**Reference book of the database and its correlations**

__“Mod“ Model__

The program of a **trading robot** and its function **is** written on** own software packages of MT4 or MT5**. MT5 is the successor version of MT4 and has the disadvantage that the offers of EAs are not so big yet. Another disadvantage in the MT5 strategy test is that no external fees are possible anymore. Furthermore, there is no way to implement your own account history.

__“Anz.P“ Rating Points__

**Shows** you **how** **many** **rating** **points** this **program** has **already** **received** from other users. Not to forget, it should be noted that even people without expertise carry out an evaluation.

__“Anz.Bew“ – Number of evaluation__

Displays the **number** **of** **reviewers** **of** **the** **rating** **points**. **The higher** the number of **evaluators**,** the more meaningful the evaluation points** are. It should be noted, that there are still many programs available that are new or have never been tested or found.

__“KfPr“ – Purchase Price__

If the product is also available for sale, this column shows you from which price you can buy the product.

__“MiPr-1Mt“ – Rental Price for 1 Month__

If the product is offered for rent for one month, this column indicates you from which price you can rent the product for one month.

__“MiPr-3Mt“ – Rental Price for 3 Month__

If the product is offered for rent for three month, this column indicates you from which price you can rent the product for three month.

__“MiPr-6Mt“ – Rental Price for 6 Month__

If the product is offered for rent for six month, this column indicates you from which price you can rent the product for six month.

__“MiPr-12Mt“ – Rental Price for 12 Month__

If the product is offered for rent for twelve month, this column indicates you from which price you can rent the product for twelve month.

__“Kl.Pr/J“ – Lowest Price per Year__

If the product is offered for rent or for sale, then this column shows you from which price the EA is offered for one year use.

__“Kl.Pr“ – Lowest Price__

If the product is offered for rent or for sale, then in this column, from which price the EA is offered for use.

__“Anz.-NuMt“ – Number of working month__

Here ist given the useful life in months, if the smallest price for the use of the EAs arises by a rent. Should the smallest price be due to a purchase price, this field will remain empty even if the EA is available for $ 0.

__“Prüf-J“ Test Year__

Here is indicated the test year, if the EA was examined by us. Otherwise, this field remains empty.

__“Einl“ – Account Deposit__

Here is displayed the amount of the **account deposit**. Each **Expert Advisor** is **optimized** by the developer and should be **adopted** by the developer as the **default setting**.For some EAs, the account deposit is included in the optimization, so in the case of too small account deposit of the EA can not start.

__“Prof/Verl“ – Profit Factor__

Here is displayed the **profit factor** **determined** by the **backtest** of the developer. Profit factor = profit / loss.

Note: Some **backtests** were **too short**, **or** the program has **no stop lot**, or a **very big stop lot**, so there was **no loss trading**. In this case, the **profit factor** would be** infinitely large** so that the **profit factor is not displayed** in the backtest. Since there is no Holy Grail, it** will** certainly **come** **to** a** loss**, which could be larger. **For this case,** this **formula was recreated new** by me. Profit factor = profit / largest account decline.

__“Prof“ – Total Net Profit__

Here is **displayed** the** total profit of the whole test period** which was **determined** by the **backtest** of the developer.

__“Kont-R“ – Largest Account Decline__

Here is indicated the** largest account decline of the entire test period**.

Exapmle:

1. Trade loss -10 Euro

2. Trade profit -15 Euro

3. Trade profit -5 Euro

4. Trade loss -5 Euro

5. Trade loss -5 Euro

6. Trade profit – 5Euro

7. Trade loss – 5Euro

8. Trade loss – 5Euro

The largest account decline in this example would be 15 euros loss.

Solution:

1. Trade total result 10 Euro

2. Trade total result 5 Euro

3. Trade total result 10 Euro

4. Trade total result 5 Euro

5. Trade total result 0 Euro

6. Trade total result 5 Euro

7. Trade total result 0 Euro

8. Trade total result 5 Euro

Here you can see the **biggest negative difference** of 15 Euro. From the 3rd trade with 10 euro credit until the 8th trade with 5 euro loss, **results** in an **account decline** of 15 euros. **Note:** This calculation is only half the truth, because the loss could be much greater until the time the trade is turned off. So it would be possible that in the 8.Trade, the loss of for example -15 euros moves, then recovered and stopped at -5 euros. In this case, the backtest would have an account decrease with the amount of 25 euros. Unfortunately **for some backtest** only this **account balance** will be **shown** with a **green line in the diagram**.

__“Sich“ – Safety factor__

The **safety factor is the safety factor of the entire test period**. This factor is one of the** most important factors** in the **whole table**, as it is a **safety factor** it is much **higher** than the **profit factor** or the **profit level.**

Safety factor = Total profit / largest account decline

That means **the higher** the **safety factor**, **the more secure** the **Expert Advisor**.

Let’s assume the safety factor has a value of 10. That means that the profit is 10 times bigger than the largest account decline. **This factor** also allows you to **see** **if** **all values have been shown** in the graph. **Should** this **factor** shrink in the actual trade or **shrink** several times, then this would be a **sign** that the **optimization** of the program should be **renewed** by the developer. Incidentally, it is also possible to perform your own optimization. You always have the option to reset the program to the defaults of the developer.

__“Stab“ – Stability factor__

The **stability factor** **of the entire test period serves as a supporting value** of the **safety factor of the entire test period**, and the higher the value the better.

Stability factor = Safety factor x number of trades x number of test years x 0.1

Let’s assume the first EA has reached a maximum account decline of 50 euro and a final gain of 100 euro over a one-year trial period only through a single trade. And assuming a second EA, has also a maximum account decline of 50 euro and a final profit of 100 euro over a one-year trial period, but only after the 100th trades. In that case both have reached a safety factor of 2.

**In this** extreme **example**, you **can see** that the **number** of **trades** have a **significant role** in the **stability factor**. If the first EA traded a loss on the second trade, that loss would most likely be so high that the gain no longer exists. In contrast, the **step size** of the second EA is much **smaller**, so it **needs many trades** to **reduce** the** profit to zero**. Therefore, a **probability calculation** for the stability factor is included in the **number** of **trades**. Furthermore, the test period for stability also has a major role. So you could be lucky for a short test period. The longer the test period, the lower the luck factor has on the result. The 0.1 are only used to reduce the output number.

Note: The stability factor should initially only serve as information, since the table still contains the “stability factor after the first year”, and where you can still regulate the output value of the leftover EAs, for a final output.

__“Prof x Sich“ – Combination factor__

The tenth column **shows** me a **combination** of **profit factor** and the **safety factor**. **The higher** this **factor**, **the better** it is. Calculation **combi factor** = **profit factor x safety factor**

__“Zt-Per.“ – Trading period__

Here is the **time period** in **which the Expert Advisor is active**. Each Expert Advisor **has been reconciled** or optimized **by the developer** on one or more financial instruments such as the currency pair EURUSD with the **trading period** example M15 (15 minutes). So it **is** also **necessary** that the **Expert Advisor** **is placed exactly on** this currency pair with the developer-optimized **trading period** to ensure **proper program control**.

__“Balk.Anz“ – Number of bars__

The number of bars indicates **how many bars** the **strategy tester** has **worked through**. This number **depends** on the **size** of the **trading period**, **as well as** the length of the **period** plus 1000.

Since the strategy tester requires a lead time for indicators, an additional 1000 bars are added. Assuming the strategy tester runs 10 working days with a trading period of H1 (H stands for hour) then the strategy tester would have an output value of 10 days by 24 hours +1000 = 1240 bars in the test.

__“Anz.-Tg“ – Number of test days__

The number of days of testing indicates** how many working days** or **test days** have **been checked**. As in the previous example, the recalculation (1240 bars-1000) / 24 = 10 days

__“Anz.-Mt“ – Number of test months__

Number of **test months**

Note: The minimum test time in the backtest should be at least 10 months

__“Anz.-J“ – Number of test years__

Number of **test years**

__“Prof./Tg“ – Profit per day__

**Average profit per day** = profit / day

__“Prof/Einl.“ – Profitability__

**Profit** **depending** on the **first deposit** (account deposit). **Profitability** = Total profit / account deposit

__“Prof./1.J/Einl“ – Return after the first year__

The **return after the first year** is also a very** meaningful value for** the **quality of the Expert Advisor**, and is calculated from the profit after the first year of the first deposit. Yield per year = Prof./1.J / Account deposit. The higher this value, the better and more efficiently the Expert Advisor works. Thus, an Expert Advisor with a return after the first year = 2 would have earned twice the profit of an account deposit after the first year.

__“Prof./1.J“ Profit after the first year__

Is the profit after the first year. For testing times less than one year and over one year, a probability calculation of the profit after the first year is applied. This calculation is calculated and evaluated on EAs with fixed trading volumes, but also on dynamic trading volumes with a corresponding dynamic and fixed trading volume share.

*What is a trading volume*

Trading volume or trading size is given in lot. Ein **Standardlot** ist die **Handelsgröße** von **100.000** der **Ersten Währung** eines **Währungspaares**. A **standard lot** is the **trading size** of **100,000** the **first currency** of **a currency pair**. Thus, a **standard lot** in the currency pair **EURUSD** would have the trading size of **100,000** euros. Let’s stay with the example currency pair **EURUSD**. There are brokers which only offer mini solders as the smallest trading level. A **mini lot** would be **0.1 lot** and would have a trading size of **10,000 euros**. Most brokers offer micro lots. A **micro lot** would be **0.01 lot** and would have a trading size of **1000 euros**. Very rarely there are brokers who offer nano solder. A **nano lot** would be in this case** 0,001 Lot** and would have a trading size of **100 Euro**

**Expert Advisor with Dynamics Lot Systems or Fix Lot Systems and their trading sizes**

**There** are two groups for the **plumb billing** of the Expert Advisor. The **main group** consists of the **Fix Lot System** and the **Dynamik Lot System.** Then there are the **subgroups** which work with **martingale systems** and **grid systems** as well as a **pure fix-solder system.** But let’s start with the main group first and the subgroups later.

**Difference between the dynamics solder system and fix solder system**

The **difference** between the **dynamics solder system** and fix solder system is that the dynamics solder system operates at a specified percentage **as compound interest**. This means that in the dynamics lot system, the current **account balance** for **calculating** the **trade size** participates with a specified percentage. For example, the Expert Advisor would set a trade size of 0.1 Lot from a balance of 1000 Euro, with a percentage also called Leverage of 10%. Calculation: **Dynamics Lot Size = (account balance** x **percentage) / 100,000 (standard lot).** If the account balance were 2000 euros at a percentage of 10%, then the Expert Advisor would set a trading size of 0.2 lots. In order to perform a calculation for the profit after the first year, the specified percentage is calculated on a fixed interest rate of the dynamic lot rate, the remaining part of 100% is calculated as a natural account increase by the Fixlotanteil and combined to a result.

For a **fix lot system**, the **account balance** is not **included** in the trade size calculation. Should the system run on the basis of a **pure Fix Lot system**, the **trading size would always be the same. **In this case, the formula would be [Prof./1.J] = profit / years

__“Kont-R/1.J“ Biggest account decline after the first year__

Is the biggest account decline after the first year. For test times less than one year and over one year, a probability calculation of the biggest account decline after the first year is used. This calculation is calculated and evaluated on EAs with fixed trading volumes, but also on dynamic trading volumes with a corresponding dynamic and fixed trading volume share.

*Evaluation for Kont-R/1.J*

In a fixed-lot system, I assume that the largest account decline can occur at any time because the lot size is always the same. Therefore Largest Account Drop = Largest Account Drop. In a dynamic pilot system, the cont.R / 1.J is computed and evaluated accordingly, as in the case of Prof./1.J, by a dynamic soldering component and a fixed soldering component. The difference in the calculation lies in the distribution, since the fixed lot share is not subject to any division and is always taken over 1 to 1.

__“Sich./1.J“ – Safety factor after the first year__

The calculation **Safety factor** **after the first year** is only a **checkpoint** or **clue**, and should **not be less** **than** the **setting** of the **safety factor of the entire test period.**

Exapmle: The safety factor of the entire test period has been set to a minimum value of 10, then the adjustment of the safety factor after one year should not fall below this value.

Furthermore, the safety factors always form a fixed ratio between the profit and the largest account decline. Sich./1.J = [Prof./1.J] / [Kont-R / 1.J]

__“H.Akt/J“ Trade actions per year__

The **trade actions per year** show an average of **how many times** the **Expert Advisor** **has executed an order** in one year.

H.Akt / J = number of commercial actions total / trial period Ges.

__“Stab./1.J“ – Stabilty factor after the first year__

**The stability factor after the first year shows the stability as well as the final quality of an EAs. ****So the larger the value, the better** and is used to sort out the remaining EAs. Stab./1.J = [Sich./1.J] x number of trades x number of test years x 0.1

You probably already wondered at the biggest contraction of the account after one year on the basis of the fixed-lot system, how the quality is calculated by a longer test period. With this formula you will now find your answer.

__“Spread“ – Spread size__

Here are **displayed** the **spreads in pipettes** with which spread size the program was optimized. Each broker requires **fees** on each** trading order** and in most cases these fees are paid in the form of spread.

*Course changes and their units*

To better understand the spread cost, we first need the price unit. In **forex trading**, the **price change** of a currency pair is** indicated in the unit pip**. For exchange rates that only have one decimal place, as in the example EUR / USD, the price change from 1.179**0** to 1.179**1** corresponds to one pip, which corresponds to an exchange rate change of 0.000**1**. For the yen pairs, one pip would be a change of 0.0**1**.

Cost calculation of 1Pip: Pip costs in Euro = 1Pip / Current Price EURUSD x Sstandard lot

Pip costs in Euro = 0.0001 / 1.1790 x 100.000 = 8.48 €

Most brokers also offer a fifth decimal place. The **fifth decimal place** would be called a **pipette**.

*How does a spread billing work?:*

Depending on the **broker** and **currency pair**, the broker raises **more or less fees**. For example, a broker might ask for 1Pip or multiple pips on a trade order.

Example: We want to carry out a trading order on the EURUSD currency pair, and suppose the current EURUSD price is currently at 1.1790. Now we make a **buy order** (buy order = buy or long order) the size **of a lot**, then the price **rises** by **5 pip**, so that the current exchange rate is 1.1795. Now we close the order and we would normally have made a profit of 5 pips. But since the broker demands a **fee** of **1 pip**, we ultimately only earned a profit of 4 pips.

Profit = 0,0004/1,1790 x 100.000 = 33,32 €

Another example of the current EURUSD price is 1.1790 and we would execute a **sell order** (sell order = sell or short order) the size of **one lot**, then the **price rises** by **5 pips** so that the current exchange rate is 1.1795. Now we close the order as we believe the price would continue to rise. In this case, we would have **lost 5 pip**. Since the **broker** demands a **fee** of **1 pip**, we ended up trading a **loss** of **6 pips.**

Loss= 0,0006/1,1790 x 100.000 = 50,89 €

**Why is the spread so important for a correct program flow?**

Let’s say we have to pay two pips (2 pip = 20 pipettes) in spread, but the **program** has been **optimized for just a pip** of **spread**, and let’s say the program is executing a buy order and is taking a take profit of 5 pips above the current exchange rate. In order to achieve the take profit, the price now would have to rise by seven pips, so that the order is closed by the take profit. The **7 pips result** from the **2 pips** **spread** and **5 pips** from the **current price** **to** the **take profit**. Now, **the exchange rate** only **increases** by **6 pips**, which would have been enough for a spread of one pip to capitalize on the take profit and close the order with a profit **but now** the **price** **goes down** as far as one **stop los** is **activated** and the order **closes** with a **minus.**

This means that a **larger spread** could **upset** the entire **logistics** of a program. Therefore, the **spread** is **very important!** **Especially** **with small trading periods**, for example M1 of the smallest trading period which can lead **to** serious differences and so** to a large loss.**

noticeable rate: The smaller the spread the better and more profitable the Expert Advisor!

__“Instr.“ – Financial instrument__

Shows on which **financial instrument** the **optimization** **was carried out** and on which financial instrument has to be** traded afterwards.**

__“Anz-H.Akt“ – Number of commercial actions__

The **number of trades** shows **how often** the **Expert Advisor** has **completed an order** throughout the trial period. If the **Expert Advisor** were aligned for a **pure Fix Lot system**, you would have the possibility to roughly **calculate** the **spread costs.** A precise calculation is not possible because we are not aware of the current price for each individual order.

**Total trades and impact of spread costs on the final result**

Example: Spread costs of EURUSD are two pips at a rate of 1.1790. The fix lot would have a trading size of 0.1 lot. Number of trades are 8280 trades

Cost at Spread = (Pips / Current Price) x (Standard Lot / 10) x Number of Trades

Cost at Spread = 0.0002 / 1.1790 x 10.000 x 8280 = 14.045,8 €

So you can see that the **spread costs** contribute a **very high** share of the costs of the** final result.**

If we had only **1 pip** of **spread costs**, the costs would be cut in half and the profit would be higher by that amount. This example with 8280 trades was taken from an Expert Advisor with a one-year trial period and a M15 trading period.

__“Start-L“ Start-Lot__

Here is speciefied the **start lot size. **If it is a **fix lot system**, the **first** **trade always starts with this trade size.** **In** a **dynamics lot system**, **this lot size is considered safe only for the first trade.**

__The calculation for the lot size in a dynamics solder system __

Dynamic Lot Size = (Account Balance x Percent) / 100,000 (standard Lot)

For example, the **Expert Advisor** would set a trade size of **0.1 Lot** out of a balance of **1000 Euro** or a **percentage** called leverage or risk of **10%**.

**If** the **account balance **were **2000 euros at** a **percentage** of **10%** then the **Expert Advisor** **would** **set** a trading size of **0.2 lot** as Start Lot.

Some Expert Advisor with a dynamics lot system have a start lot explicitly for launch which is independent involved in the account balance in the program.

This is usually the case for programs that start with a small account to first generate a certain account size and then switch to the dynamics system. Most programs start with a small account balance with the smallest lot size of 0.01 Lot until the account balance has grown enough to switch to a lot size 0.02 Lot.

__“D-F“ – D-F Lot__

This column indicates whether it is a Fix Lot System or a Dynamics Lot System.

Note: **Whether** a **martingale system or** a **grid system is integrated can not be ruled out.**

__“D%“ – Specification of the percentage for a dynamic solder__

This column indicates the **percentage** in which the dynamics lot system calculates the lot size **depending on the account balance.**

__The calculation for the lot size in a dynamics solder system__

Dynamic Lot Size = (Account balance x percentage) / 100,000 (standard lot)

__“N“ – No grid no martingale__

Here are specified only the **lot sizes** of **Expert Advisors** which **explicitly** refer to the description **of no grid system** and **no martingale system.** This does not mean that only those Expert Advisor exist who are working on a pure Fix Lot System or a pure Dynamics Lot System. This was not addressed by the developer for many pure fix solder systems and pure dynamics solder systems. A** pure dynamics solder system** **does not** include **a martingale system** or a **grid system.** A **pure fix solder system does not** include a **martingale system, a grid system** or a **dynamics solder system.**So that an approximate recalculation to spread costs would be possible.

The main groups Fix Lot and Dynamik Lot already have been mentioned in the upper section. What is missing is the subgroup like Martingale System and the grid system.

*What is a martingale system:*

Although a **Martingale system** has a higher level of logistics than a grid system both systems are dangerous systems, as the **trading sizes are determined by multipliers** in order to force a profit.

A simple example: The program executes a **buy order** with a **lot size of 0.1 lot** instead of rising the price and making a profit, **the price drops.** Due to the internal logistics of the program (this could be caused for example by an indicator built into the program) the program executes another buy order after a **loss** of** 9 pips** but this time with the **double bet** (multiplier = 2) so that the** lot size is 0,2 lot.**

Apart from the spread, the B**reak Even Point** which is the **point** that **leads back into profit**, would have been **reached** with a **rise of 3 pips.**

__Short Break Even Point calculation:__

In this calculation, the spread costs are not calculated!

The calculation assumes an assumption of 1 euro in the trade size of a minilot (1 minilot = 0.1 lot) per pip.

1.Buy order with 0.1 lot price drops 9 pips thereafter the price recovers by 3 pips so the end point is in minus with 6 pips (loss 6 euros)

The second buy order was executed after the first order of 9 pips in minus, with 0.2 lot, then the price rises by 3 pips so there appears a profit of 6 euros for this order.

To sum up, the 1st order would have a current minus of 6 euros and the 2nd order a current profit of 6 euros therefore the sum = 0 = Break Even Point

__Back to our Martingale System__

We are now playing this game forward. The **price drops further** and the program creates **another Buy Order** this time with** 0.4 lot**, the **next** one would be **0.8 lot** … etc. This process goes so far **until** the price rises again and **enters the profit zone.**

__What happens if the price is no longer in profit__

The **programs** are still **equipped with** other **security factors** so the program could **intervene** with a **Counter-order** (called hedge) or through an order that uses the money management. This means that the decline is included in the account balance. Thus, a logistics could be included in the program that says, that after a **maximum account decline**, for example, of 10%, **all orders of the account balance are closed.**

**Or**, the third option would be, the **margin** has been **used up** so the **broker** **closes** the **orders.**

*What is a Margin*

This **financial trading based on CFDs** **means contract for difference.** You **buy (also called long) or sell (also called short) at a current price **and **close** the **order at another price**, this **creates a difference.** The **advantage** with **CFDs** one **can move a large capital** **without** **having** the **necessary money** for it. **Depending** on the **broker** **and trading instrument you get** **a lever** that is **100 times** to **400 times higher** **than the capital** **that** you have to **deposit for it.** For **example**, if we take the **EURUSD**, **1 lot would be 100,000 euros.** **With a leverage** **of 100**, **a margin** **of 1%** of **collateral** would have to be **deposited for the Broker.** In this case, this **would be 1000 euros **and we would **move** a **trade size of 100,000 euros** with it. **Since** we **still have spread costs** **on an order**, the **margin would not be sufficient**, **so** **that** is is **not feasible** with a deposit of 1000 euro **trading** with 1 lot. **But** let’s assume we would **close a deal **with **a deposit** of EUR 1000 on the EURUSD currency pair and put **0.2 on long** which would mean we are **raising** a total of **EUR 20,000.** Now the **price** is **falling** and we are **already** down by **100 Euro**, we **double** the bet with a new order and go with** 0.4 Lot on Long. ****Now** we are already **moving** a sum of **60,000 euros.** The **necessary margin would be 600 euros** in this case.

**After** we are **already in the minus with 100 euros**, we are only more **300 euros** **to the margin call** of 1000 euros **away.** The **course keeps falling,** so that **these 300 euros are lost. ** **Now** we **only** have **600 euros** from 1000 euros left. This is **exactly the amount which is deposited as a margin. **The **price continues to fall** **and** now you **receive a Margin Call message** that the **margin is insufficient.** Now we **want to open a short position as a counterorder** called **hedge** in the size of **0.2 lot.** **Since** the **margin** has already fallen below, you will **receive the message** that you can no **longer execute a new order** because the margin has already fallen below. **Now** you have the **option** to **close** one **Order **after another **or** you have to **wait** even **longer.** **Depending on the broker**, this can **lead to total loss.** **Some brokers stop** all **orders** **when** the **required margin is only 10%.** You would only have an **account balance** of **60 euros** **by then.**

*What is a grid system:*

The **grid system** also uses **multipliers for trade size** calculation. The **difference** to the **Martingale system,** the **Grid system works with** a **rigid structure** of pending order. **For this purpose**, **pending orders** with an **ever higher lot** are **used at regular intervals.**

Note: **For** most Expert Advisor’s, the **drawdowns are always very large** which include a **martingale system** or a **grid system. **You can see that in some **diagrams** **looking at a green line.** For **some**, these** lines are extremely down.** Since this **green line** is not **always shown**, our **safety factor calculation helps us** to present a comparison between profit and maximum drawdown.

*What is a Pending Order:*

**A pending order** is placed at a** distance** in a **kind of waiting position** from the current **course status.** **Should** the **course** **status** **reach** the **pending order**, this **pending order will be activated.**

__There are several types of pending orders__

The **Pending Order** **Buy Limit**: This order will be **placed below the current course.** Should the **course** **fall** and reach the pending order, a **long order** (buy order) will be executed.

The **Pending Order** **Sell Limit**: This order will be **placed above the current course**. Should the **course rise** and reach the pending order, a **short order** (sell order) will be executed.

The **Pending Order** **Buy Stop**: This order will be **placed above the current course**. Should the **course rise** and reach the pending order, a **long order** (buy order) will be executed.

The **Pending Order** **Sell Stop**: This order will be **placed below the current course.** Should the **course fall** and reach the pending order, a **short order** (sell order) will be executed.

__“Kl.Pr/J“ – Lowest price per year__

The lowest price of an EAs for a year of use is a crucial point in sorting out the last EAs and for that reason it is mentioned again.

__“Kl.Pr“ – Lowest price__

The lowest price of an EA is a crucial point to sort out the last EAs and therefore stated here again.

__“Anz.-NuMt“ – Number of working months__

The useful life in months of an EA, if the smallest price for use by a rent arises is a crucial point to the sorting out of the last EAs and is indicated therefore again.

__“Opt. Einl.“ – Optimized account deposit__

The optimal account deposit of the respective EA will be calculated on the basis of the smallest possible starting slot in connection with the starting lot of the test result and the largest account decline after the first year. So the optimal account deposit should be 10 times larger than the optimized largest account decline. If you fall below the 10 times the size of the account deposit, the optimal account deposit increases each by $500.

__“Opt. HV“ – Optimal trading volume__

Here is determined the optimal lot size of the trading volume as a function of the optimal account deposit and the largest account decline after the first year. The lot size is regulated in such a way, that in each optimal account deposit of each EA, approximately the same maximum account reductions arise.

__“Opt. JProf.“ Optimized year profit
__

Here is calculated the optimized annual profit from the previously calculated optimal trading volume and the profit after the first year.

__“Opt. JKonto-R“ – Optimized largest annual account decline
__

Here is calculated the optimized largest annual account decline in terms of the optimal account deposit, depending on the previously optimal calculated trading volume, as well as the largest account decline after the first year.

*Note: All these values per year are assumptions made by calculations to form a common denominator of all EAs. Exceptions are only EAs which were tested exactly to an annual length. Of course, this also includes the self-tests that are not only tested to exactly one year’s length but also form a common denominator over time.*

__“Bez.“ Designation__

If there is something wrong with the entry of the values in a line then you have the option of sending a message to us by the meaning of this name. Furthermore, this column is used to filter individual lines.

__“Image“__

If the check is made by us, a link to our image is implemented of the test result here.

__“EA“ (Expert Advisor) Product link button__

In this column are embedded the EA product link button which redirects our customers to the desired product.