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多资产市场广度动量策略

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学术论文

Protective Asset Allocation (PAA): A Simple Momentum-Based Alternative for Term Deposits

作者保护性资产配置（PAA）；一种基于简单动量的定期存款替代方案 [点击查看论文]

机构

NLVrije Universiteit Amsterdam
?VU University Amsterdam
?TrendXplorer

论文链接https://papers.ssrn.com/sol3/papers.cfm?abstract_id=2759734

策略概要

该策略涉及12种跨不同资产类别的ETF：美国股票（SPY、QQQ、IWM）、全球股票（VGK、EWJ）、新兴市场（EEM）、另类资产（GSG、GLD、IYR）和债券（HYG、LQD、TLT、IEF）。资产基于12个月的动量指标（MOM > 0）进行选择。投资者使用保护因子2计算债券比例（BF）。选择动量为正的前6名资产作为风险投资组合。风险资产的比例计算为（1-BF）/BF，投资组合中的资产等权重。

II. 策略合理性

该策略在熊市期间提供比传统双重动量策略更高的保护，因为它倾向于将更高比例的资金转移到低风险资产中。因此，即使PAA策略在原始回报方面表现不如传统双重动量策略，它也往往能实现更好的风险特征，即显著更低的跌幅和标准差。

回测表现

波动率7.9%

夏普比率1

索提诺比率0.28

最大回撤-8.8%

胜率66%

完整 Python 代码

1from AlgorithmImports import *
2from collections import deque
3class MultiAssetMarketBreadthMomentum(QCAlgorithm):
4def Initialize(self):
5self.SetStartDate(2008, 1, 1)
6self.SetCash(100_000)
7
8self.symbols: List[str] = [
9    'SPY', 'QQQ', 'IWM', 'VGK', 'EWJ', 'EEM', 'GSG', 'GLD', 'IYR', 'HYG', 'LQD', 'TLT'
10]
11self.safe_bond: str = 'IEF'
12
13period: int = 12 * 21
14self.data: Dict[str, deque] = {}
15self.sma: Dict[str, SimpleMovingAverage]  = {}
16
17for symbol in self.symbols:
18    self.AddEquity(symbol, Resolution.Daily)
19    self.data[symbol] = deque(maxlen = period)
20    self.sma[symbol] = self.SMA(symbol, period, Resolution.Daily)
21        
22    history: DataFrame = self.History(self.Symbol(symbol), period, Resolution.Daily)
23    if not history.empty:
24        closes: Series = history.loc[symbol].close
25        for time, close in closes.items():
26            self.sma[symbol].Update(time, close)
27
28self.AddEquity(self.safe_bond, Resolution.Daily)
29self.last_month: int = -1
30
31def OnData(self, slice: Slice) -> None:
32if self.last_month == self.Time.month:
33    return
34self.last_month = self.Time.month
35
36mom: Dict[str, float] = {}
37for symbol in self.symbols:
38    symbol_obj: Symbol = self.Symbol(symbol)
39    # SMA data is ready.
40    if self.sma[symbol].IsReady:
41        if symbol_obj in slice.Bars:
42            price: float = slice.Bars[symbol_obj].Value
43            if price != 0:
44                mom[symbol] = price / self.sma[symbol].Current.Value - 1
45    else:
46        return  # Wait for every asset.
47        
48if len(mom) != 0:
49    # Bond fraction calc.
50    good_assets: List = sorted([x[0] for x in mom.items() if x[1] > 0], key = lambda x: x[1], reverse = True)[:6]
51    N: int = len(self.symbols)
52    n: int = len(good_assets)
53    a: int = 2
54    n1: float = a*N/4
55    BF: float = (N-n)/(N-n1)
56    
57    bond_share: float = (1-BF)/BF
58    # Trade execution.
59    self.Liquidate()
60    
61    # Risky part.
62    # "leverage" ratio in case there's two parts of portfolio - risky as well as safe part.
63    ratio: float = 0.5 if bond_share != 0 else 1
64    
65    for symbol in good_assets:
66        self.SetHoldings(symbol, ratio * (1/n))
67    
68    # Bond part.
69    self.SetHoldings(self.safe_bond, ratio * bond_share)