Equity · United States · ETFs · Daily · United States Free

Trading VIX ETFs v2

Academic paper

Paper linkhttps://papers.ssrn.com/sol3/papers.cfm?abstract_id=2753300

Strategy in a nutshell

The strategy trades SPY and SH for S&P 500 exposure and VXX and XIV for short-term VIX futures exposure. It calculates the relative difference between front-month VIX futures and spot VIX to identify contango or backwardation:

Contango (futures > spot): Buy XIV and hedge with SH.

Backwardation (futures < spot): Buy VXX and hedge with SPY.

Positions are closed when the relative basis crosses predetermined sell thresholds. The strategy performs best with a 0% hedge ratio, but alternative hedge levels can be applied to adjust risk-return profiles.

Economic rationale

VIX futures consistently trade at a premium to spot VIX because VIX is non-tradable and investors pay for volatility protection. Research (Simon & Campasano, 2014) shows that VIX futures prices revert toward the spot index: futures above VIX tend to fall, while those below tend to rise. This mispricing, driven by risk aversion and volatility hedging demand, creates persistent opportunities for systematic trading.

Backtest performance

Annualised return69%

Volatility39%

Beta-0.243

Sharpe ratio2.11

Sortino ratio0.239

Maximum drawdown-24.5%

Win rate53%

Full Python code

1from QuantConnect.Python import PythonQuandl
2from AlgorithmImports import *
3class TradingVIXETFsv2(QCAlgorithm):
4def Initialize(self):
5self.SetStartDate(2010, 1, 1)
6self.SetCash(100000)
7self.vixy = self.AddEquity('VIXY', Resolution.Minute).Symbol
8
9# Vix futures data.
10self.vix_future = self.AddFuture(Futures.Indices.VIX, Resolution.Minute)
11# Vix spot.
12self.vix_spot = self.AddData(CBOE, 'VIX', Resolution.Daily).Symbol
13
14self.vix_future.SetFilter(timedelta(0), timedelta(30))
15
16# Vix futures active contract updated on expiration.
17self.active_contract = None
18
19self.Schedule.On(self.DateRules.EveryDay(self.vixy), self.TimeRules.AfterMarketOpen(self.vixy, 1), self.Rebalance)
20def Rebalance(self):
21# split data error prevention
22if self.Time.year == 2021 and self.Time.month == 5:
23    self.Liquidate()
24    return
25    
26if self.active_contract:
27    if self.Securities.ContainsKey(self.vix_spot):
28        spot_price = self.Securities[self.vix_spot].Price
29        vix_future_price = self.active_contract.LastPrice
30        if spot_price == 0 or vix_future_price == 0: 
31            return
32        
33        relative_basis = vix_future_price / spot_price
34        
35        # BU 8%, SU 6%, BL -8%, SL -6% thresholds.
36        # Short volatility.
37        if relative_basis > 1.08:
38            if not self.Portfolio[self.vixy].IsShort and self.Securities[self.vixy].Price != 0:
39                self.SetHoldings(self.vixy, -1)
40        
41        if relative_basis >= 1.06 and relative_basis <= 1.08 and self.Portfolio[self.vixy].IsLong:
42            self.Liquidate(self.vixy)
43        
44        if relative_basis < 1.06 and relative_basis > 0.94:
45            if self.Portfolio[self.vixy].Invested:
46                self.Liquidate(self.vixy)
47        
48        if relative_basis <= 0.94 and relative_basis >= 0.92 and self.Portfolio[self.vixy].IsShort:
49            self.Liquidate(self.vixy)
50        
51        # Long volatility.
52        if not self.Portfolio[self.vixy].IsLong and relative_basis < 0.92:
53            if self.Securities[self.vixy].Price != 0:
54                self.SetHoldings(self.vixy, 1)
55def OnData(self, slice):
56chains = [x for x in slice.FutureChains]
57cl_chain = None
58if len(chains) > 0:
59    cl_chain = chains[0]
60else:
61    return
62
63if cl_chain.Value.Contracts.Count >= 1:
64    contracts = [i for i in cl_chain.Value]
65    contracts = sorted(contracts, key = lambda x: x.Expiry)
66    near_contract = contracts[0]
67    self.active_contract = near_contract