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How we're challenging traditional investment assumptions

October 29th 2015

The industry needed a more personal approach

Independent financial advisors and discretionary investment managers tend to serve retail clients by relying on a very narrow definition of risk profiling. Each client is typically placed into one of between 10 and 30 predefined model portfolios, where they are charged fairly high management fees for the privilege.

At ETFmatic, we firmly believe that this combination is not in the client's best interests. This is down to a number of reasons. Firstly, the standard risk profiling used by these intermediaries often focuses on very narrow measures of risk (such as volatility or broad estimates of acceptable allocations to equity versus fixed income). Volatility is a concept very few retail clients understand and the typically broad allocations between equities and fixed income don’t differentiate between the risk profiles of different markets - such as emerging market equities versus a broad FTSE 100 index, or an IPO for example. This makes for very blunt risk profiling, and where volatility as a proxy for risk is concerned, the FCA themselves argue that this is not a sufficient measure of risk.

Secondly, model portfolios are a crude way to allocate assets for widely differing client objectives. As such, we believe there is a need for a more personalised approach to both risk profiling and investment management. Below we outline exactly how ETFmatic works to better serve an individual client’s investment needs.

Allowing our clients to define their investment preferences in a number of ways ensures that we can tailor the management of each goal to the clients’ wishes.

The core idea behind ETFmatic

ETFmatic provides a personalised investment management approach that until now was only really available to ultra-high-net-worth individuals. We do this by allowing our clients to define highly granular investment strategies for each goal, and manage the journey through asset allocation, ongoing rebalancing and trade execution on a goal-by-goal basis. This provides the best possible outcome for each goal given the constraints. This is all done in a highly systematic manner and by keeping operational costs low.

You might call ETFmatic ‘vendor-agnostic’. We certainly argue that significant longer term opportunities exist in optimising the mass-market (or non-wealth type solutions of very small account sizes) which might be funded by just £50 per month, for example. The ‘smart’ execution - or reducing the number of portfolio trades etc - is the key to reducing the total costs to our clients.

We have a very clear focus on ensuring that operational costs are kept as low as possible. In contrast to many alternative offerings, we are fully aware of how ‘excessive rebalancing’ affects customer outcomes (due to taxes among other things). From allocating regular asset purchases, progressively moving a client’s investments towards the dynamic target asset allocation, and adjusting for multiple divestment options, our approach has been built from the ground up - to make sure the ETFmatic solution is 100% aligned with its client’s needs.

Profiling that challenges the traditional classification of client preferences

A big noise is made of achieving the best returns. Yet rarely is the question asked about what ‘best’ actually means?”. To us, it means managing our clients’ investments in a way that they can not only achieve their goals but have the reassurance that whatever the market conditions, their portfolio is managed precisely in accordance with these goals.

We allow an investor to define investment preferences on a goal-by-goal basis, using a sophisticated and efficient automated solution. Where goal creation is concerned we naturally look at cognitive variables, including an investor’s attitude to risk and time horizon. In addition, we will look at the required speed of reaction to market movements as well as the magnitude and direction of trading in response to these developments. And we also ask the client what kind of withdrawal strategy they expect to have for the goal once they stop contributing.

Finally, we create an initial optimal solution in the mean-variance framework: an optimised, bottom-up solution parameterised with the estimated cognitive variables. We then use the investment preferences that the client has provided for each goal to ensure that the goal always stays within the parameters that we have been given.

Allowing our clients to define their investment preferences in a number of ways ensures that we can tailor the management of each goal to the clients’ wishes. It also allows us to tailor communications to those clients - to explain why we are making the asset allocation and trading decisions we make on their behalf.

An asset allocation tailored to each specific goal

The asset allocation is the key to achieving an investor’s goals. An investor’s choice and mix of different asset class exposures will have a far bigger impact on their risk-adjusted returns than any individual choice of specific security or fund. And the right mix of asset classes (subject to disciplined rebalancing) offers crucial diversification benefits across a variety of market conditions, while also reducing correlation risks. This helps protect an investor’s risk-adjusted returns.

Effectively, our technology takes the investment preferences that the client has given us for each goal, and uses this to determine the appropriate target asset allocation. The investment preferences defined for each goal are more comprehensive than what is usual. It means we can avoid some of the more sweeping market assumptions based on rules of thumb, like saving 15% per year over 35 years will provide a 2/3 income replacement in retirement, or that you should determine your equity exposure by subtracting your age from 100. While these ‘guidelines’ might be useful in avoiding the simplest personal finance mistakes, they ignore too many short-term variables. They usually lack sufficient response to the big market picture in terms of dynamic asset allocation adjustment too.

Having identified the target asset allocation for each goal, we finally identify the trades required to bring the goal in line with the target asset allocation.

A dynamic approach to instrument selection and rebalancing

Using only the most cost-effective ETF funds, our process and technology automatically rebalances an individual portfolio towards the exposures that provide an investor the best chance of achieving their financial goals. The rebalancing is a very important process sub-component - often overlooked - and is implemented by an almost algorithmic-trading type process of automating, optimising and allocating new contributions.

Focusing the asset allocation on indices gives us an additional level of flexibility when selecting (at any given point in time) the most appropriate instruments to use in our portfolio rebalancing process. ETF providers are well known for continuously driving down their costs and passing these savings on to their customers. As such, we continuously evaluate which ETFs are most appropriate for any given index and incorporate this into the overall rebalancing process.

ETFmatic's methodology has been peer reviewed over the last two years, and we are continuosly implementing new improvements. You can always read the latest version of our whitepaper here and are welcome to share any questions or feedback emailing us at whitepaper@etfmatic.com.

With all investments your capital is at risk and the value of your investments and the income deriving from it can rise as well as fall. Past performance is not a guide to future performance.