The impact of investor sentiment on markets has increased dramatically over the past decade, so it is now crucial for multi-asset managers to analyse market behaviour critically in order to be successful. Investors are still adjusting to a ‘new normal’ of record low or even negative interest rates, persistently low growth and inflation, increased political and policy uncertainty, and lower expected returns on savings and investments.
Contrary to the ‘irrational exuberance’ of the late 1990s, it seems that the global financial crisis in 2008-09 has installed a fair degree of dread risk in the minds of investors: an excessive focus on downside risks which in turn can create its own reality. Such risk only wears off slowly, and in the meantime risk premiums can be elevated, volatile and more susceptible to shocks than before 2008.
Financial markets have also lost some of their fundamental anchor. Massive price-insensitive, asset-buying programmes by central banks, reduced liquidity in secondary markets, increased usage of exchange-traded funds (ETFs) and derivatives and the rapid gains in speed of information processing and trading activity have added to the impact of investors’ emotions on markets.
For a multi-asset manager, next to fundamental analysis the study of market behaviour has become more important than ever before when it comes to making deliberate asset-allocation decisions. Mapping the mood of the market by finding and assessing signals to understand its behaviour allows for differentiation in positioning rather than getting lost in the noise. It is necessary to analyse the exposures of active allocation managers, such as other multi-asset, macro hedge and long-short equity funds.
In addition to current positioning, the strength of investment flows of both institutional and retail investors to various asset classes must also be assessed. As the amount of money invested in passive products increases, the study of ETF flows has grown in importance in this regard.
Next to flow and price dynamics, the analysis of observed emotions, or sentiment, of the market is very useful. This desire to measure sentiment is not new. Investor surveys have been common for many years and provide a good insight into how bullish or bearish investors say they are when asked directly.
However, digitalisation and the emergence of social media, self-teaching algorithms and the ability to process large amounts of data – practically in real time – have created an entirely new way to measure sentiment. These digital news and social media feeds can be converted into sentiment indices such as optimism, fear, joy or conflict, providing real-time insight into the sentiment that plays a role in driving markets.
The point then is to combine the model inputs with the fundamental research and insights of strategists, economists and portfolio managers to come to a coherent view on the markets. In other words, combining the best of man and machine.
One of the benefits of this approach is that it helps to protect against the known behavioural pitfalls of investors, such as the underestimation of risk and overestimation of returns, but also fear and loss aversion. The use of human judgement – which is still better able to assess the consequences of geopolitical events and central bank policy – alongside the use of data-derived models that protect against known human biases, enables the manager to make well-informed decisions that are as unbiased as possible.