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Risk.net
A growing field of mathematical research could help us understand correlation fluctuations, says quant expert
Harry Markowitz famously quipped that diversification is the only free lunch in investing. What he did not say is that this is only true if correlations are known and stable over time.
Markowitz’s optimal portfolio offers the best risk-reward trade-off – for a given set of predictors – but requires the covariance matrix of a potentially large pool of assets to be known and representative of future realised correlations.
The empirical determination of large covariance matrices is, however, fraught with difficulties and biases. But the vibrant field of random matrix theory (RMT) has provided original solutions to this big data problem – and has droves of possible applications in econometrics, machine learning and for other large dimensional models.
12:12 EDT, 24 December 2020
For portfolio managers and investors alike, 2020 is likely to have been as turbulent a year as most in the asset management world have ever experienced.
Whilst the effects of the COVID-19 pandemic have been felt ubiquitously across global markets, income-seekers have suffered particularly severely as a consequence of recent corporate dividend-cutting and suspensions, with non-financial considerations widely impacting dividend decisions, which have served only to accentuate an already challenging climate of record-low interest rates and collapsing government bond yields.
This unique investing environment has mandated a large degree of fresh thinking and, inevitably, UK investors – seeing their traditional sources of income, such as bank deposits and gilts, undermined – have sought alternatives in equity income funds.