diff --git a/backtesting/filter/__init__.py b/backtesting/filter/__init__.py
index 6fd6e80..f7e8bb1 100644
--- a/backtesting/filter/__init__.py
+++ b/backtesting/filter/__init__.py
@@ -1,2 +1,3 @@
 from .backtest_filter import BacktestFilter
-from .volatility_regime_filter import VolatilityRegimeFilter
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+from .volatility_regime_filter import VolatilityRegimeFilter
+from .vvix_regime_filter import VVIXRegimeFilter
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diff --git a/backtesting/filter/vvix_regime_filter.py b/backtesting/filter/vvix_regime_filter.py
new file mode 100644
index 0000000..5c72a08
--- /dev/null
+++ b/backtesting/filter/vvix_regime_filter.py
@@ -0,0 +1,55 @@
+from datetime import datetime, timedelta
+from dotenv import load_dotenv
+from os import getenv
+from pandas import concat, DataFrame, Series
+
+from database.ohlc import ohlc
+
+from .backtest_filter import BacktestFilter
+
+load_dotenv()
+
+class VVIXRegimeFilter(BacktestFilter):
+
+    def __init__(self):
+        self.backtest_filter = self.filter()
+
+    def filter(self) -> DataFrame:
+        data_start_date = datetime.strptime(getenv('OPTION_DATA_START_DATE'), '%Y-%m-%d')
+
+        now = datetime.now()
+        vvix_data = ohlc(
+            symbol = 'VVIX.XO', 
+            timeframe = '1d', 
+            start_date = data_start_date - timedelta(weeks = 52), 
+            end_date = now
+        )
+
+        vvix_data.rename(columns = {'Timestamp': 'Date'}, inplace = True)
+
+        """""""""""""""""""""""""""""""""""""""""""""""""""""""""""""""""""""""""""""""""""""""""""""""""""""""""
+            Filtering is based on the previous day's close, so the current date can be included even though the 
+            data may not be availble yet.
+
+            This allows for utilizing the filter in live trading to decide whether to trade prior to market open.
+        """""""""""""""""""""""""""""""""""""""""""""""""""""""""""""""""""""""""""""""""""""""""""""""""""""""""
+        vvix_data = concat([
+            vvix_data,
+            DataFrame({
+                'Date': [datetime.combine(now, datetime.min.time())],
+                'Open': [0.0],
+                'High': [0.0],
+                'Low': [0.0],
+                'Close': [0.0],
+                'Volume': [0.0]
+            })], 
+            ignore_index = True
+        )
+
+        percent_rank = lambda x: Series(x).rank(pct = True).iloc[-1]
+        vvix_data['Percent Rank'] = vvix_data['Close'].shift(1).rolling(window = 252).apply(percent_rank)
+
+        filtered_data = vvix_data[vvix_data['Date'] >= data_start_date].copy()
+        filtered_data['Trade Allowed'] = filtered_data['Percent Rank'] < 0.50
+        filtered_data = filtered_data[['Date', 'Trade Allowed']].reset_index(drop = True)
+        return filtered_data
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