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4 Jan 2016

QLAB Invest - Update December 2015
    

Absolute-Return Strategy Performance as of 31 December 2015

MULTI-ASSET LONG ONLY
MTD
1Y
3Y
5Y
10Y
RISK (10Y)
MDD(10Y)
QLAB Asset Allocation
-0.28%
-0.48%
2.90%
3.05%
7.28%
5.57%
-7.20%
QLAB Dynamic Allocation
-0.28%
-0.75%
7.09%
7.31%
13.57%
12.21%
-13.65%
Naïve Market Portfolio[1]
-0.20%
-7.03%
-1.32%
0.05%
4.92%
8.74%
-26.37%


COMMODITY LONG/SHORT
MTD
1Y
3Y
5Y
10Y
RISK (10Y)
MDD(10Y)
QLAB Quadrant Commodity L/S
-0.19%
2.90%
3.72%
1.65%
17.39%
15.78%
-19.15%
Commodity Market[2]
-1.17%
-20.81%
-13.08%
-11.65%
-2.86%
17.49%
-54.68%

RETURNS: Annualised if >1Y   |   RISK: Annualised standard deviation or volatility, daily data   |   MDD: Maximum drawdown, peak to trough.
Index live dates vary, see
www.qlabi.com for more details or QLAB <GO> on Bloombergy.
Strategy indices calculated net of trading costs, gross of product fees. Investable products may have lower returns and shorter track records.
[1] Naïve market portfolio is a performance reference, comprising 25% US equities, 25% Commodities, 20% FX, 30% US Fixed Income.
[2] Commodity market is a performance reference, comprising 10 S&P GSCI single total return commodities indices, equal weight.


Download this Newsletter in PDF  here -> QLAB_UPDATE_DECEMBER_2015.pdf

SUMMARY

2015 is surely another year where much will be written about who got which calls right, that volatility was unexpected, that central banks confounded economic forecasts or that a particular fixed mix of equities and bonds outperformed most active managers. Hindsight is a powerful bias and it’s easy to confuse skill with luck, however a year ago, who could have skilfully predicted the returns of the major benchmarks or which would be the one best strategy to hold in advance?

QLAB INVESTMENT UNIVERSE 2015 RETURNS
 
OTHER MARKET 2015 RETURNS
US Equities
0.69%
 
UK Equities
-5.88%
Commodities (CCI)
-15.31%
 
Europe ex UK Equities
6.14%
2YR US Treasury Bond
0.53%
 
Emerging Market Equities
-5.76%
5YR US Treasury Bond
1.52%
 
Japanese Equities
8.12%
G10 FX long against USD
-6.99%
 
UK Core Gilts
0.57%
USD Cash
0.20%
 
German 7-10YR Bunds
0.82%
 
 
 
Global Corporate Bonds
-0.24%
 
 
 
GBP Cash
0.51%
 
 
 
EUR Cash
-0.07%


The left table shows the total returns for the assets in the QLAB multi-asset strategy investment universe. Whilst we are not happy with the slightly negative 1 year returns of the QLAB strategies, given the long-only constraint it is easy to see it could have been worse had it not been for the active asset selection process ensuring we avoided larger losses. As of mid-August 2015 the YTD strategy performance was respectable and the strategies were at all-time-highs, driven by good equity and bond performance and lack of commodity and FX exposure. However, the US equity market correction that occurred in August eroded those returns in a matter of days. Equities were exited as a result and the portfolio went defensively into fixed income. Since then the bonds have also had slightly negative returns due to rising interest rates.

With a glance at a sample of other markets’ local total returns in the right table, a broader investment universe would not have been much help, except (with hindsight) for European and Japanese equities, thanks to their QE programmes.

Broad hedge fund indices have not fared much better with YTD performance as of 30-Dec-15 standing at -3.49% for the HFRX Global Hedge Fund Index and -1.42% for the HFRX Macro/CTA Index. By contrast, the QLAB Commodity Long/Short strategy ended the year up 2.9%, which against very weak commodity markets, we feel is very satisfactory.

Over 3 years and beyond, the QLAB multi-strategy returns are more in line with our expectations, and given the strategy indices and the underlying models have now turned 5 years old, it is appropriate to look back at the key asset decisions and impact on returns and risk in more detail.

REVIEW OF 5 YEARS LIVE PERFORMANCE

As you will recall, the QLAB models are fully systematic, meaning rules driven, in order to avoid behavioural and emotional biases. Secondly, the models are reactive, not predictive and use medium term price momentum and volatility as inputs aiming to steer exposure to the better performing assets and avoid the worst performing assets. Finally, sophisticated risk management and portfolio construction techniques convert asset selection decisions into portfolio weights used to calculate the strategy index performance. The index levels are published daily, net of transaction fees but gross of product fees, to allow for meaningful analysis and replication under license in a wide variety of formats.

FIGURE 1: LIVE INDEX PERFORMANCE, REBASED TO 100 ON 31-DEC-2010



Figure 1 shows live index performance compared to the naïve market portfolio. QLAB Asset Allocation’s ambition to outperform the naïve market portfolio (absolute and risk adjusted) with a maximum volatility of 6% and avoid the major drawdowns has been achieved.
 
QLAB Dynamic Allocation’s ambition to significantly outperform QLAB Asset Allocation with maximum volatility of 15% and drawdown tolerance of -15% has also been achieved. It is also worth comparing QLAB Dynamic Allocation to the S&P500 which did have higher return but with higher volatility and a much larger drawdown.

The correlation of both QLAB strategies to US equities over this time was 0.32 indicating the diversification benefits of the QLAB strategies in an overall portfolio context.

FIGURE 2: LIVE DRAWDOWNS



Figure 2 shows the live drawdowns. QLAB Asset Allocation has consistently shown lower drawdowns than the market it is investing in, as a result of the active asset selection. More recently, the market has declined significantly with commodity and FX sell-offs and the strategy has successfully avoided this large drawdown. We know from behavioural studies that loss of capital, or drawdowns can force even quite passive investors to become active at the wrong time and it is one of QLAB’s main ambitions that our clients can sleep well knowing that drawdown risk is being effectively managed.
 
QLAB Dynamic Allocation is compared to US equities and a broad Commodity index (CCI). Against equities, drawdowns are similar, only occasionally higher than equities, but the largest equity drawdown of -18% has been avoided. Versus Commodities the strategy has been even more successful, commodities are now in one of the largest drawdowns of all-time, perhaps a reminder that they are an asset class only to be played actively.
 
Whilst investors cannot avoid some level of drawdown risk, the QLAB asset allocation approach can exit whole sectors and asset classes which creates asymmetric or convex returns versus the investment universe. This convexity is truly in line with investor loss aversion, which is fearing losses more than appreciating gains. Traditional benchmark investing, which is deviating from neutral positions, cannot achieve this property and so the QLAB solutions sit well alongside traditionally managed strategies to add convexity to an overall portfolio.

FIGURE 3: LIVE ROLLING 1 YEAR VOLATILITY




Figure 3 shows the rolling 1 year live volatility, based on daily data. QLAB Asset Allocation managed to stay below its target maximum of 6% with the exception of a few months in 2011 and was more stable than the market volatility. QLAB Dynamic Allocation was almost entirely below its target maximum of 15% and also more stable than the equity market. Volatility is something that can be controlled in active strategies, but less so in benchmark driven strategies where traditional benchmarks can show highly variable volatility.

FIGURE 3: LIVE ASSET ALLOCATION




Figure 4 shows that Asset allocation moves are decisive, yet intuitive, reacting to current market conditions, not making predictions about the future. Any one single allocation move may or may not pay off, but over time the consistent systematic application of the models keeps the portfolio exposed to the stronger performing assets and avoids the weaker assets. This results in lower drawdowns, more stable volatility and outperformance versus the market over a 3-5 year investment horizon.
 
OUTLOOK
 
Whilst market predictability will always be weak, exploiting persistence in momentum and volatility in a highly disciplined fashion continues to add significant value, especially in managing drawdown risk, which is arguably the true driver of irrational investor behaviour. The QLAB models have been effective now for 5 years and the various strategies provide robust building blocks for any investor’s liquid portfolio with more stable risk and return properties than benchmark driven or buy-and-hold approaches. Going in to 2016, the QLAB Multi-asset strategies remain cautiously positioned out of equities and commodities.
 
NEWS – QLAB OFFERS CUSTOM STRATEGIES
 
This year also saw QLAB introduce custom strategies for institutions. These strategies use exactly the same investment models as our live strategies but the models are applied to the investment universe defined by the institution with a corresponding set of investment constraints. These may be set to position the strategies alongside other offerings on the product shelf, or comply with regulations such as UCITS. The resulting strategies add convexity to client portfolios through lower drawdown risk than comparable benchmark investing with strong outperformance across an investment cycle, and are delivered via a simple and low-cost license agreement.
 
Finally, all of us at QLAB would like to wish you, our clients, followers and partners, a happy, healthy and successful 2016.
 
For more information on QLAB Invest, visit www.qlabi.com or Email us at info@qlabi.com






Close disclaimer

DISCLAIMER: This document does not constitute an offer, a solicitation, an advice or a recommendation to purchase or sell any investment products associated with the material described herein. The purpose of this document is to describe the principles, research and ideas behind the QLAB Invest strategy indices. Prior to an investment in any product tracking a strategy index, you should make your own appraisal of the investment risks as well as from a legal, tax and accounting perspective, without relying exclusively on the information provided by QLAB Invest. Investment products tracking the indices must be issued or/and marketed by a regulated company. This document is strictly for informative purpose. The single source of the underlying asset data is Thomson Reuters Datastream and QLAB Invest cannot guarantee the correctness of the underlying asset data and cannot be held legally responsible in this regard. Any references made to historical performance up to the official live inception do not reflect actual live performance and can be subject to selection, curve fitting and other statistical biases. Performance in investment products linked to the indices may be reduced by the effect of commissions, fees or other charges in excess of those already factored into the index calculations. The level of the indices will fluctuate due to the volatility of the underlying exposures and past performance or volatility is not necessarily indicative of future results.