https://github.com/micahparks/go-ad

The Accumulation Distribution Line (A/D) technical analysis algorithm implemented in Golang.
https://github.com/micahparks/go-ad

go golang technical-analysis

Last synced: about 6 hours ago
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The Accumulation Distribution Line (A/D) technical analysis algorithm implemented in Golang.

• Host: GitHub
• URL: https://github.com/micahparks/go-ad
• Owner: MicahParks
• License: mit
• Created: 2021-11-11T15:50:30.000Z (about 3 years ago)
• Default Branch: main
• Last Pushed: 2025-01-02T14:50:20.000Z (11 days ago)
• Last Synced: 2025-01-02T15:35:17.764Z (11 days ago)
• Topics: go, golang, technical-analysis
• Language: Go
• Homepage:
• Size: 16.6 KB
• Stars: 4
• Watchers: 2
• Forks: 0
• Open Issues: 0
• Metadata Files:
  • Readme: README.md
  • License: LICENSE

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README

        
[![Go Reference](https://pkg.go.dev/badge/github.com/MicahParks/go-ad.svg)](https://pkg.go.dev/github.com/MicahParks/go-ad) [![Go Report Card](https://goreportcard.com/badge/github.com/MicahParks/go-ad)](https://goreportcard.com/report/github.com/MicahParks/go-ad)

# go-ad

The Accumulation Distribution Line technical analysis algorithm implemented in Golang.

```go

import "github.com/MicahParks/go-ad"

```

# Usage

For full examples, please see the `examples` directory.

## Step 1

Gather the input for the current period.

```go

input := ad.Input{

	Close:  closePrices[i],

	Low:    low[i],

	High:   high[i],

	Volume: volume[i],

}

```

## Step 2

Create the A/D data structure and get the first result

```go

adLine, result := ad.New(input)

```

## Step 3

Use the next period's data to calculate the next point on the A/D line. Repeat for all periods.

```go

result = adLine.Calculate(input)

```

# Somewhat complete example (without data)

```go

package main

import (

	"log"

	"os"

	"github.com/MicahParks/go-ad"

)

func main() {

	// Create a logger.

	logger := log.New(os.Stdout, "", 0)

	// Iterate through the rest of the periods' data and calculate the A/D line's point for the given period.

	var adLine *ad.AD

	var result float64

	for i := range open {

		input := ad.Input{

			Close:  closePrices[i],

			Low:    low[i],

			High:   high[i],

			Volume: volume[i],

		}

		if adLine == nil {

			adLine, result = ad.New(input)

		} else {

			result = adLine.Calculate(input)

		}

		logger.Printf("Index: %d AD: %.4f", i, result)

	}

}

```

# Testing

There is 100% test coverage and benchmarks for this project. Here is an example benchmark result:

```

$ go test -bench .

goos: linux

goarch: amd64

pkg: github.com/MicahParks/go-ad

cpu: Intel(R) Core(TM) i5-9600K CPU @ 3.70GHz

BenchmarkAD_Calculate-6         1000000000               0.0000010 ns/op

BenchmarkBigAD_Calculate-6      1000000000               0.0000765 ns/op

PASS

ok      github.com/MicahParks/go-ad     0.004s

```

# Other Technical Algorithms

Looking for some other technical analysis algorithms? Here are some other ones I've implemented:

* Accumulation/Distribution (A/D): [go-ad](https://github.com/MicahParks/go-ad)

* Chaikin: [go-chaikin](https://github.com/MicahParks/go-chaikin)

* Moving Average Convergence Divergence (MACD), Exponential Moving Average (EMA), Simple Moving Average (SMA):

  [go-ma](https://github.com/MicahParks/go-ma)

* Relative Strength Index (RSI): [go-rsi](https://github.com/MicahParks/go-rsi)

# Resources

I built and tested this package using these resources:

* [Investopedia](https://www.investopedia.com/terms/a/accumulationdistribution.asp)

* [Invest Excel](https://investexcel.net/accumulation-distribution-line/)