Economic and market forecasting
Accurately predicting future economic outcomes will always be challenging. However, the bigger the dataset being used, the greater the chance AI can predict likely outcomes. But whilst investors and wealth managers do seem comfortable with forecasting, we are less optimistic about the possible risks when considering markets.
JP Morgan now believes that only about 10 per cent of US equity investment is now done by traditional, discretionary traders. AI quant funds use powerful supercomputers to crunch huge amounts of data, unearth patterns and survey trading strategies across different markets in real time. They do not care why markets move, only that they do, effectively ignoring the role of the economist.
So, should you really want agnostic AI technology managing your investments?
Passive investments, such as exchange-traded funds (ETFs) and index funds, similarly ignore fundamentals. ETFs, by nature, have to buy more of equities rising in price, as they start to form a larger part of the index and less of the cheaper equities which potentially offer better value. That’s the polar opposite of the adage ‘buy low, sell high’. This creates a piling-on effect, sending rising share prices higher, which risks the possibility of a bubble. It is reasonable to assume that conversely, if there were to be a sustained market correction these equities that have been overbought could be oversold as their market share within the index starts to contract, creating excessive negative pressure and potentially disproportionate losses than many investors may have grown to expect. This can all be intensified by the speed at which trading is now done; the average holding period for a security on the New York Stock Exchange has fallen from two months in 2008 to just under 20 seconds today, according to analysis from Cumberland Advisors.
There are of course regulatory measures in place, both within the AI coding and market exchanges, to help prevent the impact of potentially harmful effects from this sort of trading. However, with the flash crashes we have seen recently, it is yet to be understood how these measures would hold up within an extended market crash.
We are still firm believers that when looking at the allocation of medium to longer-term capital, the best approach continues to be based on fundamentals. It is likely that the recent volatility that we saw in Q4 2018 will become more routine as high quantum short-term trading increases, but for managers and investors that can keep their cool through these times there is still potential for good returns based in fundamental investing.
It will be interesting to see how AI in this area will develop and whether the more traditional fundamental approach to investing can be complemented by the new price movement-centric approach of AI trading.
It is interesting to see that one of the areas where the investors surveyed were least comfortable was with the idea of AI involvement in investment advice and yet 79% felt that AI would play a significant role within this process within the next five years.
Investment advice covers a multitude of areas, but there are three key concepts that I think are worth exploring; advice for the next generation, risk management and financial planning.
Advice for the next generation
You don’t have to look far to find an article about how drastically our information consumption has changed over the last few decades. With us now more likely to turn to a digital media source, or even social media, I can definitely see AI alternatives being popular with the next generation of investors.
We have already seen the rise of robo-advice within banking, mortgages and personal insurance, and I whole heartedly believe that this will likely be the first experience of financial advice for many in the future.
However, while AI will help to make advice more accessible, care needs to be given to ensure that people are suitably educated to identify the limitations of these services and when they would be better served elsewhere.
As we have already touched on, AI provides the ability to analyse and interpret vast amounts of data which can help provide us with insights into opportunities and threats that are upon the horizon.
With all this information now so quickly available, the potential to capitalise on tactile adjustments within portfolios should improve the ability for active managers to control and therefore target the level of risk that is suitable for their client’s individual circumstances.
I currently see this being more prominent within short-term trading, where turnover of investments is higher, rather than with longer-term investment strategies. However, the potential to be able to create truly bespoke investment strategies on scale is an exciting thought and something to keep an eye on in the future.
At its core, planning centres around the ongoing assessment of your financial strategy in the context of your life goals and personal values.
It is unclear how the current AI communication techniques will be able to develop to such a degree where they can comprehend the emotional factors that influence many of the financial decisions that our clients make, as emotions by their nature are irrational. It is because of this, I would envisage this area still being heavily reliant on human to human interaction.
AI will, however, prove as a useful tool within the financial planning process. For example, one particular element that could benefit from AI automation is the utilisation of valuable allowances each tax year, from ISAs to Pensions and even the annual gift allowance.
The general indication seems to be that the digitisation of financial planning is seen as a positive trend by wealth managers and investors alike, which is echoed within the study by Temenos and Forbes Insight. Crucially, processes that can be automated with the use of AI will increase efficiency, improve quality and ultimately help reduce the costs of providing bespoke planning.
As a high-net-worth investor, your circumstances are often more complex. And, as a result, understanding the critical motivators behind your objectives remains vital. Morgan Stanley’s Jeff McMilan puts it best “The machine does a very good job of identifying opportunities. Connecting that with humans who are able to talk, reason, discern and empathise is a really powerful combination”. We are here to do just that.
Ultimately, AI is already in our lives and is something to be embraced to help identify opportunities, improve efficiencies and provide better outcomes for all. However, while exciting, caution must be exercised during these early stages to understand all of the factors that impact these fantastic machines.