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The Influence of the "Big-3" on Systematic Investment Strategies in Switzerland

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In the last OLZ Research Blog, we looked at the low-volatility anomaly in Switzerland and noted that the outperformance of this factor strategy has not diminished in recent years. Nevertheless, some defensive strategies in the Swiss equity market have recently failed to beat the SPI benchmark - despite the general market weakness. This includes our minimum variance fund OLZ Equity Switzerland Optimized ESG. The role of the "Big-3" in the SPI index, i.e., Nestlé, Roche and Novartis, is of key importance here. In this blog article, we want to examine the influence of these three mega-cap stocks on our minimum variance fund.

Heavyweights dominate the Swiss stock market

When thinking of Swiss stocks, Nestlé immediately comes to mind for many investors. With a market capitalization of more than CHF 300 billion, the world's largest food company is also a heavyweight on the international stock markets, making it into the world's 20 largest listed companies. But the numbers two and three on the Swiss stock market are not much smaller: Roche has a market capitalization of around CHF 240 billion, while Novartis has a market capitalization of around CHF 190 billion. Taken together, these three heavyweights, named "Big-3" for short, have a total capitalization of just under 50% of the SPI Index (see Figure 1). In addition, two of these stocks, Roche and Novartis, come from the pharmaceutical sector. This historically high concentration of Big-3 stocks in the SPI makes the index top-heavy and entails a significant cluster risk that many investors are unwilling or unable to take for regulatory reasons.

Figure 1: Share of Big-3 market capitalization in the SPI Index

Maximum weights reduce cluster risk

Systematic investment strategies therefore usually set a maximum weighting at the level of individual stocks that is significantly lower than the capital weighting of the Big-3 stocks in the SPI - as is the case in our OLZ Equity Switzerland Optimized ESG fund, which has a maximum weighting of 10% per stock[1].  The lower weight of the heavyweights leads accordingly to an overweighting of the remaining stocks, especially mid- and small-cap stocks. This shift towards smaller companies has a significant impact on the return and risk characteristics of the portfolio and should be taken into account in benchmark comparisons with the SPI.

The fact that the Big-3 stocks (especially Nestlé) are rather defensive stocks makes it challenging for risk-optimized investments with Big-3 underweights to achieve an additional risk reduction compared to the SPI. One might therefore ask whether this type of risk optimization in the Swiss equity market then makes sense? For one, it is important to distinguish between historical volatility and cluster risks: while volatility is reflected in the fluctuation range of individual stocks at any point in time, cluster risk is invisible most of the time and only manifests itself when one of the Big-3 stocks gets into trouble. In the past, e.g. there was a corruption scandal at Novartis, which led to an "ESG Red Flag" from MSCI and consequently to the exclusion from the investment universe based on our ESG criteria. These company-specific risks are referred to in technical jargon as unsystematic or diversifiable risk and can be avoided through better portfolio construction. While this does not mean that the portfolio return is increased at all times, a more efficient allocation in terms of the risk-return tradeoff is achieved in the long term.

Q4 2021 and Q1 2022 difficult for Swiss small and mid caps

Figure 2: Short-term performance since Q4 2021

In Q4 2021 and Q1 2022, our Swiss fund trailed the SPI index and did not provide the expected buffer in the downside. So, at first glance, one could think that risk-based portfolio optimization does not provide significant downside protection. However, this line of reasoning overlooks a key feature of this investment universe: the SPI benchmark is not in the solution space of our portfolio optimization at all, as we require significantly lower maximum weights. Thus, simplistic comparisons with the SPI are not very meaningful. Taking other benchmarks into account - such as the SMIM Index (30 mid-cap companies below the 20 stocks of the SMI) or the SPI Extra (all stocks of the SPI that are not included in the SMI) - allows for a more accurate analysis. In addition, we create the "Big-3 Index", which tracks the three heavyweights and weights them based on their historical capitalization.

As seen in Figure 2, our fund lost 3.8% over the period from October 1, 2021 to March 31, 2022, while the SPI Index gained almost 3.3%. However, over this period, SMIM lost 6.4% and SPI Extra 6.6%, while at the same time the Big 3 stocks gained a whopping 8.6%, led by Roche and Novartis (both around 10%). Against this background, the performance of our fund appears in a different light: we achieve a significant reduction in volatility and maximum loss compared to SMIM and SPI Extra, but cannot keep up with the performance of the SPI, as this is driven by the very strong performance of the Big-3. Hence, our minimum variance approach has worked within its means, but performance has been weighed down by mid- and small-cap stocks.

In Q2 2022, the difference has already narrowed somewhat: SMIM has lost 14.2% and SPI Extra 14.4%, while the SPI has lost 11.0% and the Big-3 Index 6.6%. Mega-cap stocks were thus no longer able to escape the general downward trend. In this difficult stock market environment, our fund lost only 9.8%, thus outperforming the SPI by 1.2%. Moreover, we were able to significantly reduce volatility compared to all benchmarks mentioned.

Higher return through mid- and small-cap premium

Figure 3: Long-term performance since Q3 2003. OLZ returns before Dec. 20, 2010 are a backtest simulation

So, our fund holds more mid- and small-cap companies to avoid cluster risk in the Big-3. Recently, this has not paid off. However, this is not in line with the long-term picture. It is a well-documented empirical finding that mid- and small-cap stocks deliver significantly higher returns than large-caps over the medium to long term. Figure 3 shows the performance over the long term (almost 20 years). Both the SPI Extra and the less broad SMIM index significantly outperformed the SPI and the Big-3. Like any factor premium, the low-size effect is subject to time fluctuations, which is why smaller stocks underperform in some phases, but significantly outperform higher capitalized companies in other phases. In the past, this low-size premium has contributed to the OLZ fund's outperformance over the SPI. Based on the robust data and the wide acceptance of this effect in academia and among practitioners, we see no reason to believe that this pattern should change in the future.

A convincing track record - highest risk-adjusted returns since fund inception

Higher weights in smaller stocks combined with sophisticated risk control pays off in the long run. Table 1 shows the return and risk numbers since the launch of our OLZ Equity Switzerland Optimized ESG. Our fund achieves a risk reduction compared to all benchmark indices, especially the SMIM and the Big-3. At the same time, our OLZ Equity Switzerland Optimized ESG achieved the highest risk-adjusted return in this comparison with a Sharpe Ratio of 0.63 since launch.

Table 1: Key return and risk figures since OLZ fund launch on 20.12.2010 to 30.06.2022

The OLZ Equity Switzerland fund therefore offers investors the opportunity to profit from the higher long-term returns of medium-sized and smaller companies, without having to take on a higher risk than in the SPI. Moreover, we avoid the SPI's problematic cluster risk, which lurks beneath the surface of an apparently broadly diversified market index.

New OLZ offering in the area of Swiss mid- and small-caps

In order to offer our clients an even more focused investment in Swiss mid- and small-caps with optimal risk diversification and consideration of sustainability criteria, OLZ will expand its product range by a minimum variance strategy in the SPI Extra investment universe starting in autumn 2022. More information will follow shortly.

In conclusion:

  • Compared to the SPI and other popular Swiss equity indices, OLZ Equity Switzerland Optimized ESG consistently achieves lower volatility.

  • The amount of risk reduction is smaller compared to the SPI because defensive Big-3 stocks are underweighted in optimized portfolios.

  • Compared to mid- and small-cap stocks, the minimum variance approach always significantly reduced the risk of loss.

  • Our fund benefits in its long-term performance from mid- and small-caps - with lower volatility than the SPI and significantly mitigated cluster risk.

 [1] This includes a buffer for floating of the weights between portfolio rebalancings. The actual upper weights in our optimization procedure are at 8%.

Effizientes Anlegen durch risikooptimierte Portfoliokonstruktion
OLZ Quantitative Research Patrick Walker

Dr. Patrick Walker

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