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

Trading VIX ETFs

Academic paper

AuthorsTony Cooper

Institute

?Double-Digit Numerics

Paper linkhttp://papers.ssrn.com/sol3/papers.cfm?abstract_id=2255327

Strategy in a nutshell

The strategy trades four volatility ETNs (XIV, VXX, ZIV, VXZ), ranking them daily by their 83-day momentum. The ETN with the highest positive momentum is held, and if none are positive, the portfolio stays in cash. Daily rebalancing ensures alignment with momentum signals, capturing trends in volatility ETNs efficiently.

Economic rationale

The strategy exploits the volatility premium, where long volatility provides crisis protection at a negative premium, and short volatility yields positive premium but high tail risk. Using a momentum filter allows dynamic exposure, capturing returns while reducing extreme losses in crisis periods.

Backtest performance

Annualised return84.6%

Volatility51.2%

Beta0.043

Sharpe ratio1.57

Sortino ratio0.14

Maximum drawdown-43.2%

Win rate55%

Full Python code

1from AlgorithmImports import *
2class TradingVIXETFs(QCAlgorithm):
3def Initialize(self):
4self.SetStartDate(2010, 1, 1)
5self.SetCash(100000)
6self.symbols = ["SVXY", "VXX", "ZIV", "VXZ"]
7self.data = {}
8self.period = 83
9self.SetWarmUp(self.period)
10for symbol in self.symbols:
11    data = self.AddEquity(symbol, Resolution.Daily)
12    self.data[symbol] = RollingWindow[float](self.period)
13def OnData(self, data):
14for symbol in self.data:
15    symbol_obj = self.Symbol(symbol)
16    if symbol_obj in data.Keys:
17        if data[symbol_obj]:
18            price = data[symbol_obj].Value
19            if price != 0:
20                self.data[symbol].Add(price)
21
22if self.IsWarmingUp: return
23self.Liquidate()
24returns = {}
25for symbol in self.symbols:
26    if self.data[symbol].IsReady:
27        prices = [x for x in self.data[symbol]]
28        returns[symbol] = prices[0] / prices[-1] - 1
29
30if len(returns) != 0:
31    sorted_by_return = sorted(returns.items(), key = lambda x: x[1], reverse = True)
32    
33    symbols = [x[0] for x in sorted_by_return]
34    top_symbol = symbols[0]
35    top_val = returns[top_symbol]
36
37    # if self.Portfolio.Invested:
38    #     if not self.Securities[top_symbol].Invested:
39    #         self.Liquidate()
40    #         if top_val > 0:
41    #             self.SetHoldings(top_symbol, 1/2)
42    # else:
43    #     self.SetHoldings(top_symbol, 1/2)
44    
45    if top_val > 0:
46        if self.Securities[top_symbol] != 0:
47            self.SetHoldings(top_symbol, 1/2)