Stronghold EUR: lower risk in September and negative yield advantage
Head of Equity Strategy
Summary: Stronghold EUR delivered 0.2% return in September compared to 0.7% for the benchmark as higher rates negatively impacted the portfolio. During September and early October the model has reduced exposure in momentum equities as the volatility structure in this asset class has changed for the worse as a result of the mini-crash in US momentum equities during September. The model has added the global properties asset class for the first time since inception.
September was a more difficult month for the Stronghold EUR delivering only 0.2% compared to 0.7% for the benchmark portfolio as rates climbed on the backdrop of higher risk sentiment by global investors. The Stronghold EUR portfolio is up 12.1% as of September compared to the benchmark up 3.5% in the same period. The model’s significant exposure to minimum volatility equities and long duration bonds have contributed to performance on a relative and absolute basis. The annualized Sharpe ratio is currently 0.9 and this year’s performance relative to the benign drawdown in Q4 2018 is among the better when we compare the model against its peers. Clients have noticed this leading to material client net inflow into the strategy in Q3 2019.
The strategy has a reference benchmark consisting of 65 % global government bonds (EUR-hedged) and 35 % developed market equities (EUR hedged). Stronghold performance includes trading costs and management fee. Past performance does not guarantee future results, which may vary. The value of investments and the income derived from investments will fluctuate and can go down as well as up. A loss of capital may occur.
During September the model slightly reduced risk in the portfolio reducing its exposure in momentum equities as the mini-crash in US momentum equities caused the volatility structure to change. In early October the model has further reduced exposure in momentum equities and increased the government exposure while for the first time since the portfolio went live added exposure to the global properties asset class.
Currently the portfolio has 40.3% of its weight in government bonds and equities only stand at 32% the lowest exposure since late May. But as the chart with asset class weights over time shows the portfolio changes have been smooth except for Q4 last year and the portfolio has not yet experienced changing its overall exposure profile to a very defensive portfolio. The volatility structure remains still very balanced, but this could change fast in Q4 with the potential negative fallout from Brexit and US-China trade negotiations.
In several discussions with potential clients, that want a defensive portfolio because they believe the economy is likely going into a recession or just want to protect capital from large swings, we constantly highlight the fact that government bonds yield so little these days that a defensive portfolio today is most likely to deliver negative expected real returns after fund costs. The $17trn worth of negative yielding bonds have effectively killed the strategic defensive portfolio.
The Stronghold EUR portfolio offers a tactical approach to asset allocation only taking risks in equities when the volatility structure allows it. On the other hand, the portfolio will go ultra-defensive in a 2008 crisis repeat where correlations across everything rose dramatically offering little diversification effects. Many clients then say why would I be in negative yielding assets if that scenario happens? Our view is that -1% over 12 months is better than potentially -20% due to excessive exposure in equities during a recessionary period.
The key risks for the Stronghold EUR portfolio at this point are significantly higher rates which would create losses in the bond part of the portfolio. The portfolio also has unhedged USD exposure through its exposure to minimum volatility equities and should the USD suddenly drop in value this will have a negative impact on performance. A rapidly changing volatility structure could also create losses in the portfolio as the model cannot predict changes but only react intelligently after the fact.
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