go-rsi

The Relative Strength Index (RSI) technical analysis algorithm implemented in Golang.

import "github.com/MicahParks/go-rsi/v2"

Usage

For full examples, please see the examples directory.

Preconditions

1. Gather test data.
2. Decide on the number of periods, p, for the RSI algorithm. Populate a slice of prices whose length is p + 1.

// Determine the number of periods for the initial inputs. Defaults to 14.
const initialLength = rsi.DefaultPeriods + 1
initial := prices[:initialLength]

Step 1

Create the RSI data structure and get the first result.

r, result := rsi.New(initial)

Step 2

Use the remaining data to calculate the RSI value for that period.

remaining := prices[initialLength:]
for i, next := range remaining {
	result = r.Calculate(next)
}

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-rsi/v2
cpu: Intel(R) Core(TM) i5-9600K CPU @ 3.70GHz
BenchmarkBigRSI_Calculate-6     1000000000               0.0001744 ns/op
BenchmarkRSI_Calculate-6        1000000000               0.0000017 ns/op
PASS
ok      github.com/MicahParks/go-rsi/v2    0.005s

Other Technical Algorithms

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

• Accumulation/Distribution (A/D): go-ad
• Chaikin: go-chaikin
• Moving Average Convergence Divergence (MACD), Exponential Moving Average (EMA), Simple Moving Average (SMA): go-ma
• Relative Strength Index (RSI): go-rsi

Resources

I built and tested this package using these resources:

• Investopedia
• Invest Excel