The efficiency, speed and low cost of Robo Advisory models has been described at great length. Firms such as WealthFront and Betterment claim to have blossomed in its warm glow, and industry titans such as Fidelity are now joining the party with their new Fidelity Go product. However, even as parts of the industry are playing catch-up to Robo Advisory 1.0 - other, nimbler players, are already forging ahead with Robo Advisory 2.0. Firms such as Huygens Capital, Hedgeable, Lyons Wealth and even our own Privé Manager are already incorporating tactical signals, or the ability to create bespoke portfolios into their robo offerings.
With Robo Advisory 2.0, the tactical signals typically aim to reduce the impact of equity market dips by using a risk-prediction system. Such a risk-prediction system may take into account a host of variables - such as implied volatilities, credit spreads or the equity risk premium with the overall aim being to generate a reliable signal of when to decrease the exposure to equity markets - and when to revert to full equity exposure again. Over the long-term, by avoiding the drawdowns, such a methodology aims to outperform a pure ‘buy and hold’ equity exposure - and indeed the track-records of some funds which do follow such a methodology for a single market have outperformed a long-only strategy.
By employing tactical signals within a model portfolio, the portfolio can ‘tilt’ its exposure away from, or towards equities depending on such signals. The model therefore becomes more dynamic, and not just a static allocation with fixed weights.
Equally the standard robo-generated model is not typically successful at incorporating views or preferences expressed by the individual client. Usually, with Robo Advisory 1.0, there is a selection of 3-5 static model portfolios - and, based on your risk profiling, you may be allocated into one of these. This is not so helpful if you have strong views on a certain market, are already exposed through assets/liabilities not captured by the static model or have specific holdings which you need to be incorporated within the model. The new generation of Robo Advisory 2.0 offerings allow you to optimise a portfolio whilst both incorporating your investment preferences and any specific holdings - the investment portfolio may use a model as a ‘base’ - but the final portfolio has been optimised and tailored to the individual client circumstances. The more sophisticated offerings use concepts from the field of Artificial Intelligence, specifically Genetic Algorithms, to perform optimizations on the fly, and can build the entire efficient frontier for each client.
The key to making Robo Advisory 2.0 a success is to do the above in an automated and scalable fashion. This will then offer the client a personalised model portfolio service, yet with the cost benefits of ‘Robo’.
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