view.

– Open/Close Strategy

Open Close Strategy d-score

These two Attributes are linked to each other, so much so that Darwinex analyses them jointly within the same section.

This analysis is as much interesting and fascinating for traders like us, as it is basically (almost) useless for the investor. The system aims at identifying the predictive capabilities of the trader, to demonstrate that luck has no part in trading.

The returns of transactions made by the trader (white line thicker than the others) is measured against the hypothetical values of other open (top chart) or closed (bottom chart) operations before or after. The range considered for entry and exit points is of positive or negative 10%, 20%, 30%, 40% and 50%.

The analysed period can be set by going to the D-Periods at the top right, whereas positioning the mouse pointer over a point in the chart will allow users to see, for every operation, its average ranking and its position in the ranking, compared to the others.

To better clarify the meaning of these Attributes we can analyse the image, from which we can see that the returns would be greater if the operations were opened with a delay of -50% and closed with a delay of -20%.

Open Close Strategy d-score tableBy better analysing the performance of the strategy compared to those of other operations, we can see that:

  • As per opening the operations, the trader’s strategy has the fifth position;
  • As for closing the position, this strategy comes in last.

This indication can also be very useful to the trader himself, as he is shown that closing transactions with a 20% delay would maximize his returns. It should be noted, however, that such reasoning is much more easily said than done.

Again, on the right, we have a statistics panel for both open and closed trades:

  • Trades over 10 minutes: The amount of trades with a duration of over 10 minutes
  • Average strategy ranking: The ranking of the trader’s strategy, compared to the other 10
  • Percentile compared to random strategies: Percentage returns of the strategy compared to the other simulated strategies
  • Strategy final ranking: The final ranking of the strategy over the others
  • Best strategy: Which of the 11 strategies has proven to give the best performance
  • Evolution of Score: The scoring performance and the minimum and maximum values, plus the chart showing the historical evolution of the data

– Positive e Negative Return Consistency

Positive Negative Return Consistency d-scores

These are other two attributes that are jointly analysed. The goal is to identify whether the trader chooses the closing points of his operations, whether with profits or losses, using solid strategies or patterns.

Darwinex provides a graph that shows the Duration on the Y axis (duration of the operation) and the returns, in pips, on the X axis. A large concentration of dots (green for profit, and red for operations with losses) in certain areas of the chart identifies the existence of recurring operating logics and predefined patterns to determine the closing of operations.

Positive Negative Return Consistency tableObviously, the greater the concentration, the stronger and more rigid is the closing logic.

The following data can be found in the statistics table to the right of the chart:

  • Total Days: The total number of days considered by the analysis
  • Days with positive returns: Total number of days closed with profits
  • Days with negative returns: Total number of days closed with losses
  • Positions with positive returns: Amount of transactions closed with profits
  • Positions with negative returns: Amount of transactions closed with losses
  • Evolution of Score: The scoring performance and the minimum and maximum values, plus the chart showing the historical evolution of the data. This value is clearly divided by Positive Return and Negative Return attributes.

– Duration

Duration d-scores

The Duration section deals with how long an operation is open on the market before being closed.

The chart is similar to the previous one, although it returns different data. The duration is on the Y axis, while the X axis displays the gained/lost pips; the chart represents a sample of one hundred operations going back in time, starting from the date set on the top right-hand calendar.

The green dots represent operations closed taking profits, the red ones represent those closed with losses. Placing the mouse pointer on one of the dots will provide information on:

  • date and time of the operation
  • positive or negative return in pips
  • duration (how long the trader kept the position on the market)
  • the VaR (always referring to the operation)
  • the leverage

By checking the arrangement of the operations (red or green dots) user can get an idea of how the strategy works on short or long-term operations, and what can be the amount of profits depending on the duration of the operations.

Traders who run profits will have a concentration of green dots in the top right of the chart; conversely, green or red dots concentrated in the centre of the chart next to the horizontal axis will identify fast scalping-like operations (reduced profits and shorter times).

Duration d-scores tableScalping strategies are difficult to replicate, which is why Darwins with such characteristics tend to be less appealing than others.

In the statistics table on the right of the chart, the highlighted data is the following:

  • Total Days: The total number of days included in the analysis (based on the date set in the upper right the system performs an analysis since that day back to the last 100 performed operations)
  • Total Positions: Total number of analysed operations
  • Total Positive Positions: Total number of positions closed taking profits
  • Total Negative Positions: Total number of positions closed with losses
  • Evolution of Score: The evolution of the score, the minimum and maximum values ​​achieved, plus the usual chart to see the score’s performance over time.

– Loss Aversion

Loss Aversion d-scores

One of the secrets of successful trading is having the ability to let profits run and to cut losses.

Loss Aversion tries to assess whether the trader has such ability.

The Y axis of this Darwinex chart represents returns, calculated as a percentage on the asset value, while the X axis displays a list of the positions, from the oldest (left) to the most recent. As with other charts, a D-Period can be set on the top right, to better analyse the strategy.

Each bar represents the oscillation of a single operation, from the entry to the exit spot. Hovering over the chart with the mouse pointer allows user to find out:

  • date and time when the position was opened
  • the asset on which the trader has invested
  • the highest and lowest values of the trade
  • the profit/loss percentage when the position has been closed, graphically represented on the bar by a notch.

This at-a-glance aspect is definitely interesting. A strategy that tends to contain negative oscillations, trying to achieve positive oscillations two or three times wider, will have a graph with green bars far taller than the red ones.

Loss Aversion d-scores tableTraders using this type of strategy are universally more valued than others.

The values ​​in the right table are:

  • Successive trades on same asset: The amount of consequent transactions on the same asset
  • Average positive excursion: The average value of positive excursions
  • Average negative excursion: the average value of negative excursions
  • Best positive excursion: The value of the best positive excursion
  • Worst negative excursion: The value of the worst negative excursion
  • Average on extreme positive excursions: The average of the highest positive excursions
  • Average on extreme negative excursions: The average of the highest negative excursions
  • Evolution of Score: The progress of the score, with the lowest and highest values ​​for the analysed period, and their graphic representation.

– Performance

Performance d-scores

According to Darwinex’s theory, to correctly assess the validity of the trader’s strategy, it must be compared with another 10,000 random variants, operating with the same risks, assets and timing. The result of this comparison is a sort of performance ranking within which the Darwin will be placed.

A D-Period can be set for analysis in this case as well. The better the ranking, the higher the score of the Performance attribute.

Performance d-scores tableThe goal of the Performance parameter is to find out how much of the trader’s performance is to be attributed to fate rather than the trader’s ability, thus determining the strength of the strategy in place.

The statistics table shows:

  • Positions: The amount of operations being analysed
  • Market Days: Market days considered to consider all operations
  • Activity Days: The amount of days the trader has worked on the markets, opening or closing operations
  • Percentile: The percentile value under which the results of the trader’s strategy falls when compared to the 10,000 simulations
  • Evolution of Score: The evolution of the score, represented through a linear graph, plus the highest and lowest values ​​for the period of reference.

– Capacity

Capacity d-scores

The purpose of the Capacity attribute is to understand whether more investors could negatively affect the trader’s strategy. This may depend on several factors related to the operational strategy.

Capacity: Divergence sensitivity

The first chart focuses on Divergence Sensitivity, i.e. how much the Darwin’s strategy is sensitive to a hypothetical loss of 0.2, 0.5, 1, or 2 pips per trade.

In the top right, users can set the historical period of reference, to see how the Darwin’s returns might change.

To find out the performance of the Darwin and of other simulated cases on a given day, users can just place the mouse pointer over a point in the chart. Looking at the chart’s trend over time, it’s easy to see how great of an impact a drop of value of even a few pips per operation could have on the strategy’s performance.

Generally speaking, strategies with profits amounting to a few pips per transaction are influenced far more by these negative variations than strategies that close operations with wider profits.

Max. divergence allowed (In pips)

Max divergence allowed d-scores

This graph shows the highest divergence in pips recorded over time, day by day. The purpose of this indicator is to highlight the repeatability of the strategy.

The lower the line is, the less divergence there is, the better the strategy is overall.

Average leverage per trade (DARWIN)

Average leverage per trade

This chart shows the trend of the average D-Leverage per trade, day by day.

Max. estimated investment (DARWIN)

Max estimated investment

This chart estimates the amount invested in the Darwin, day by day.

Comparing this chart to the one of the Max. Divergence Allowed (In pips), it can be noted that, at least for the Darwin in example, as the invested volumes and pip divergence increase, the performance value decreases.

Capacity d-scores tableIn the statistics table, the following parameters are highlighted:

  • Return of Darwin: The return percentage achieved by the Darwin
  • Return with 0.2 pips of divergence: The return percentage of the Darwin considering a value loss of 0.2 pips per trade
  • Return with 0.5 pips of divergence: The return percentage of the Darwin considering a value loss of 0.5 pips per trade
  • Return with 1 pip of divergence: The return percentage of the Darwin considering a value loss of 1 pips per trade
  • Return 2 pips of divergence: The return percentage of the Darwin considering a value loss of 2 pips per trade
  • Max. Divergence allowed (pips) | Max in reference period: The highest pip divergence recorded in the reference period
  • Max. Divergence allowed (pips) | Min. in reference period: The lowest pip divergence recorded in the reference period
  • Average leverage per DARWIN’s trade | Max. in reference period: The highest leverage which has been applied in the reference period
  • Average leverage per DARWIN’s trade | Min. in reference period: The lowest leverage which has been applied in the reference period
  • Max. Estimated Investment: The highest investment recorded on the Darwin
  • Evolution of Score: The usual information regarding the evolution of the Attribute, together with the lowest and highest values and its graphical representation.

Darwin Analysis Section: Divergence

In Darwinex’s Divergence section, the goal is to assess the extent to which the investor has succeeded in replicating the transactions made by the trader (61% of retail CFD accounts lose money).

– Divergence in %

Divergence in %

The Divergence in % graph shows the Darwin’s returns compared to those of the investors who have it in their portfolio. A period of reference can be set, to assess, at the end of the period, how the Darwin’s performance compares to the investors’ who employ it.

Positioning the mouse at any point in the chart provides the date and time of the operation, the returns so far produced by the Darwin and the returns replicated by the investor, in addition to the divergence % up to that moment.

This can be useful to understand if the results of the analysis can be maintained even after the investor has the Darwin in his portfolio.

Divergence in % tableThe statistics table provides the following values:

  • DARWIN (representative orders): Darwin’s returns in percentage for the period of reference
  • Investors’ estimated return: The estimated return for investors
  • Divergence in period: The divergence for the period, i.e. the difference between what the Darwin has made and how much it was replicated by the investors
  • Current monthly divergence: The divergence of performance for the current month.

– Divergence per order

Divergence per order

The Divergence per order chart displays the positive and negative divergence levels for each operation.

Each operation is represented by a pale blue dot for positive divergence, and a red dot for negative divergence. Another element shown in the chart, on the Y axis, is latency, i.e. how long it takes to replicate the same operation for the investor.

Hovering over a single dot, users can see the date and time of the transaction, the asset on which the trader operated, the volume of the trade, the latency, and the pip offset pertaining the original result.

The ideal case would be to see the dots (i.e. operations) gathered towards the central area (which means 0 divergence pips), and low on the Y axis (i.e. 0 latency seconds)

Divergence per order tableThe statistical table for this attribute provides the following information:

  • Number of Orders: The amount of orders considered for the analysis of the selected period of reference
  • Average order size: The average size of orders
  • Average divergence: The average divergence of pips
  • Median divergence: The median divergence, still expressed in pips (find out here about the difference between average and median divergence)
  • Average latency: The average latency on the total number of transactions considered
  • Median latency: The median latency
  • Orders (<987.96 ms latency): The amount of orders, over all the analysed orders, with a latency below 987.96 ms
  • Average divergence: The average divergence in pips for operations with latency below 987.96 ms
  • Median divergence: The median divergence in pips for operations with latency below 987.96 ms.

Darwin Analysis Section: Correlation

This Darwinex section is very interesting (and useful) to create a properly structured portfolio (61% of retail CFD accounts lose money).

By properly using the tools provided by Darwinex within the Correlation section, users can figure out whether the Darwins they have chosen will live in harmony within their investment portfolio.

A high degree of correlation indicates that two Darwins respond the same to similar market conditions. Understanding this key element, users can assess whether to include in their portfolio Darwins which behave the same.

– Correlation between XXX and other DARWINs (highest to lowest)

Correlation between

The first available element is a table that shows the correlation degree between the Darwin currently being analysed and others. The Darwins in the table range from the one most related to the least-related one. The closer the value is to 1, the greater the correlation.

The bottom of the table also informs user whether that Darwin is included in the DarwinIA contest.

– Correlation between XXX and…

Correlation between 2

This graph allows to study the correlation between two Darwins, the one in analysis and another.

By default, the Darwin with the highest degree of correlation is used, however it can be replaced with whatever is preferred, also the period of reference for the analyses can range from 1 to 6 months.

The graph displays the performance of both Darwins in the period of reference, providing the opportunity, hovering over the chart with the mouse pointer, to visualize the date and performance of both strategies. It will then be easy to understand how the Darwins would have behaved in the past, and to assess whether both strategies could fit in the same portfolio.

Correlation between tableThe statistics table reports the following:

  • Correlation: The degree of correlation between the two Darwins
  • Trades by XXX: The number of operations made by the Darwin you are analysing (XXX)
  • Trades by YYY: The number of operations made by Darwin you are comparing to (YYY)
  • Similar trades: The number of similar trades
  • Trades earlier than YYY: The number of transactions made by XXX before YYY started operating
  • Trades after YYY: The number of transactions made by XXX after YYY stopped operating
  • Does XXX participate in DarwinIA?: Specifies if the Darwin you are analysing takes part in DarwinIA
  • Does YYY participate in DarwinIA?: Specifies if the Darwin you are comparing to takes part in DarwinIA
  • DARWIN that overrides XXX: The Darwin who is “beating” the Darwin in analysis in the DarwinIA contest; sometimes you might find the name of Darwin, other times you could find the reason that led Darwinex to exclude the Darwin from the competition
  • DARWIN that overrides YYY: Same thing, but for the Darwin you’re comparing to.

Darwin Analysis Section: Underlying strategy

We finally got to the last section of Darwinex (61% of retail CFD accounts lose money). The goal here is to give you a better insight into the underlying strategy of a Darwin.

The information provided here is interesting, though not exhaustive (as opposed to other platforms such as ZuluTrade, which however does not offer some of the analysis tools provided by Darwinex).

Darwinex does not offer a precise insight on the trader’s operating style, intended as the individual operations. This is precisely a peculiarity of Darwinex, which in this way seeks to protect the intellectual property of the trader’s strategy.

Trading Journal

darwinex Trading Journal

Darwinex’s trading journal is made up of a central body, consisting of a 5 cascade charts, all aligned to the horizontal axis of time, offering the chance to set up a period of analysis, and the opportunity to consult a detailed table with data relating to specific points selected with the mouse pointer.

The first chart shows the Return, i.e. the return for the period of reference. Next is the D-Leverage, the leverage applied at any given time, and the Open Trade, i.e. the amount of trades opened in a given period. Following is the D-Score, represented by chart showing its evolution; and to top it off is the Trades Distribution chart, i.e. the distribution of asset operations with the amount and duration of the transactions.

Thanks to the side table, for each point the following data will be provided:

  • Which trade we are analysing relating to the total trades performed by the trader
  • The start and end date and time of the operation
  • the duration of the operation
  • the outcome, positive or negative
  • The oscillation range, obtained from sums of open market positions
  • The amount of trades opened at that time
  • The D-Leverage and the D-Score.

How to Choose a Darwin: The Most Important Things to Consider with Darwinex

Since the criteria to select a good investment for the future are extremely personal, and the word “future” has a different meaning for every investor, we now mean to speak of the elements we at InvestinGoal pay more attention to when selecting Darwins on Darwinex (61% of retail CFD accounts lose money).

The decision-making process to choose strategies is made up of several steps, namely:

  1. assessing the potential of a Darwin
  2. measuring the strength of the strategy and the repeatability of its results
  3. checking the possibility of coexistence within the investment portfolio.

1. Assessing a Darwin’s Potential

At InvestinGoal, the first thing we check for is the risk-related performance. If we invest, we want to know what the expected returns are for potential risks.

Therefore, the first parameters we check are the “Return (since inception)” with the whole available operating history (to find it just go to the Return/Risk section, select the “All” period and place the mouse at the beginning of the chart, to find out when the trader started working with that strategy).

This is important for two reasons:

  1. Regardless of the results, we tend to exclude all Darwins with less than one year of operational history, since we only want to consider strategies which have already proven to be stable and consistent over time
  2. We measure the performance against the number of months it took to achieve it; you must agree that a 50% return in one year is more exciting than the same return made in the twice the time (2 years).

Once we have established the returns over time, we relate this factor to the associated risk. Here, the Drawdown (which should be as small as possible) and the VaR (we tend to prefer VaRs which are not too high) come into play.

Considering the percentage of returns, the time taken to achieve it, and the risks involved in terms of volatilty and maximum loss (VaR and DrawDown), we can start skimming the first batch of results.

2. Assess the stability of the strategy

Once we have identified the Darwins with an interesting Risk/Return profile, we are going to start to deepen our understanding of the strategy (which is not an easy task in Darwinex, as mentioned earlier, given the trader’s intellectual property protection policy).

First, we use the D-Score (Darwinex Score). Normally we are not too excited to use judgements created by others, especially if the others are a somewhat interested party. However, as explained earlier, we must recognize that the elements used by Darwinex to determine this synthetic score are actually very good and refined.

That’s why we are interested in a Darwin’s Darwinex Score. Obviously, we don’t just stop here, let’s go deeper. The things we are most interested in looking at are:

  • The Trade Excursion, visible from the Assets & TimeFrames section, under the subsection Max Positive/Negative Excursion per Trade. We are trying to eliminate or downgrade all Darwins with notable negative excursions, particularly if they are accompanied by unimportant positive excursions.
  • Of the Investable Attributes, we inspect Risk Stability, preferring strategies with a highly controlled VaR history, with no excessive peaks and abrupt movements.
  • We also check that Darwinex hasn’t had to intervene too often to limit damage, controlling the Risk Adjustment attribute.

If the Darwin passes this test as well, then we proceed to the “results replication” phase.

Darwin’s Replicability

Sold by the Risk/Returns profile and the strategy details, we need to understand if the performance we are interested in is replicable within our account. The ideal place to look at for this inspection is the Divergence section.

If the value decline does not strongly impact the short or the long term, then the Darwin has passed most of our tests. There is only one left.

3. Coexistence within the portfolio

Choosing the right Darwins is the first important element, however it should not be secondary to verifying whether they can coexist in a wider integrated portfolio logic.

The first section to be tested is Assets & Timeframes, in the Trading Time Distribution and Asset Allocation subsections. Here, we can see the operating hours of the trader’s strategy and the assets on which he/she usually works.

It is important, though not indispensable, to find Darwins that do not concentrate most of their operations in the same time frames and on the same assets, to maintain a portfolio diversification logic, which is useful to depreciate risks.

Another very important section to check out is the Correlation one, where the degree of correlation between the Darwins we’d like to include in our portfolio can be assessed correctly. As a rule of thumb, the best thing would be to add to the portfolio Darwins with low levels of correlation. The reason is simple: being too correlated, the risk is that at some point, in certain market situations, your entire portfolio will be put to the test (with losses).

And finally, we’ve reached the end of this long guide to Darwinex. Please keep in mind that many of our considerations are the results of our risk appetite and of our investment goals! You may have other ideas, and to be able to fully develop them you must be able to understand what you are analysing and how it works.

Therefore, the best thing you can do, is read through this guide once more time. Also, leave a comment below to let us know what you think!

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Darwinex Guide and Tutorial FAQs

Is Darwinex a good broker?

Darwinex offers low spreads, trusted regulation, and a top-quality copy trading service. These factors make it a popular broker choice.

Is Darwinex regulated?

Darwinex is well-regulated by the FCA under license number 586466.

filippo ucchino

About The Author

Filippo Ucchino
Co-Founder - CEO - Broker Expert
Filippo is the co-founder and CEO of InvestinGoal.com. He has 15 years of experience in the financial sector and forex in particular. He started his career as a forex trader in 2005 and then became interested in the whole fintech and crypto sector.
Over this time, he has developed an almost scientific approach to the analysis of brokers, their services, and offerings. In addition, he is an expert in Compliance and Security Policies for consumers protection in this sector.
With InvestinGoal, Filippo’s goal is to bring as much clarity as possible to help users navigate the world of online trading, forex, and cryptocurrencies.

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