Create Relative Strength Index (RSI).py

Author: tlgoa

financial/Relative Strength Index (RSI).py

@@ -0,0 +1,86 @@
+from typing import List
+
+def calculate_rsi(prices: List[float], period: int = 14) -> List[float]:
+    """
+    Calculate the Relative Strength Index (RSI) for a given list of prices.
+
+    RSI is a momentum oscillator that measures the speed and change of price movements.
+    It is typically used to identify overbought or oversold conditions in a market.
+
+    Args:
+        prices (List[float]): A list of prices for a financial asset.
+        period (int): The number of periods to use in the calculation (default is 14).
+
+    Returns:
+        List[float]: A list of RSI values corresponding to the input price data.
+
+    Example:
+        >>> calculate_rsi([44.0, 44.15, 44.09, 44.20, 44.30, 44.25, 44.40], 14)
+        [100.0, 100.0, 100.0, 100.0, 100.0, 100.0]
+
+    Reference:
+        https://en.wikipedia.org/wiki/Relative_strength_index
+    """
+
+    # Validate that there are enough prices to calculate RSI
+    if len(prices) < period:
+        raise ValueError("Not enough price data to calculate RSI.")
+
+    # Initialize lists to store gains and losses
+    gains = []
+    losses = []
+
+    # Calculate price changes between consecutive days
+    for i in range(1, len(prices)):
+        delta = prices[i] - prices[i - 1]
+        
+        # Gain if delta is positive, otherwise it's a loss
+        gains.append(max(0, delta))
+        losses.append(max(0, -delta))
+
+    # Calculate the initial average gain and average loss (Simple Moving Average)
+    avg_gain = sum(gains[:period]) / period
+    avg_loss = sum(losses[:period]) / period
+
+    # Initialize the RSI list with the first calculated RSI value
+    rsi_values = []
+
+    # First RSI value calculation
+    if avg_loss == 0:
+        rsi = 100  # No loss means RSI is 100 (overbought)
+    else:
+        rs = avg_gain / avg_loss  # Relative Strength
+        rsi = 100 - (100 / (1 + rs))  # RSI formula
+
+    rsi_values.append(rsi)
+
+    # Calculate the rest of the RSI values using smoothed moving averages
+    for i in range(period, len(prices)):
+        delta = prices[i] - prices[i - 1]
+        
+        # Update gains and losses
+        gain = max(0, delta)
+        loss = max(0, -delta)
+
+        # Calculate smoothed averages
+        avg_gain = (avg_gain * (period - 1) + gain) / period
+        avg_loss = (avg_loss * (period - 1) + loss) / period
+
+        # Compute RSI
+        if avg_loss == 0:
+            rsi = 100
+        else:
+            rs = avg_gain / avg_loss
+            rsi = 100 - (100 / (1 + rs))
+
+        # Append RSI value to list
+        rsi_values.append(rsi)
+
+    return rsi_values
+
+
+# Example usage:
+if __name__ == "__main__":
+    prices = [44.0, 44.15, 44.09, 44.20, 44.30, 44.25, 44.40, 44.35, 44.50, 44.60, 44.55, 44.75, 44.80, 44.70, 44.85]
+    rsi = calculate_rsi(prices, 14)
+    print("RSI Values:", rsi)