The butterfly effect of overriding quantitative models

When walking investors through the quantitative process we adopt within our China strategies, one topic that is frequently discussed is how often we ‘override’ our models. The short answer is ‘never’, although we emphasise the need to review the models periodically to ensure that outcomes align with strategy expectations. Periods of underperformance are to be expected, although we hope that a robust investment framework underpinned by extensive research ensures such periods are occasional.

We believe that tinkering with the models in reaction to such periods of underperformance is counterproductive and a recipe for disaster. In trying to deliver a quick ‘fix’ to solve the recent past, future outcomes are invariably compromised. Nevertheless, a quantitative investment process does require evolution, and we are constantly striving to refine and enhance the models to deliver a better outcome for clients. 

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The prospect of quarterly portfolio rebalancing, as opposed to monthly rebalancing as we are currently, is an initiative we have been seeking to implement for some time now. However, the duration and frequency of the dataset became a stumbling block that could only be solved with time and patience. When we initiated the quantitative process back in July 2014, our investable China universe had only been liquid and accessible for c.10 years. We now have enough historical and live data points to give us confidence in the process going forward.

Consequently, we are pleased to report that our China strategies moved to quarterly rebalancing, effectively 1 May 2019.

Aside from less frequent turnover (four rebalancing exercises per annum versus twelve currently) and therefore a substantial reduction in aggregate trading costs, the primary consideration is our clients. Our research suggests that performance will not be negatively impacted. On the contrary, our expectation looking forward is for superior risk-adjusted returns.

Investors wishing to access our China quantitative modelling capabilities can do so through the Ashburton Chindia Equity Fund or via bespoke and segregated mandates.