Indicators

A Java library that provides a variety of technical indicators for time series data, such as OHLC bars.

Installation

For build.gradle.kts:

implementation("trade.invision", "indicators", "1.2.0")

For build.gradle:

implementation group: 'trade.invision', name: 'indicators', version: '1.2.0'

For pom.xml:

<dependency>
    <groupId>trade.invision</groupId>
    <artifactId>indicators</artifactId>
    <version>1.2.0</version>
</dependency>

Usage

There are two base classes in this library to be aware of: Series and Indicator.

Series is a class that provides a simple interface for storing and retrieving values from a series. Values can only be added to the Series, except for the last value, which can be replaced with a new value. When the number of values stored in the Series exceed a configurable maximum upon adding a new value, then values at the beginning of the Series are removed. This emulates the behavior of a bar/candlestick chart that displays historical bars along with a continuously-updating end bar that reflects live trade data. There are two types of Series this library provides: BarSeries (for a series of Bars) and NumSeries (for a series of NumDatapoints).

Indicator is an abstract class for performing calculations on a Series or another Indicator, with optional result caching. An Indicator will implement some formula/algorithm and provide the result of the calculation at a given index. Some Indicator implementations and consumer access patterns may retrieve calculated results at previously-calculated indices. So, in order to prevent redundantly recalculating the results at the same index, the Indicator can cache its results in memory, with the cache size being the same as the Series maximum length. Result caching is disabled by default since the typical access pattern is to continually calculate the Indicator value at the end index of a Series and perform some action based on that result. The cache should be enabled when consumers of an Indicator use the calculated values of non-ending indices, as opposed to only using the calculated value of the end index. Indicator implementations that utilize recursion should extend RecursiveIndicator, which forces caching and prevents StackOverflowError exceptions. Typically, an Indicator will be one of the following three types: Num (decimal number), Boolean (true/false), or Instant (timestamp). Each Indicator implementation provides a public static method for consumers to acquire an instance reference to the Indicator, as the constructor for Indicator implementations is protected and cannot be instantiated directly.

Check out the Javadoc for all classes and method signatures, but here's a simple example:

Imports

import trade.invision.indicators.indicators.Indicator;
import trade.invision.indicators.indicators.barprice.Hlc3;
import trade.invision.indicators.indicators.barprice.Ohlc4;
import trade.invision.indicators.indicators.bullishbearish.global.GlobalBullishPercentage;
import trade.invision.indicators.indicators.crossed.Crossed;
import trade.invision.indicators.indicators.ma.sma.SimpleMovingAverage;
import trade.invision.indicators.indicators.statistical.StandardDeviation;
import trade.invision.indicators.series.bar.Bar;
import trade.invision.indicators.series.bar.BarSeries;
import trade.invision.num.Num;

import java.io.InputStream;
import java.net.URI;
import java.time.Instant;

import static java.lang.Long.parseLong;
import static java.time.Instant.ofEpochMilli;
import static java.time.temporal.ChronoUnit.DAYS;
import static trade.invision.indicators.indicators.bar.Close.close;
import static trade.invision.indicators.indicators.barprice.Hlc3.typicalPrice;
import static trade.invision.indicators.indicators.barprice.Ohlc4.ohlc4;
import static trade.invision.indicators.indicators.bullishbearish.global.GlobalBullishPercentage.globalBullishPercentage;
import static trade.invision.indicators.indicators.crossed.Crossed.crossed;
import static trade.invision.indicators.indicators.ma.MovingAverageSupplier.wwmaSupplier;
import static trade.invision.indicators.indicators.ma.sma.SimpleMovingAverage.simpleMovingAverage;
import static trade.invision.indicators.indicators.rsi.RelativeStrengthIndex.rsi;
import static trade.invision.indicators.indicators.statistical.StandardDeviation.stddev;

final BarSeries barSeries = new BarSeries(20); // Store a maximum of 20 bars in memory
// Get AAPL 1D bar data from 2025-01-01 to 2025-02-01.
try (final InputStream inputStream = URI.create("https://pastebin.com/raw/dnLSgw44").toURL().openStream()) {
    for (String barDataLine : new String(inputStream.readAllBytes()).split("\n")) {
        final String[] barDataCsv = barDataLine.trim().split(",");
        final Instant start = ofEpochMilli(parseLong(barDataCsv[5]));
        final Instant end = start.plus(1, DAYS);
        final Num open = barSeries.numOf(barDataCsv[1]);
        final Num high = barSeries.numOf(barDataCsv[3]);
        final Num low = barSeries.numOf(barDataCsv[4]);
        final Num close = barSeries.numOf(barDataCsv[2]);
        final Num volume = barSeries.numOf(barDataCsv[0]);
        final Num tradeCount = barSeries.numOf(barDataCsv[6]);
        final Bar bar = new Bar(start, end, open, high, low, close, volume, tradeCount);
        barSeries.add(bar);
        System.out.println("Added: " + bar);
    }
}

// Calculate the Simple Moving Average (SMA) using the bar average price.
final Ohlc4 averagePrice = ohlc4(barSeries);
final SimpleMovingAverage sma = simpleMovingAverage(averagePrice, 20);
for (long index = barSeries.getStartIndex(); index <= barSeries.getEndIndex(); index++) {
    System.out.printf("OHLC4 20 SMA at %d: %s\n", index, sma.getValue(index));
}

// Calculate the Standard Deviation (stddev) using the bar typical price.
final Hlc3 typicalPrice = typicalPrice(barSeries);
final StandardDeviation stddev = stddev(typicalPrice, 5, false);
for (long index = barSeries.getStartIndex(); index <= barSeries.getEndIndex(); index++) {
    System.out.printf("HLC3 5 STDDEV at %d: %s\n", index, stddev.getValue(index));
}

// Calculate the Relative Strength Index (RSI) using the bar close price and Welles Wilder Moving Average (WWMA).
final Indicator<Num> close = close(barSeries);
final Indicator<Num> rsi = rsi(close, 10, wwmaSupplier());
for (long index = barSeries.getStartIndex(); index <= barSeries.getEndIndex(); index++) {
    System.out.printf("C 10 RSI at %d: %s\n", index, rsi.getValue(index));
}

// Calculate the percentage of bullish bars.
final GlobalBullishPercentage globalBullishPercentage = globalBullishPercentage(barSeries);
for (long index = barSeries.getStartIndex(); index <= barSeries.getEndIndex(); index++) {
    System.out.printf("Bullish %% at %d: %s%%\n", index,
            globalBullishPercentage.getValue(index).multiply(100).round());
}

// Calculate SMA crossovers with bar close price.
final Crossed crossed = crossed(sma, close);
for (long index = barSeries.getStartIndex(); index <= barSeries.getEndIndex(); index++) {
    System.out.printf("OHLC4 20 SMA crossed C at %d: %s\n", index, crossed.getValue(index));
}

Acknowledgement

This library was inspired by the excellent ta4j library. There are several improvements and additions that this library provides:

• Usage of improved Num interface via the Num library.
• Configurable Indicator result caching.
• Indicator instance caching.
• Several optimizations to reduce memory consumption and improve execution time for common access patterns (e.g. consecutive indices, identical indices, caching and reusing Indicator instances with identical configurations).
• Configurable moving average types for Indicator implementations that utilize moving averages.
• Configurable epsilon per Series.
• Generic Series interface, allowing for NumSeries and such.
• Documentation improvements.
• Improved package structure.
• Several more helper/utility Indicator implementations.

Contributing

Contributions are welcome. Use existing Indicator class implementations as a reference for new implementations. A few guidelines for creating Indicator class implementations are as follows:

• There should only be one constructor and it should use the protected access modifier.
• Create public static methods for consumers to use for instantiation or retrieval from a weak-valued instance cache. The method name should be the full indicator name. Add overloads for acronyms.
• All implementations should implement a weak-valued instance cache, except for implementations that are subclasses of CachelessIndicator or Num/Boolean/Instant operations (e.g. UnaryOperation, BinaryOperation, and TernaryOperation).
• The class Javadoc should include an @see website reference for the indicator formula/algorithm.
• Avoid declarative calculations via the UnaryOperation, BinaryOperation, or TernaryOperation indicators. Prefer to imperatively calculate results in the calculate method.
• Avoid creating anonymous Indicator instances.
• Prefer to use Num, Boolean, or Instant as the type for the Indicator. Use Num even in cases where an Indicator only uses integer values. This greatly improves interoperability between Indicator implementations and is more convenient.

Maintained by Invision

This project is maintained by Invision. Invision enables you to automate and test your investment and trading strategies across billions of data points in seconds using quantitative finance and algorithmic trading programs you build on our code or no-code platform.