Back-testing a few technical indicators on Bitcoin using Python and evaluating the returns.
This article will be straightforward. We are simply interested in finding what works best on Bitcoin using simple technical indicators. We know that a pure indicator strategy does not work generally on financial time series but we will see that together by back-testing a few technical indicators and providing their code. The indicators back-tested will be:
The Stochastic Oscillator.
The Awesome Oscillator.
The Bollinger Bands.
The Parabolic Stop-And-Reverse Indicator.
BTCUSD Time series since 2014.
An overwhelming number of traders use the famous Relative Strength Index to help with their decisions, and although it can only serve as a confirming indicator, it nevertheless, has its weight in many trading decisions or at the very least timing the decisions. The RSI has been created by J. Welles Wilder in 1978 as a momentum indicator with an optimal look-back period of 14 bars. It is bounded between 0 and 100 with 30 and 70 as the agreed-upon oversold and overbought zones respectively. The RSI can be used through 4 known techniques:
In this article, we will be back-testing the first RSI technique and see whether touching the 30 or 70 level can provide a reversal or correction point. In other words, should we develop a system that trades when the RSI touches these levels?
We will create the below function that calculates the RSI on an OHLC data
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