How to Create a Stock Trading Algorithm in Python - Part 2
#python #algorithmictrading #tradingstrategy #technicalanalysis #stockmarket #crypto
Python Trading Algorithm using Bollinger Bands for Mean Reversion.
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Mean reversion is a financial concept that refers to the tendency of a financial instrument's price, such as a stock, bond, or commodity, to move toward the average or mean over time. In other words, when the price of an asset deviates significantly from its historical average, there is an expectation that it will eventually revert to its average or historical mean.
In our trading algorithm, we will use yahoo finance data to collect open, close, high, low, and volume data to derive Bollinger band values. The algorithm will perform a buy if the close price is below the lower Bollinger band; the trading algorithm will perform a sell if the close price is above the upper Bollinger band.
In Episode 1, we create some custom functions in python that returns the appropriate percent change sign, gathers last price and percent change from yahoo finance using yfinance and yahoo_fin.
In Episode 2, we create a stop loss python function using Average True Range to minimize losses if a trade goes south. Plus, we will calculate the Exponential Moving Average (EMA) and Bollinger Bands as technical analysis.
In Episode 3, we will close out the series with a back testing algorithm, put together the mean reversion algorithm, and make plots using matplotlib library to visually see the back test results and the buy sell signals in action.
Percent Change Symbols: ▲ ▼
00:00 Average True Range ATR and Stop Loss Function
09:01 Get Data Using Yahoo Finance
13:46 EMA and Bollinger Band Functions
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