FFERvsBTCUSD

FFERvsBTC.py

import requests
import pandas as pd
import matplotlib.pyplot as plt
import yfinance as yf

# FRED API Key (you need to get your own from https://fred.stlouisfed.org/)
FRED_API_KEY = 'YOUR_KEY_HERE'

# Define the URL for FRED (Federal Funds Rate)
FRED_URL = f'https://api.stlouisfed.org/fred/series/observations?series_id=FEDFUNDS&api_key={FRED_API_KEY}&file_type=json'

# Function to fetch Federal Funds Effective Rate from FRED API
def get_fed_funds_rate():
    response = requests.get(FRED_URL)
    data = response.json()['observations']
    # Convert the data into a pandas DataFrame
    fed_data = pd.DataFrame(data)
    fed_data['date'] = pd.to_datetime(fed_data['date'])
    fed_data['value'] = pd.to_numeric(fed_data['value'])
    fed_data = fed_data[['date', 'value']].rename(columns={'value': 'Fed_Funds_Rate'})
    return fed_data

# Function to fetch BTC/USD historical data using yfinance
def get_btc_usd():
    btc = yf.download('BTC-USD', start='2014-01-01', end='2024-09-01')
    btc_data = btc[['Close']].reset_index()
    btc_data.columns = ['date', 'BTC_USD']
    return btc_data

# Fetch data
fed_funds_rate_df = get_fed_funds_rate()
btc_usd_df = get_btc_usd()

# Merge the two DataFrames on 'date'
merged_df = pd.merge_asof(btc_usd_df.sort_values('date'), fed_funds_rate_df.sort_values('date'), on='date')

# Plotting the data
fig, ax1 = plt.subplots(figsize=(10,6))

# Plot Fed Funds Rate on the left y-axis
ax1.set_xlabel('Date')
ax1.set_ylabel('Fed Funds Rate (%)', color='tab:blue')
ax1.plot(merged_df['date'], merged_df['Fed_Funds_Rate'], color='tab:blue', label="Fed Funds Rate (%)")
ax1.tick_params(axis='y', labelcolor='tab:blue')

# Create another y-axis for BTC/USD on the right
ax2 = ax1.twinx()
ax2.set_ylabel('BTC/USD', color='tab:green')
ax2.plot(merged_df['date'], merged_df['BTC_USD'], color='tab:green', label="BTC/USD")
ax2.tick_params(axis='y', labelcolor='tab:green')

# Titles and layout
plt.title("Federal Funds Effective Rates and BTC/USD (2014-2024)")
fig.tight_layout()

# Show the plot
plt.show()