bonds, commodities, equities, REITs · Global · ETFs · Monthly · Global Free

Antonacci’s Dual Momentum

Academic paper

AuthorsGary Antonacci

Institute

?Portfolio Management Consultants

Paper linkhttps://papers.ssrn.com/sol3/papers.cfm?abstract_id=2042750

Strategy in a nutshell

Construct long-only, equal-weighted portfolios across four modules: (1) U.S./Foreign equities, (2) High-yield/credit bonds, (3) Equity/mortgage REITs, and (4) Gold/Treasuries. Within each module, select the better-performing asset using 12-month relative momentum. If no asset shows positive absolute momentum versus Treasury bills, allocate to BIL. Portfolios are equally weighted across modules and rebalanced monthly.

Economic rationale

Behavioral biases and trend persistence drive momentum. Absolute momentum captures asset trends, while relative momentum enhances diversification. This approach mitigates specific risk factors, reduces portfolio volatility, and maintains consistent returns across market regimes.

Backtest performance

Annualised return14.9%

Volatility13.93%

Beta0.218

Sharpe ratio1.07

Sortino ratio0.404

Maximum drawdown-10.92%

Win rate82%

Full Python code

1from AlgorithmImports import *
2#endregion
3
4class AntonaccisDualMomentum(QCAlgorithm):
5
6def Initialize(self):
7self.SetStartDate(2000, 1, 1)  
8self.SetCash(100000)
9
10period:int = 12 * 21
11self.SetWarmUp(period, Resolution.Daily)
12
13self.treasury_bill:Symbol = self.AddEquity("BIL", Resolution.Daily).Symbol
14
15# subscribe assets for each module
16self.equities:List[Symbol] = [self.AddEquity(x, Resolution.Daily).Symbol for x in ["SPY", "EFA"]]
17self.bonds:List[Symbol] = [self.AddEquity(x, Resolution.Daily).Symbol for x in ["HYG", "LQD"]]
18self.reits:List[Symbol] = [self.AddEquity(x, Resolution.Daily).Symbol for x in ["MBB", "VNQ"]]
19self.commodities:List[Symbol] = [self.AddEquity(x, Resolution.Daily).Symbol for x in ["TLT", "GLD"]]
20
21# traded modules
22self.modules:List[List[Symbol]] = [self.equities, self.bonds, self.reits, self.commodities]
23
24self.momentum:dict[Symbol, RateOfChange] = {}
25
26self.momentum_treshold:float = 0.
27
28for module in self.modules:
29    for asset in module:
30        # subscribe ROC indicator
31        self.momentum[asset] = self.ROC(asset, period, Resolution.Daily)
32
33self.recent_month:int = -1
34
35def OnData(self, data:Slice) -> None:
36if self.IsWarmingUp: return
37
38# monthly rebalance
39if self.Time.month == self.recent_month:
40    return
41self.recent_month = self.Time.month
42
43tbill_allocation_count:int = 0
44long:List[Symbol] = []
45
46for module_index, module in enumerate(self.modules):
47    if all(self.momentum[x].IsReady for x in module):
48        # select and buy the better-performing asset as representative of the module
49        module_perf_values:List[float] = [self.momentum[x].Current.Value for x in module]
50        max_module_perf:float = max(module_perf_values)
51        best_performing_asset:Symbol = module[module_perf_values.index(max_module_perf)]
52
53        if max_module_perf > self.momentum_treshold:
54            long.append(best_performing_asset)
55        else:
56            tbill_allocation_count += 1
57
58# tbill allocation weight relative to total number of modules with ROC data ready
59traded_asset_count:int = (tbill_allocation_count + len(long))
60tbill_allocation:float = tbill_allocation_count / traded_asset_count if traded_asset_count != 0 else 0
61
62# liquidate
63invested:List[Symbol] = [x.Key for x in self.Portfolio if x.Value.Invested]
64for symbol in invested:
65    if symbol not in long + [self.treasury_bill]:
66        self.Liquidate(symbol)
67
68# trade etfs
69for symbol in long:
70    if symbol in data and data[symbol]:
71        self.SetHoldings(symbol, 1 / traded_asset_count)
72
73# trade tbills
74if self.treasury_bill in data and data[self.treasury_bill]:
75    self.SetHoldings(self.treasury_bill, tbill_allocation)