diff --git a/strategies/trin.py b/strategies/trin.py
new file mode 100644
index 0000000..2916fbc
--- /dev/null
+++ b/strategies/trin.py
@@ -0,0 +1,46 @@
+import numpy as np
+
+from pandas import DataFrame, Series
+
+from ohlc import ohlc
+
+def calculate_rsi(data: DataFrame, period: int = 2) -> Series:
+    """
+    Calculate the RSI and return it as a Series without modifying the original DataFrame.
+    """
+    delta = data['Close'].diff()
+    gain = np.where(delta > 0, delta, 0)
+    loss = np.where(delta < 0, -delta, 0)
+
+    alpha = 1 / period
+    avg_gain = Series(gain).ewm(alpha = alpha, adjust = False).mean()
+    avg_loss = Series(loss).ewm(alpha = alpha, adjust = False).mean()
+
+    rs = avg_gain / avg_loss
+    return 100 - (100 / (1 + rs))
+
+def signals(data: DataFrame) -> Series:
+    """
+    Generate long signals based on the TRIN strategy with the following rules:
+    1. SPY is above its 200-day moving average
+    2. 2-period RSI is below 50
+    3. TRIN closes above 1
+    
+    Returns a Series with 'L' for long signals and 'N' for no signal.
+    """
+    ma_200 = data['Close'].rolling(window = 200).mean()
+
+    rsi_2 = calculate_rsi(data, period = 2)
+
+    start_date = data['Date'].min()
+    end_date = data['Date'].max()
+    trin_data = ohlc(symbol = 'RINT.Z', start_date = start_date, end_date = end_date)
+
+    trin_above_1 = trin_data['Close'] > 1
+
+    above_200_ma = data['Close'] > ma_200
+    rsi_below_50 = rsi_2 < 50
+
+    signals = Series('N', index = data.index)
+    signals[above_200_ma & rsi_below_50 & trin_above_1] = 'L'
+    return signals
\ No newline at end of file