Forex analytics native module for Node.js
Node.js native library performing technical analysis over an OHLC dataset with use of genetic algorithm. The result of technical analysis are two binary trees describing strategies for buy and sell signals which produced profit in a certain period of time specified by the input OHLC data set.
Running the source
First if you don't have it yet. Install node-gyp for comiling the c++ source code;
npm install -g node-gyp
Then run the install npm command to download and install all dependencies. It also compiles the ta-lib dependency and builds the source code
npm install
To do further builds you can use
node-gyp build
You can run embedded examples which are located in the examples folder
cd examples
node example
NPM
You can install forex.analytics via npm:
npm install forex.analytics
Usage
Import the the module
var analytics = require('forex.analytics');or with ES6 modules syntax
import analytics from 'forex.analytics'Analytics object will give you several functions to use.
findStrategy(candlesticks, options, progressCallback)
Finds the optimal strategy for a certain period defined by the candlesticks array.
candlesticks parameter should contain an array of objects representing one candlestick in OHLC chart.
{
open: 1.113990,
high: 1.113990,
low: 1.113890,
close: 1.113890,
time: 1435701600
}options parameter lists several properties that influence the genetic algorithm
{
populationCount: 100,
generationCount: 300,
selectionAmount: 10,
leafValueMutationProbability: 0.5,
leafSignMutationProbability: 0.3,
logicalNodeMutationProbability: 0.3,
leafIndicatorMutationProbability: 0.2,
crossoverProbability: 0.03,
indicators: [ 'CCI', 'MACD', 'RSI', 'SMA15_SMA50' ],
strategy: { buy : {...}, sell : {...} }
}progressCallback parameter has to be a function. This function is invoked when one generation passes. It contains three arguments: strategy, fitness, generation. Where strategy stands for the currently best strategy found in a certain generation. Fitness is a fitness value of a certain strategy calculated by fitness evaluation algorithm. Generation is the number of generation which was just completed. The strategy parameter describes which strategy it shall use as a referential. This parameter is not mandatory.
function progressCallback(strategy, fitness, generation) {
console.log('Fitness: ' + fitness + '; Generation: ' + generation);
}could print
Fitness: 0.00010751596495091384; Generation: 285
The returning value is a promise which when it's resolved passes one argument with the best found strategy.
Full example:
analytics.findStrategy(candlesticks, {
populationCount: 100,
generationCount: 300,
selectionAmount: 10,
leafValueMutationProbability: 0.5,
leafSignMutationProbability: 0.3,
logicalNodeMutationProbability: 0.3,
leafIndicatorMutationProbability: 0.2,
crossoverProbability: 0.03,
indicators: indicators
}, function(strategy, fitness, generation) {
console.log('Fitness: ' + fitness + '; Generation: ' + generation);
})
.then(function(strategy) {
console.log('------------Strategy-------------')
console.log(strategy);
});This could print something like:
Fitness: 0.0; Generation: 1
....
Fitness: 0.00010751596495091384; Generation: 297
Fitness: 0.00010751596495091384; Generation: 298
Fitness: 0.00010751596495091384; Generation: 299
Fitness: 0.00010751596495091384; Generation: 300
------------Strategy-------------
{
"buy":{
"operator":"And",
"left":{
"operator":"Or",
"left":{
"indicator":"Momentum",
"sign":">",
"value":-0.8390790893276773
},
"right":{
"indicator":"RSI",
"sign":">",
"value":74.22093161865811
}
},
"right":{
"operator":"And",
"left":{
"indicator":"Momentum",
"sign":"<",
"value":-0.6815039536729026
},
"right":{
"indicator":"Momentum",
"sign":"<",
"value":-0.32888175664540553
}
}
},
"sell":{
"operator":"And",
"left":{
"operator":"Or",
"left":{
"indicator":"Momentum",
"sign":">",
"value":-0.8390790893276773
},
"right":{
"indicator":"RSI",
"sign":">",
"value":74.22093161865811
}
},
"right":{
"operator":"And",
"left":{
"indicator":"Momentum",
"sign":"<",
"value":-0.6815039536729026
},
"right":{
"indicator":"Momentum",
"sign":"<",
"value":-0.32888175664540553
}
}
}
}
convertOHLC(candlesticks, targetTimeframe)
Converts OHLC data set to a larger timeframe (e.g. from 5 minute interval to 30 minute interval)
candlesticks parameter should contain an array of objects representing one candlestick in OHLC chart.
{
open: 1.113990,
high: 1.113990,
low: 1.113890,
close: 1.113890,
time: 1435701600
}targetTimeframe parameter defines the target interval in seconds
Example:
/**
* Converts candlesticks from lower timeframe to 30 minute timeframe
*/
function convertTo30MOhlc(candlesticks) {
return analytics.convertOHLC(candlesticks, 1800);
}This function can be used for converting ticks to OHLC as well with a simple trick.
/**
* Converts ticks to one minute OHLC
* Input could be for example: { time : 0, value : 1.225 }, { time : 10, value : 1.226 },
* { time : 20, value : 1.227 }, { time : 30, value : 1.228 }, ...
*/
function ticksTo1MOhlc(ticks) {
return analytics.convertOHLC(candlesticks
.map(t => {
open: t.value,
high: t.value,
low: t.value,
close: t.value,
time: t.time
}), 60 /* one minute interval */);
}getMarketStatus(candlesticks, options)
Returns suggestion whether to buy or sell current for the last candlestick in the candlesticks array passed in as a first parameter.
candlesticks parameter should contain an array of objects representing one candlestick in OHLC chart.
{
open: 1.113990,
high: 1.113990,
low: 1.113890,
close: 1.113890,
time: 1435701600
}options parameter lists one property
{
strategy: { buy : [...], sell : [...] }
}strategy is the result from the findStrategy function and defines when to buy and when to sell.
Example:
var status = analytics.getMarketStatus(candlesticks, { strategy: strategy });
console.log(status);Can output:
{ shouldBuy: true, shouldSell: false }
getTrades(candlesticks, options)
Returns an array of trades that were performed on a provided candlestick array with given strategy candlesticks array passed in as a first parameter.
candlesticks parameter should contain an array of objects representing one candlestick in OHLC chart.
{
open: 1.113990,
high: 1.113990,
low: 1.113890,
close: 1.113890,
time: 1435701600
}options parameter lists one property
{
strategy: { buy : [...], sell : [...] }
}strategy is the result from the findStrategy function and defines when to buy and when to sell.
Example:
var trades = analytics.getTrades(candlesticks, {
strategy: strategy
});
console.log(trades);Can output:
[
{
"Buy":true,
"Revenue":0.0031200000000000117,
"MaximumLoss":0.0023200000000000998,
"MaximumProfit":0.005009999999999959,
"ProfitBeforeLoss" : true,
"start":{
"open":1.10604,
"low":1.10586,
"high":1.10762,
"close":1.10711,
"time":1435782600
},
"end":{
"open":1.10833,
"low":1.10833,
"high":1.11044,
"close":1.11023,
"time":1435824000
}
}
]
Where buy stands for whether the specific trade was made on a profit from a rising or falling market.
Revenue is the the revenue that was obtained at the end of a trade.
MaximumLoss describes how far the price movement went against the wanted direction. MaximumProfit describes how far the price movement went on the wanted direction. start and end are the candlesticks describing the boundaries of a given trade. ProfitBeforeLoss indicates whether the maximum profit was reached before maximum loss
Roadmap
- Stabilize the solution / fix bugs
- Make the algorithm more abstract (support for different kind of chromosomes and tree nodes)
- Delegate indicator generation to a different library (perhaps use node-talib)
- Implementing support for generating indicators (math formulas with OHLC as an input) based on successful trades
- Think of more stuff to add. :)