Asia-based asset owners have an opportunity to leapfrog their peers in more developed markets in parts of their investment processes and decision-making. By embracing the growing importance of models and digitisation, they can deliver on their own evolving return expectations in today’s new market landscape. Conning Asia Pacific head of investment solutions Paul Sandhu shares his insights.
The need for this is increasingly acute, especially among insurance companies. The dynamics of the market are shifting as the economic cycle nears an inflexion point. In line with this, institutions are running out of asset classes to invest in that will enable them to generate the kinds of returns they want – and need.
All this is a result of nearly a decade of low interest rates that has, in recent months, given way to central banks around the world favouring higher interest rates. Coupled with increasing volatility since early 2018 and an ever-tense macro-political landscape, asset owners are now grappling with how to meet their long-term need for alpha.
This is easier said than done in an environment almost devoid of natural income. The search among many investors is for a balance between focusing to help generate higher returns on equities and turning back to lower-rate fixed income securities to reach their yield targets.
Multi-factor investing can fill these gaps for insurance firms in particular. It can help them capitalise on technological advances, regulatory requirements, a desire to reduce fees and greater innovation. A combination of these dynamics can lead to lower correlations with traditional asset classes in the strategic asset allocation (SAA), in turn reducing total portfolio volatility amid the goal of portfolio optimization.
In short, insurers can maximise risk-adjusted returns and diversification at the same time as leveraging uncorrelated return opportunities, all in a transparent way.
With improvements in tools, the quality of data and techniques based on experience in practice, the evidence supporting a greater role for factor-based strategies is based on statistical integrity of the performance and back-testing.
The right selection counts
Getting the factor strategies right, however, relies on taking a tailored approach for each institution. This is based on selecting the most relevant factors in order to meet a defined goal – and then combining them accordingly.
One of the main pitfalls with traditional approaches to factors is that most factor-based strategies use either one or just a few factors – such as value, momentum and/or market capitalisation. Yet a greater number of factors is required to fully decompose the extent and nuances of the market.
Another common misconception among investors is that the use of factors will replace fundamental investing. This is not the case; instead, using multiple factors is a way to diversify through a different process of portfolio construction, as well as to reduce reliance on market timing.
Further, smart beta and multi-factor strategies should not be put in the same bucket. They are as different from each other as fundamental and smart beta strategies, with the origination and design of the former focused more on general consumption.
Solution-focused factors
In theory, there has always been a place for factor investing. But the current point in the economic cycle requires insurance firms to find effective approaches to protect themselves against the ever-larger and more frequent events that are disrupting – and even threatening – the market.
With this new pressure and uncertainty for insurance portfolios, the goal is to tackle their challenge of finding reliable, sustainable and consistent returns.
For instance, while SAA for insurers requires financial modelling and stress-testing, the portfolios are sensitive to the volatility of asset classes and the correlation between them; as a result, as benchmarks shift, insurers need to be able to monitor portfolios more closely.
To address this, a multi-factor overlay can be created over the entire balance sheet.
This can drive a more manageable strategy that subsequently smoothens some of the market turbulence and enhances the overall risk-adjusted return of the entire asset portfolio.
Longer term portfolio management and planning must also be understood as drivers behind the application of multi-factor strategies.
One of the roles these can play in this context for instance, is in tackling behaviour bias. In scenarios where markets experience downturns, multi-factor investing offers an effective tool to prevent investors acting on inevitably heightened emotions.
At such times, the rationale for sticking with certain positions by following the process is clearer.
More broadly, in the face of emotionally-charged situations, the speed of decision-making that comes with a multi-factor investment strategy helps to ensure less correlated portfolios.
A new way to allocate
Ultimately, multi-factor investing is less about directional calls and more about appropriate compensation for taking certain risks.
For insurance companies looking to gain more experience in this space, perhaps the best starting point is to test the potential via a meaningful allocation to a multi-factor strategy, for the firm to be able to assess both the performance as well as the compatibility with their internal accounting and reporting systems.
Further, such experience can be a forward-looking step for an industry traditionally conservative and slower to change. For instance, multi-factor investing can make some insurance companies more aware of and exposed to the role and potential benefits of machine learning to drive parts of the investment function.
Once boards, finance teams and investment committees have the required comfort, the door to greater allocations will be opened. A