01-18-2023, 03:08 AM
Bitcoin – Trading Moving Averages or HODL? A Python Script Uncovers the Answer!
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<div class="kksr-legend" style="font-size: 19.2px;"> 5/5 – (1 vote) </div>
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<p>I’ve always wondered if a slow and high-level trading strategy focusing on long-term trends could outperform a buy-and-hold strategy.</p>
<p>To answer this question, I created a Python script that would utilize a momentum-based strategy to tell me when to buy and when to sell Bitcoin. </p>
<p>Despite my busy life and doubts that day trading would be a successful venture, I was eager to find out if this simple program could beat the market. I can run the Python code daily to decide whether to buy or sell BTC. </p>
<p class="has-base-background-color has-background"><strong>What would have happened if I had used the following strategy between the turbulent years 2020 and 2022 in Bitcoin?</strong> Read on to find out! <img src="https://s.w.org/images/core/emoji/14.0.0/72x72/1f447.png" alt="?" class="wp-smiley" style="height: 1em; max-height: 1em;" /></p>
<h2>General Idea</h2>
<div class="wp-block-image">
<figure class="aligncenter size-full"><img loading="lazy" decoding="async" width="495" height="881" src="https://blog.finxter.com/wp-content/uploads/2023/01/image-165.png" alt="" class="wp-image-1066579" srcset="https://blog.finxter.com/wp-content/uploads/2023/01/image-165.png 495w, https://blog.finxter.com/wp-content/uplo...69x300.png 169w" sizes="(max-width: 495px) 100vw, 495px" /></figure>
</div>
<p>The idea of this algorithm is to allow traders to automate their Bitcoin trading decisions using two moving averages. </p>
<p class="has-base-background-color has-background"><img src="https://s.w.org/images/core/emoji/14.0.0/72x72/1f449.png" alt="?" class="wp-smiley" style="height: 1em; max-height: 1em;" /> <strong>Finxter Academy</strong>: <a href="https://academy.finxter.com/course/setting-up-binance-and-development-environment-3/" data-type="URL" data-id="https://academy.finxter.com/course/setting-up-binance-and-development-environment-3/" target="_blank" rel="noreferrer noopener">Complete Python Trading Course (Binance) — Simple Moving Average</a></p>
<p>The algorithm will enter buy positions when the shorter-term moving average (<code>MA1</code>) is higher than the longer-term moving average (<code>MA2</code>) indicating a positive momentum of the Bitcoin price, and enter sell positions when the shorter-term moving average is lower than the longer-term moving average indicating a negative momentum of the Bitcoin price. </p>
<p>When the moving averages cross, the algorithm will close any existing positions and reverse the trading direction.</p>
<h2>Algorithm Steps</h2>
<figure class="wp-block-image size-large"><img decoding="async" loading="lazy" width="1024" height="683" src="https://blog.finxter.com/wp-content/uploads/2023/01/image-166-1024x683.png" alt="" class="wp-image-1066580" srcset="https://blog.finxter.com/wp-content/uploads/2023/01/image-166-1024x683.png 1024w, https://blog.finxter.com/wp-content/uplo...00x200.png 300w, https://blog.finxter.com/wp-content/uplo...68x512.png 768w, https://blog.finxter.com/wp-content/uplo...ge-166.png 1113w" sizes="(max-width: 1024px) 100vw, 1024px" /></figure>
<p>My strategy follows these simple steps:</p>
<ol>
<li>Initialize two moving averages, <code>MA1</code> and <code>MA2</code>, with different lookback periods.</li>
<li>Calculate the current value of each moving average.</li>
<li>If <code>MA1 > MA2</code>, enter a buy position in the Bitcoin market.</li>
<li>If <code>MA1 < MA2</code>, enter a sell position in the Bitcoin market.</li>
<li>Monitor the market for any changes in the moving averages.</li>
<li>When the moving averages cross, close any existing positions and reverse the trading direction (buy if previously selling, sell if previously buying).</li>
<li>Repeat steps 2 to 6.</li>
</ol>
<h2>Python Program to Automate It</h2>
<div class="wp-block-image">
<figure class="aligncenter size-large"><img decoding="async" loading="lazy" width="1024" height="684" src="https://blog.finxter.com/wp-content/uploads/2023/01/image-167-1024x684.png" alt="" class="wp-image-1066593" srcset="https://blog.finxter.com/wp-content/uploads/2023/01/image-167-1024x684.png 1024w, https://blog.finxter.com/wp-content/uplo...00x200.png 300w, https://blog.finxter.com/wp-content/uplo...68x513.png 768w, https://blog.finxter.com/wp-content/uplo...ge-167.png 1113w" sizes="(max-width: 1024px) 100vw, 1024px" /></figure>
</div>
<p>The following program implements these steps in practice by pulling the Bitcoin price data from an online API, calculating the moving averages (short- and long-term), and trading based on whether the short-term MA is below or above the long-term MA. </p>
<p>I’ll explain the code in a minute!</p>
<pre class="EnlighterJSRAW" data-enlighter-language="python" data-enlighter-theme="" data-enlighter-highlight="" data-enlighter-linenumbers="" data-enlighter-lineoffset="" data-enlighter-title="" data-enlighter-group="">import pandas as pd
import numpy as np
import matplotlib.pyplot as plt
import requests # Get Bitcoin Price Data
URL = 'https://www.alphavantage.co/query?function=DIGITAL_CURRENCY_DAILY&symbol=BTC&market=USD&apikey=APIKEY'
response = requests.get(URL) data = response.json() daily_data = data["Time Series (Digital Currency Daily)"] # Convert JSON to DataFrame
df = pd.DataFrame(daily_data)
df = df.T # Create two Moving Averages
MA1 = 20
MA2 = 50
df['MA1'] = df['1a. open (USD)'].rolling(MA1).mean()
df['MA2'] = df['1a. open (USD)'].rolling(MA2).mean() # Initialize variables
position = 0
my_usd = 10000
my_btc = 0 print('Initial balance:', str(my_usd), 'USD') # Backtest Algorithm
for i in range(len(df)): # Get price price = float(df['1a. open (USD)'].iloc[i]) # Buy position if df['MA1'].iloc[i] > df['MA2'].iloc[i] and position == 0: position = 1 my_btc = price / my_usd my_usd = 0 print('Buying at', price, 'on', df.index[i]) # Sell position elif df['MA1'].iloc[i] < df['MA2'].iloc[i] and position == 1: position = 0 my_usd = price * my_btc my_btc = 0 print('Selling at', price, 'on', df.index[i]) print('Final balance:', str(my_usd + my_btc * price)) initial_btc = float(df['1a. open (USD)'].iloc[0]) / 10000
value_today = initial_btc * float(df['1a. open (USD)'].iloc[-1])
print('Final balance (buy and hold):', str(value_today))
</pre>
<h2>Code Explanation</h2>
<div class="wp-block-image">
<figure class="aligncenter size-large"><img decoding="async" loading="lazy" width="1024" height="684" src="https://blog.finxter.com/wp-content/uploads/2023/01/image-168-1024x684.png" alt="" class="wp-image-1066595" srcset="https://blog.finxter.com/wp-content/uploads/2023/01/image-168-1024x684.png 1024w, https://blog.finxter.com/wp-content/uplo...00x200.png 300w, https://blog.finxter.com/wp-content/uplo...68x513.png 768w, https://blog.finxter.com/wp-content/uplo...ge-168.png 1113w" sizes="(max-width: 1024px) 100vw, 1024px" /></figure>
</div>
<p>This code implements the algorithm described above. </p>
<p>The first portion of the code is getting the daily Bitcoin price data from the API and converting it into a <a href="https://blog.finxter.com/how-to-create-a-dataframe-in-pandas/" data-type="post" data-id="16764" target="_blank" rel="noreferrer noopener">DataFrame</a>. </p>
<p>Next, the code creates two moving averages, <code>MA1</code> and <code>MA2</code>, based on the open price of Bitcoin. Then, the code initializes the position variable to 0.</p>
<p>The backtest algorithm then runs a loop to iterate through the DataFrame to identify when conditions are met to buy or sell. If the shorter-term <code>MA1</code> is higher than the longer-term <code>MA2</code>, the code will enter a buy position. </p>
<p>Similarly, if the shorter-term <code>MA1</code> is lower than the longer-term <code>MA2</code>, the code will enter a sell position. We don’t assume short selling so “selling” on an empty position just means waiting for the next buy opportunity.</p>
<p>Finally, if the <code>MA1</code> and <code>MA2</code> cross, the code will close any existing position and reverse the trading direction.</p>
<h2>Backtesting the Strategy</h2>
<div class="wp-block-image">
<figure class="aligncenter size-full"><img decoding="async" loading="lazy" width="587" height="881" src="https://blog.finxter.com/wp-content/uploads/2023/01/image-169.png" alt="" class="wp-image-1066596" srcset="https://blog.finxter.com/wp-content/uploads/2023/01/image-169.png 587w, https://blog.finxter.com/wp-content/uplo...00x300.png 200w" sizes="(max-width: 587px) 100vw, 587px" /></figure>
</div>
<p>Let’s have a look at an example run — note to read this from bottom to top! <img src="https://s.w.org/images/core/emoji/14.0.0/72x72/1f447.png" alt="?" class="wp-smiley" style="height: 1em; max-height: 1em;" /></p>
<pre class="EnlighterJSRAW" data-enlighter-language="raw" data-enlighter-theme="" data-enlighter-highlight="1,22,23" data-enlighter-linenumbers="" data-enlighter-lineoffset="" data-enlighter-title="" data-enlighter-group="">Initial balance: 10000 USD
Buying at 20905.58 on 2022-11-07
Selling at 18809.13 on 2022-09-26
Buying at 21826.87 on 2022-09-12
Selling at 19331.28 on 2022-07-13
Buying at 28424.71 on 2022-06-12
Selling at 41941.7 on 2022-03-10
Buying at 42380.87 on 2022-02-07
Selling at 36660.35 on 2022-01-25
Buying at 41566.48 on 2022-01-08
Selling at 57471.35 on 2021-10-12
Buying at 47674.01 on 2021-08-25
Selling at 44572.54 on 2021-08-08
Buying at 40516.28 on 2021-06-15
Selling at 57351.56 on 2021-03-22
Buying at 57641.0 on 2021-03-19
Selling at 56900.74 on 2021-03-17
Buying at 11318.42 on 2020-08-26
Selling at 9538.1 on 2020-07-25
Buying at 9772.44 on 2020-06-10
Selling at 9315.96 on 2020-05-16
Final balance: 14806.674822101442
Final balance (buy and hold): 15095.029852800002</pre>
<p>So, you see, in the period between May 2020 and November 2022, trading wouldn’t have been more profitable than simply buying and holding Bitcoin — even when ignoring trading fees and higher tax burden. </p>
<p>And ignoring the fact that Bitcoin has had huge up and down volatility, which should be great for trading. That is — in theory.</p>
<h2>Conclusion</h2>
<div class="wp-block-image">
<figure class="aligncenter size-large"><img decoding="async" loading="lazy" width="1024" height="711" src="https://blog.finxter.com/wp-content/uploads/2023/01/image-170-1024x711.png" alt="" class="wp-image-1066604" srcset="https://blog.finxter.com/wp-content/uploads/2023/01/image-170-1024x711.png 1024w, https://blog.finxter.com/wp-content/uplo...00x208.png 300w, https://blog.finxter.com/wp-content/uplo...68x533.png 768w, https://blog.finxter.com/wp-content/uplo...ge-170.png 1113w" sizes="(max-width: 1024px) 100vw, 1024px" /></figure>
</div>
<div style="height:45px" aria-hidden="true" class="wp-block-spacer"></div>
<p>Buy and HODL!</p>
</div>
https://www.sickgaming.net/blog/2023/01/...he-answer/
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<div class="kksr-legend" style="font-size: 19.2px;"> 5/5 – (1 vote) </div>
</p></div>
<p>I’ve always wondered if a slow and high-level trading strategy focusing on long-term trends could outperform a buy-and-hold strategy.</p>
<p>To answer this question, I created a Python script that would utilize a momentum-based strategy to tell me when to buy and when to sell Bitcoin. </p>
<p>Despite my busy life and doubts that day trading would be a successful venture, I was eager to find out if this simple program could beat the market. I can run the Python code daily to decide whether to buy or sell BTC. </p>
<p class="has-base-background-color has-background"><strong>What would have happened if I had used the following strategy between the turbulent years 2020 and 2022 in Bitcoin?</strong> Read on to find out! <img src="https://s.w.org/images/core/emoji/14.0.0/72x72/1f447.png" alt="?" class="wp-smiley" style="height: 1em; max-height: 1em;" /></p>
<h2>General Idea</h2>
<div class="wp-block-image">
<figure class="aligncenter size-full"><img loading="lazy" decoding="async" width="495" height="881" src="https://blog.finxter.com/wp-content/uploads/2023/01/image-165.png" alt="" class="wp-image-1066579" srcset="https://blog.finxter.com/wp-content/uploads/2023/01/image-165.png 495w, https://blog.finxter.com/wp-content/uplo...69x300.png 169w" sizes="(max-width: 495px) 100vw, 495px" /></figure>
</div>
<p>The idea of this algorithm is to allow traders to automate their Bitcoin trading decisions using two moving averages. </p>
<p class="has-base-background-color has-background"><img src="https://s.w.org/images/core/emoji/14.0.0/72x72/1f449.png" alt="?" class="wp-smiley" style="height: 1em; max-height: 1em;" /> <strong>Finxter Academy</strong>: <a href="https://academy.finxter.com/course/setting-up-binance-and-development-environment-3/" data-type="URL" data-id="https://academy.finxter.com/course/setting-up-binance-and-development-environment-3/" target="_blank" rel="noreferrer noopener">Complete Python Trading Course (Binance) — Simple Moving Average</a></p>
<p>The algorithm will enter buy positions when the shorter-term moving average (<code>MA1</code>) is higher than the longer-term moving average (<code>MA2</code>) indicating a positive momentum of the Bitcoin price, and enter sell positions when the shorter-term moving average is lower than the longer-term moving average indicating a negative momentum of the Bitcoin price. </p>
<p>When the moving averages cross, the algorithm will close any existing positions and reverse the trading direction.</p>
<h2>Algorithm Steps</h2>
<figure class="wp-block-image size-large"><img decoding="async" loading="lazy" width="1024" height="683" src="https://blog.finxter.com/wp-content/uploads/2023/01/image-166-1024x683.png" alt="" class="wp-image-1066580" srcset="https://blog.finxter.com/wp-content/uploads/2023/01/image-166-1024x683.png 1024w, https://blog.finxter.com/wp-content/uplo...00x200.png 300w, https://blog.finxter.com/wp-content/uplo...68x512.png 768w, https://blog.finxter.com/wp-content/uplo...ge-166.png 1113w" sizes="(max-width: 1024px) 100vw, 1024px" /></figure>
<p>My strategy follows these simple steps:</p>
<ol>
<li>Initialize two moving averages, <code>MA1</code> and <code>MA2</code>, with different lookback periods.</li>
<li>Calculate the current value of each moving average.</li>
<li>If <code>MA1 > MA2</code>, enter a buy position in the Bitcoin market.</li>
<li>If <code>MA1 < MA2</code>, enter a sell position in the Bitcoin market.</li>
<li>Monitor the market for any changes in the moving averages.</li>
<li>When the moving averages cross, close any existing positions and reverse the trading direction (buy if previously selling, sell if previously buying).</li>
<li>Repeat steps 2 to 6.</li>
</ol>
<h2>Python Program to Automate It</h2>
<div class="wp-block-image">
<figure class="aligncenter size-large"><img decoding="async" loading="lazy" width="1024" height="684" src="https://blog.finxter.com/wp-content/uploads/2023/01/image-167-1024x684.png" alt="" class="wp-image-1066593" srcset="https://blog.finxter.com/wp-content/uploads/2023/01/image-167-1024x684.png 1024w, https://blog.finxter.com/wp-content/uplo...00x200.png 300w, https://blog.finxter.com/wp-content/uplo...68x513.png 768w, https://blog.finxter.com/wp-content/uplo...ge-167.png 1113w" sizes="(max-width: 1024px) 100vw, 1024px" /></figure>
</div>
<p>The following program implements these steps in practice by pulling the Bitcoin price data from an online API, calculating the moving averages (short- and long-term), and trading based on whether the short-term MA is below or above the long-term MA. </p>
<p>I’ll explain the code in a minute!</p>
<pre class="EnlighterJSRAW" data-enlighter-language="python" data-enlighter-theme="" data-enlighter-highlight="" data-enlighter-linenumbers="" data-enlighter-lineoffset="" data-enlighter-title="" data-enlighter-group="">import pandas as pd
import numpy as np
import matplotlib.pyplot as plt
import requests # Get Bitcoin Price Data
URL = 'https://www.alphavantage.co/query?function=DIGITAL_CURRENCY_DAILY&symbol=BTC&market=USD&apikey=APIKEY'
response = requests.get(URL) data = response.json() daily_data = data["Time Series (Digital Currency Daily)"] # Convert JSON to DataFrame
df = pd.DataFrame(daily_data)
df = df.T # Create two Moving Averages
MA1 = 20
MA2 = 50
df['MA1'] = df['1a. open (USD)'].rolling(MA1).mean()
df['MA2'] = df['1a. open (USD)'].rolling(MA2).mean() # Initialize variables
position = 0
my_usd = 10000
my_btc = 0 print('Initial balance:', str(my_usd), 'USD') # Backtest Algorithm
for i in range(len(df)): # Get price price = float(df['1a. open (USD)'].iloc[i]) # Buy position if df['MA1'].iloc[i] > df['MA2'].iloc[i] and position == 0: position = 1 my_btc = price / my_usd my_usd = 0 print('Buying at', price, 'on', df.index[i]) # Sell position elif df['MA1'].iloc[i] < df['MA2'].iloc[i] and position == 1: position = 0 my_usd = price * my_btc my_btc = 0 print('Selling at', price, 'on', df.index[i]) print('Final balance:', str(my_usd + my_btc * price)) initial_btc = float(df['1a. open (USD)'].iloc[0]) / 10000
value_today = initial_btc * float(df['1a. open (USD)'].iloc[-1])
print('Final balance (buy and hold):', str(value_today))
</pre>
<h2>Code Explanation</h2>
<div class="wp-block-image">
<figure class="aligncenter size-large"><img decoding="async" loading="lazy" width="1024" height="684" src="https://blog.finxter.com/wp-content/uploads/2023/01/image-168-1024x684.png" alt="" class="wp-image-1066595" srcset="https://blog.finxter.com/wp-content/uploads/2023/01/image-168-1024x684.png 1024w, https://blog.finxter.com/wp-content/uplo...00x200.png 300w, https://blog.finxter.com/wp-content/uplo...68x513.png 768w, https://blog.finxter.com/wp-content/uplo...ge-168.png 1113w" sizes="(max-width: 1024px) 100vw, 1024px" /></figure>
</div>
<p>This code implements the algorithm described above. </p>
<p>The first portion of the code is getting the daily Bitcoin price data from the API and converting it into a <a href="https://blog.finxter.com/how-to-create-a-dataframe-in-pandas/" data-type="post" data-id="16764" target="_blank" rel="noreferrer noopener">DataFrame</a>. </p>
<p>Next, the code creates two moving averages, <code>MA1</code> and <code>MA2</code>, based on the open price of Bitcoin. Then, the code initializes the position variable to 0.</p>
<p>The backtest algorithm then runs a loop to iterate through the DataFrame to identify when conditions are met to buy or sell. If the shorter-term <code>MA1</code> is higher than the longer-term <code>MA2</code>, the code will enter a buy position. </p>
<p>Similarly, if the shorter-term <code>MA1</code> is lower than the longer-term <code>MA2</code>, the code will enter a sell position. We don’t assume short selling so “selling” on an empty position just means waiting for the next buy opportunity.</p>
<p>Finally, if the <code>MA1</code> and <code>MA2</code> cross, the code will close any existing position and reverse the trading direction.</p>
<h2>Backtesting the Strategy</h2>
<div class="wp-block-image">
<figure class="aligncenter size-full"><img decoding="async" loading="lazy" width="587" height="881" src="https://blog.finxter.com/wp-content/uploads/2023/01/image-169.png" alt="" class="wp-image-1066596" srcset="https://blog.finxter.com/wp-content/uploads/2023/01/image-169.png 587w, https://blog.finxter.com/wp-content/uplo...00x300.png 200w" sizes="(max-width: 587px) 100vw, 587px" /></figure>
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<p>Let’s have a look at an example run — note to read this from bottom to top! <img src="https://s.w.org/images/core/emoji/14.0.0/72x72/1f447.png" alt="?" class="wp-smiley" style="height: 1em; max-height: 1em;" /></p>
<pre class="EnlighterJSRAW" data-enlighter-language="raw" data-enlighter-theme="" data-enlighter-highlight="1,22,23" data-enlighter-linenumbers="" data-enlighter-lineoffset="" data-enlighter-title="" data-enlighter-group="">Initial balance: 10000 USD
Buying at 20905.58 on 2022-11-07
Selling at 18809.13 on 2022-09-26
Buying at 21826.87 on 2022-09-12
Selling at 19331.28 on 2022-07-13
Buying at 28424.71 on 2022-06-12
Selling at 41941.7 on 2022-03-10
Buying at 42380.87 on 2022-02-07
Selling at 36660.35 on 2022-01-25
Buying at 41566.48 on 2022-01-08
Selling at 57471.35 on 2021-10-12
Buying at 47674.01 on 2021-08-25
Selling at 44572.54 on 2021-08-08
Buying at 40516.28 on 2021-06-15
Selling at 57351.56 on 2021-03-22
Buying at 57641.0 on 2021-03-19
Selling at 56900.74 on 2021-03-17
Buying at 11318.42 on 2020-08-26
Selling at 9538.1 on 2020-07-25
Buying at 9772.44 on 2020-06-10
Selling at 9315.96 on 2020-05-16
Final balance: 14806.674822101442
Final balance (buy and hold): 15095.029852800002</pre>
<p>So, you see, in the period between May 2020 and November 2022, trading wouldn’t have been more profitable than simply buying and holding Bitcoin — even when ignoring trading fees and higher tax burden. </p>
<p>And ignoring the fact that Bitcoin has had huge up and down volatility, which should be great for trading. That is — in theory.</p>
<h2>Conclusion</h2>
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<figure class="aligncenter size-large"><img decoding="async" loading="lazy" width="1024" height="711" src="https://blog.finxter.com/wp-content/uploads/2023/01/image-170-1024x711.png" alt="" class="wp-image-1066604" srcset="https://blog.finxter.com/wp-content/uploads/2023/01/image-170-1024x711.png 1024w, https://blog.finxter.com/wp-content/uplo...00x208.png 300w, https://blog.finxter.com/wp-content/uplo...68x533.png 768w, https://blog.finxter.com/wp-content/uplo...ge-170.png 1113w" sizes="(max-width: 1024px) 100vw, 1024px" /></figure>
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<p>Buy and HODL!</p>
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https://www.sickgaming.net/blog/2023/01/...he-answer/