A recent study, which compared the average performance of the discretionary strategy and enhanced indexing quant strategy in China over the past three years, showed that enhanced indexing quant strategy delivered higher average return and smaller drawdown, beating the discretionary strategy’s overall performance.

Is computer better than human, therefore Quant Model superior to Portfolio Manager’s judgement? We think there were cyclical as well as tendency factors behind this phenomenon.

Although different managers investing stocks with different styles, the basic rule of stock selection is similar, that is to buy good companies at favourable valuations. Generally, the definition of a good company includes strong profitability and high growth, which are profitability factor and growth factor in quant terms. Between 2019 and 1H2021, discretionary strategy funds raised substantial capital after a period of great performance, and these capitals were in turn buying the above-mentioned good companies, which pushed up the prices, setting the backdrop for future selling pressure in the Large-Growth stocks. This is the cyclical factor.

The tendency factor is essentially the computing power of quant strategy provides a much wider coverage of the stock market versus the limited capacity of equity analysts. As China market continues to develop, the number of listed stocks increases, resulting in the declining of analyst coverage ratio. There are about 5000 listed companies in China now, and less than half of them covered by sell-side research analysts. Single asset management firm actively can follow less than 500 listed companies in most case. The whole industry is facing the challenge of declining coverage ratio as the investment universe expands. With the improving computing power and technology, quant model not only capable of full coverage of the market universe, but also strengthen the investment efficiency thanks to more data access and better data processing.   

Cyclical factor could be reversed over the time. Market style has its cycle. The large-growth style favoured by the discretionary strategy will rebound after a few years’ adjustment. There will still be opportunity for discretionary strategy to deliver performance as long as managers stick to their holdings at the market trough and waits patiently.

Tendency factor has to be dealt with by innovation and evolution. Contrast to limited investment principles discretionary strategy use, quant model can discover more hidden investment patterns via empirical test and back testing. In addition to profitability, growth, valuation factors, there are also scale, momentum, reversal, consensus, event-driven and high-frequency price volume factors etc. Discretionary managers should leverage these new methods in order to catch up with the market’s development.

Not only discretionary strategy needs innovation, so does quant strategy. The alpha generated by enhanced indexing quant strategy has been on a diminishing trend in the past three years, from 20%+ in 2021 to 10%+ in 2022 and single digit year-to-date, as quant strategy space is getting more crowded. China market always evolves at a fast pace. What works this year might be obsolete next year.

The market and era are constantly moving, but the requirement for innovative and differentiating investment method remains constant. If the investment methods are homogeneous, the investment results will be similar, hence little alpha. For both discretionary and quant strategies, innovating by learning from each other’s advantages is a valuable path to avoid crowdedness in the investment universe.

We have been exploring the quandamental investment method for the past three years. Hoping to combine discretionary strategy’s clearer logic and deeper individual stock research with quant strategy’s wider coverage, back testing and rapid iteration to keep innovating and differentiating. It has been fruitful.  

The only new equity fund we launched this year so far is the Minority Growth Fund using our proprietary quandamental method. The weak market sentiment has been a challenge to launch new fund. But we think it is the right time to start raise money for this particular strategy as we believe this innovative and differentiated approach will be able to generate alpha in this market environment. The smooth performance so far has vindicated the effectiveness of the approach. We have also been utilising this strategy for half holdings of our existing products, and may increase the weight going forward.

When the market outlook is dim and the confidence in discretionary strategy is low, we need to see the cyclicality of the market as well as the investment method evolution. Every dark cloud has a silver lining.