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Portfolio construction

Volatility targeting

Takes the risk-parity mix and scales the whole portfolio up or down so that its volatility matches your target.

2 мин чтения · Попробовать в оптимизаторе портфеля ↗

Идея простыми словами

Most models decide the mix; this one decides the size. If the risk-parity mix is calmer than your target, it is leveraged; if it is wilder, part of the money stays in cash. When markets calm down, exposure rises; when they get rough, it falls.

Как считается

Compute the risk-parity weights and their volatility, multiply the weights by target ÷ volatility, capped at the maximum leverage. The rest (1 − sum) is cash, or borrowing if negative.

w = w_RP × k,   k = min(σ_target ÷ σ(w_RP), L_max)

Как использовать

  • Set Settings › target volatility (10% by default) to the yearly swing you are comfortable with.
  • Rebalance regularly: as volatility changes, the scaling changes too.
  • Use the maximum leverage setting to cap how far it can borrow.

Выводы

  • A scale above 1 means leverage: the study's notes show the factor.
  • Its Sharpe ratio is the same as risk parity's; only the size differs.

Пример

Running example (used in every portfolio guide): US500, GER40, gold (XAUUSD) and EURUSD, two years of daily data. Expected returns 8%, 7%, 7% and 1% a year; volatilities 18%, 20%, 15% and 7%. US500 and GER40 move together (correlation about 0.7); gold hardly moves with the indices (about 0.04). Risk parity alone has 8.5% volatility; to reach 10% the weights are multiplied by 1.17: 21% US500, 19% GER40, 25% gold, 53% EURUSD, 117% invested in total. Return 5.2%, volatility 10.0%.

Входные данные примера условны; веса и цифры — это то, что для них выдаёт наш оптимизатор.

На что обратить внимание

  • Leverage magnifies losses as well as gains, and paper trading charges margin for it.
  • Volatility estimated on the past reacts with a delay to a sudden storm.

Немного истории

Volatility targeting spread after 2008 in risk-parity and managed-futures funds. Moreira and Muir, "Volatility-Managed Portfolios" (Journal of Finance, 2017), found that cutting exposure when volatility is high raised risk-adjusted returns for many strategies.

Только образовательный материал. Ни одна модель портфеля не знает будущего: все они работают на оценках из прошлого, и ничто здесь не является инвестиционной рекомендацией.