Align edge documentation to configuration page
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docs/edge.md
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docs/edge.md
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# Edge positioning
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# Edge positioning
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This page explains how to use Edge Positioning module in your bot in order to enter into a trade only if the trade has a reasonable win rate and risk reward ratio, and consequently adjust your position size and stoploss.
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@ -9,6 +9,7 @@ This page explains how to use Edge Positioning module in your bot in order to en
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Edge does not consider anything else than buy/sell/stoploss signals. So trailing stoploss, ROI, and everything else are ignored in its calculation.
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## Introduction
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Trading is all about probability. No one can claim that he has a strategy working all the time. You have to assume that sometimes you lose.
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But it doesn't mean there is no rule, it only means rules should work "most of the time". Let's play a game: we toss a coin, heads: I give you 10$, tails: you give me 10$. Is it an interesting game? No, it's quite boring, isn't it?
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@ -22,43 +23,61 @@ Let's complicate it more: you win 80% of the time but only 2$, I win 20% of the
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The question is: How do you calculate that? How do you know if you wanna play?
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The answer comes to two factors:
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- Win Rate
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- Risk Reward Ratio
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### Win Rate
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Win Rate (*W*) is is the mean over some amount of trades (*N*) what is the percentage of winning trades to total number of trades (note that we don't consider how much you gained but only if you won or not).
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W = (Number of winning trades) / (Total number of trades) = (Number of winning trades) / N
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```
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W = (Number of winning trades) / (Total number of trades) = (Number of winning trades) / N
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```
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Complementary Loss Rate (*L*) is defined as
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L = (Number of losing trades) / (Total number of trades) = (Number of losing trades) / N
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```
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L = (Number of losing trades) / (Total number of trades) = (Number of losing trades) / N
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```
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or, which is the same, as
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L = 1 – W
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```
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L = 1 – W
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```
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### Risk Reward Ratio
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Risk Reward Ratio (*R*) is a formula used to measure the expected gains of a given investment against the risk of loss. It is basically what you potentially win divided by what you potentially lose:
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R = Profit / Loss
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```
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R = Profit / Loss
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```
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Over time, on many trades, you can calculate your risk reward by dividing your average profit on winning trades by your average loss on losing trades:
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Average profit = (Sum of profits) / (Number of winning trades)
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```
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Average profit = (Sum of profits) / (Number of winning trades)
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Average loss = (Sum of losses) / (Number of losing trades)
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Average loss = (Sum of losses) / (Number of losing trades)
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R = (Average profit) / (Average loss)
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R = (Average profit) / (Average loss)
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```
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### Expectancy
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At this point we can combine *W* and *R* to create an expectancy ratio. This is a simple process of multiplying the risk reward ratio by the percentage of winning trades and subtracting the percentage of losing trades, which is calculated as follows:
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Expectancy Ratio = (Risk Reward Ratio X Win Rate) – Loss Rate = (R X W) – L
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```
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Expectancy Ratio = (Risk Reward Ratio X Win Rate) – Loss Rate = (R X W) – L
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```
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So lets say your Win rate is 28% and your Risk Reward Ratio is 5:
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Expectancy = (5 X 0.28) – 0.72 = 0.68
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```
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Expectancy = (5 X 0.28) – 0.72 = 0.68
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```
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Superficially, this means that on average you expect this strategy’s trades to return .68 times the size of your loses. This is important for two reasons: First, it may seem obvious, but you know right away that you have a positive return. Second, you now have a number you can compare to other candidate systems to make decisions about which ones you employ.
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@ -69,6 +88,7 @@ You can also use this value to evaluate the effectiveness of modifications to th
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**NOTICE:** It's important to keep in mind that Edge is testing your expectancy using historical data, there's no guarantee that you will have a similar edge in the future. It's still vital to do this testing in order to build confidence in your methodology, but be wary of "curve-fitting" your approach to the historical data as things are unlikely to play out the exact same way for future trades.
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## How does it work?
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If enabled in config, Edge will go through historical data with a range of stoplosses in order to find buy and sell/stoploss signals. It then calculates win rate and expectancy over *N* trades for each stoploss. Here is an example:
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| Pair | Stoploss | Win Rate | Risk Reward Ratio | Expectancy |
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@ -83,6 +103,7 @@ The goal here is to find the best stoploss for the strategy in order to have the
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Edge module then forces stoploss value it evaluated to your strategy dynamically.
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### Position size
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Edge also dictates the stake amount for each trade to the bot according to the following factors:
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- Allowed capital at risk
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@ -90,13 +111,17 @@ Edge also dictates the stake amount for each trade to the bot according to the f
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Allowed capital at risk is calculated as follows:
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Allowed capital at risk = (Capital available_percentage) X (Allowed risk per trade)
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```
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Allowed capital at risk = (Capital available_percentage) X (Allowed risk per trade)
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```
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Stoploss is calculated as described above against historical data.
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Your position size then will be:
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Position size = (Allowed capital at risk) / Stoploss
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```
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Position size = (Allowed capital at risk) / Stoploss
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```
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Example:
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@ -115,100 +140,30 @@ Available capital doesn’t change before a position is sold. Let’s assume tha
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So the Bot receives another buy signal for trade 4 with a stoploss at 2% then your position size would be **0.055 / 0.02 = 2.75 ETH**.
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## Configurations
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Edge module has following configuration options:
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#### enabled
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If true, then Edge will run periodically.
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(defaults to false)
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#### process_throttle_secs
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How often should Edge run in seconds?
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(defaults to 3600 so one hour)
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#### calculate_since_number_of_days
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Number of days of data against which Edge calculates Win Rate, Risk Reward and Expectancy
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Note that it downloads historical data so increasing this number would lead to slowing down the bot.
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(defaults to 7)
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#### capital_available_percentage
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This is the percentage of the total capital on exchange in stake currency.
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As an example if you have 10 ETH available in your wallet on the exchange and this value is 0.5 (which is 50%), then the bot will use a maximum amount of 5 ETH for trading and considers it as available capital.
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(defaults to 0.5)
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#### allowed_risk
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Percentage of allowed risk per trade.
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(defaults to 0.01 so 1%)
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#### stoploss_range_min
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Minimum stoploss.
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(defaults to -0.01)
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#### stoploss_range_max
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Maximum stoploss.
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(defaults to -0.10)
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#### stoploss_range_step
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As an example if this is set to -0.01 then Edge will test the strategy for \[-0.01, -0,02, -0,03 ..., -0.09, -0.10\] ranges.
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Note than having a smaller step means having a bigger range which could lead to slow calculation.
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If you set this parameter to -0.001, you then slow down the Edge calculation by a factor of 10.
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(defaults to -0.01)
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#### minimum_winrate
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It filters out pairs which don't have at least minimum_winrate.
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This comes handy if you want to be conservative and don't comprise win rate in favour of risk reward ratio.
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(defaults to 0.60)
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#### minimum_expectancy
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It filters out pairs which have the expectancy lower than this number.
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Having an expectancy of 0.20 means if you put 10$ on a trade you expect a 12$ return.
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(defaults to 0.20)
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#### min_trade_number
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When calculating *W*, *R* and *E* (expectancy) against historical data, you always want to have a minimum number of trades. The more this number is the more Edge is reliable.
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Having a win rate of 100% on a single trade doesn't mean anything at all. But having a win rate of 70% over past 100 trades means clearly something.
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(defaults to 10, it is highly recommended not to decrease this number)
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#### max_trade_duration_minute
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Edge will filter out trades with long duration. If a trade is profitable after 1 month, it is hard to evaluate the strategy based on it. But if most of trades are profitable and they have maximum duration of 30 minutes, then it is clearly a good sign.
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**NOTICE:** While configuring this value, you should take into consideration your ticker interval. As an example filtering out trades having duration less than one day for a strategy which has 4h interval does not make sense. Default value is set assuming your strategy interval is relatively small (1m or 5m, etc.).
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(defaults to 1 day, i.e. to 60 * 24 = 1440 minutes)
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#### remove_pumps
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Edge will remove sudden pumps in a given market while going through historical data. However, given that pumps happen very often in crypto markets, we recommend you keep this off.
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(defaults to false)
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| Parameter | Description |
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|------------|-------------|
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| `enabled` | If true, then Edge will run periodically. <br>*Defaults to `false`.* <br> ***Datatype:*** *Boolean*
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| `process_throttle_secs` | How often should Edge run in seconds. <br>*Defaults to `3600` (once per hour).* <br> ***Datatype:*** *Integer*
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| `calculate_since_number_of_days` | Number of days of data against which Edge calculates Win Rate, Risk Reward and Expectancy. <br> **Note** that it downloads historical data so increasing this number would lead to slowing down the bot. <br>*Defaults to `7` (once per hour).* <br> ***Datatype:*** *Integer*
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| `capital_available_percentage` | This is the percentage of the total capital on exchange in stake currency. <br>As an example if you have 10 ETH available in your wallet on the exchange and this value is 0.5 (which is 50%), then the bot will use a maximum amount of 5 ETH for trading and considers it as available capital. <br>*Defaults to `0.5` (once per hour).* <br> ***Datatype:*** *Float*
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| `allowed_risk` | Ratio of allowed risk per trade. <br>*Defaults to `0.01` (1%)).* <br> ***Datatype:*** *Float*
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| `stoploss_range_min` | Minimum stoploss. <br>*Defaults to `-0.01`.* <br> ***Datatype:*** *Float*
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| `stoploss_range_max` | Maximum stoploss. <br>*Defaults to `-0.10`.* <br> ***Datatype:*** *Float*
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| `stoploss_range_step` | As an example if this is set to -0.01 then Edge will test the strategy for `[-0.01, -0,02, -0,03 ..., -0.09, -0.10]` ranges. <br> **Note** than having a smaller step means having a bigger range which could lead to slow calculation. <br> If you set this parameter to -0.001, you then slow down the Edge calculation by a factor of 10. <br>*Defaults to `-0.001`.* <br> ***Datatype:*** *Float*
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| `minimum_winrate` | It filters out pairs which don't have at least minimum_winrate. <br>This comes handy if you want to be conservative and don't comprise win rate in favour of risk reward ratio. <br>*Defaults to `0.60`.* <br> ***Datatype:*** *Float*
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| `minimum_expectancy` | It filters out pairs which have the expectancy lower than this number. <br>Having an expectancy of 0.20 means if you put 10$ on a trade you expect a 12$ return. <br>*Defaults to `0.20`.* <br> ***Datatype:*** *Float*
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| `min_trade_number` | When calculating *W*, *R* and *E* (expectancy) against historical data, you always want to have a minimum number of trades. The more this number is the more Edge is reliable. <br>Having a win rate of 100% on a single trade doesn't mean anything at all. But having a win rate of 70% over past 100 trades means clearly something. <br>*Defaults to `10` (it is highly recommended not to decrease this number).* <br> ***Datatype:*** *Integer*
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| `max_trade_duration_minute` | Edge will filter out trades with long duration. If a trade is profitable after 1 month, it is hard to evaluate the strategy based on it. But if most of trades are profitable and they have maximum duration of 30 minutes, then it is clearly a good sign.<br>**NOTICE:** While configuring this value, you should take into consideration your ticker interval. As an example filtering out trades having duration less than one day for a strategy which has 4h interval does not make sense. Default value is set assuming your strategy interval is relatively small (1m or 5m, etc.).<br>*Defaults to `1440` (one day).* <br> ***Datatype:*** *Integer*
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| `remove_pumps` | Edge will remove sudden pumps in a given market while going through historical data. However, given that pumps happen very often in crypto markets, we recommend you keep this off.<br>*Defaults to `false`.* <br> ***Datatype:*** *Boolean*
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## Running Edge independently
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You can run Edge independently in order to see in details the result. Here is an example:
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```bash
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``` bash
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freqtrade edge
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```
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