bonds, equities · United States · ETFs, options · Monthly · United States Free

Portfolio Hedging Using VIX Options

Academic paper

Paper linkhttps://papers.ssrn.com/sol3/papers.cfm?abstract_id=2792358

Strategy in a nutshell

The strategy combines a 60% stock and 40% bond portfolio using SPY for equities and IEF for bonds, with a small allocation to VIX call options (0–100 bps) across one- to four-month maturities. The allocation is adjusted dynamically based on VIX levels, rolled before expiration, and reinvested into the stock/bond portfolio, providing a systematic hedge against market volatility.

Economic rationale

The strategy exploits the mean-reverting behavior of volatility, buying more VIX calls when volatility is low and fewer when it is high. By carefully selecting moneyness, expiry, and timing, the investor avoids overpaying for protection, maintaining an optimal risk-return balance while hedging against market turbulence.

Backtest performance

Annualised return8.63%

Volatility8.44%

Beta0.636

Sharpe ratio1.02

Sortino ratio0.504

Maximum drawdown-10.47%

Win rate35%

Full Python code

1from AlgorithmImports import *
2class PortfolioHedgingUsingVIXOptions(QCAlgorithm):
3def Initialize(self):
4self.SetStartDate(2010, 1, 1)
5self.SetCash(1000000)
6
7data = self.AddEquity("SPY", Resolution.Minute)
8data.SetLeverage(5)
9self.spy = data.Symbol
10
11data = self.AddEquity("IEF", Resolution.Minute)
12data.SetLeverage(5)
13self.ief = data.Symbol
14
15data = self.AddEquity("VIXY", Resolution.Minute)
16data.SetLeverage(5)
17self.vix = data.Symbol
18
19option = self.AddOption('VIXY', Resolution.Minute)
20option.SetFilter(-20, 20, 25, 35)
21
22def OnData(self,slice):
23for i in slice.OptionChains:
24    chains = i.Value
25    # Max 2 positions - spy and ief are opened. That means option expired.
26    invested = [x.Key for x in self.Portfolio if x.Value.Invested]
27    if len(invested) <= 2:
28        calls = list(filter(lambda x: x.Right == OptionRight.Call, chains))
29        
30        if not calls: return
31    
32        underlying_price = self.Securities[self.vix].Price
33        expiries = [i.Expiry for i in calls]
34        
35        # Determine expiration date nearly one month.
36        expiry = min(expiries, key=lambda x: abs((x.date() - self.Time.date()).days - 30))
37        strikes = [i.Strike for i in calls]
38        
39        # Determine out-of-the-money strike.
40        otm_strike = min(strikes, key = lambda x:abs(x - (float(1.35) * underlying_price)))
41        otm_call = [i for i in calls if i.Expiry == expiry and i.Strike == otm_strike]
42
43        if otm_call:
44            # Option weighting.
45            weight = 0.0
46            
47            if underlying_price >= 15 and underlying_price <= 30:
48                weight = 0.01
49            elif underlying_price > 30 and underlying_price <= 50:
50                weight = 0.005
51              
52            if weight != 0: 
53                options_q = int((self.Portfolio.MarginRemaining * weight) / (underlying_price * 100))
54
55                # Set max leverage.
56                self.Securities[otm_call[0].Symbol].MarginModel = BuyingPowerModel(5)
57                
58                # Sell out-the-money call.
59                self.Buy(otm_call[0].Symbol, options_q)
60                
61                self.SetHoldings(self.spy, 0.6)
62                self.SetHoldings(self.ief, 0.4)