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Socially responsible investing is booming and is getting popular among practitioners and academics as well. While the social aspect is indisputable, many researchers rightfully doubt that ESG cannot provide an edge in terms of performance. A good example could be an ESG level strategy that buys (and could also short) highest (lowest) ESG score stocks. The profits are small and too little compared to simple, smart beta strategies.
This novel research proves that socially responsible investing and exceptional performance can be achieved. It is possible to obtain a good performing strategy through a combination of ESG scores and price momentum. The ESG scores and momentum anomaly can be related to the famous optimization knapsack problem. One of the most straightforward explanations of the knapsack problem is a robber that has limited capacity in the backpack, and naturally, wants to return from the store with a maximal loot. Therefore, the weight of the loot is limited, and robber wants to maximize his profit by choosing the most valuable combination of items that would fit into his knapsack.
Therefore, it is possible to make classical momentum more „sustainable“ or ESG friendly. In this case, the aim is to pick stocks with the highest momentum, but at the same time, maximize the ESG score of the portfolio. In other words, the momentum represents the weight, the higher the momentum, lower the weight. The limited capacity of the knapsack ensures that only stocks with high momentum (low weight) would be included in a portfolio. The ESG score of each stock represents the value. Therefore, picking stocks with the lowest „weight“ and maximizing the „value“ creates a more ESG friendly momentum strategy. Secondly, the situation can be reversed, and ESG can represent the „weight“ of the stock – higher the ESG, lower the weight. In this case, momentum represents the „value“ of the stock. In practice, such an approach chooses portfolio with as highest ESG as possible while maximizing the momentum of the stocks.
To sum it up, the knapsack algorithm finds the best combination of stocks to achieve a momentum portfolio with high ESG scores, or high ESG scores portfolio with large momentum. As a result, the performance does not suffer; knapsack portfolios only slightly reduce the profits and outperform the classical momentum on a risk-adjusted basis. We would centre our attention around the high ESG portfolios that maximize the momentum since the performance is the most consistent and the strategy delivers the best risk-adjusted return.
Fundamental reason
There are two reasons for the functionality of the combined ESG and momentum strategies. Firstly, it is a functionality of the momentum anomaly that was repeatedly proven to be working. Secondly, ESG criteria significantly improve the risk characteristics of the portfolio. Research consistently identify high ESG stocks as less risky. Therefore, the momentum largely contributes to the return, while the ESG ensures that the portfolio would not be largely volatile and would have smaller drawdowns. Both characteristics are also supported by the Theil´s regression, where the ESG score explains the volatility or drawdown. The ESG score has a statistically and also economically significant influence on the risk measures.
Additionally, the Knapsack algorithm and the optimization ensures that both the ESG and momentum are mixed most optimally, producing momentum portfolios with high ESG or ESG portfolios with high momentum. Moreover, the Knapsack algorithm also does not try to find the portfolio with the best return, which could lead to an overfitted portfolio that would not be that profitable in the future. The knapsack algorithm instead combines two distinct effects such that the maximal benefit would be achieved in terms of social responsibility, return and risk of the portfolio.
Lastly, the complicated optimization problem which complexity raises with the number of stocks can be efficiently solved using a slightly modified simulated annealing approach proposed in the paper.
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Keywords
Market Factors
Confidence in Anomaly's Validity
Period of Rebalancing
Number of Traded Instruments
Notes to Number of Traded Instruments
Complexity Evaluation
Financial instruments
Backtest period from source paper
Indicative Performance
Notes to Indicative Performance
Estimated Volatility
Notes to Estimated Volatility
Notes to Maximum drawdown
Sharpe Ratio
Regions
Simple trading strategy
The investment universe consists of large US stocks for which OWL Analytics ESG data were provided. Firstly, consider a scaled total ESG score, that is between zero and one, and classical equity 12-months momentum signal where the last month is omitted. The knapsack problem consists of finding the combination of objects (stocks) that maximize the value, given the condition of the maximal weight. In the case of ESG-MOM strategy (a strategy that wants the highest ESG stocks with the largest momentum), the weight is represented by the reversed value (absolute value of 1 minus ESG score) to ensure that the condition of maximal weight is meaningful. Maximal weight (weight cap) is set to be a sum of the top 10% of reversed ESG scores, which ensures that only top ESG stocks should be included. The value is represented by the ranked momentum, where the higher the rank of the stock is, the higher momentum is. The combination of weight, weight cap and value creates an optimization problem represented by equation 1 in the paper. The optimization problem is solved by the simulated annealing and results in the optimized long-only portfolio consisting of high ESG, high Momentum stocks. The strategy is equally-weighted and rebalanced monthly.
Hedge for stocks during bear markets
Partially – Based on figure 1, the performance is very consistent and largely reduces drawdowns, however, the strategy could not be applicable as a complete hedge
Related picture
Source paper
Padyšák, Matúš: ESG scores and price Momentum are more than compatible
Abstract: While price momentum is a stable part of financial markets, ESG scores are emerging more and more. However, there is an ongoing debate on the social responsibility of firms and the relationship with the performance. Literature offers mixed results whether the ESG enhances the performance of a stock, does not influence performance at all or even hampers the performance. In this paper, the pure price momentum is combined with ESG scores using a knapsack algorithm. Knapsack algorithm is a well-known mathematical problem of optimization, and in the case of momentum and ESG, can be used to make the momentum portfolios significantly more responsible, with lower volatility and better risk-adjusted return. The second option is to make the ESG portfolio substantially more profitable by using Knapsack algorithm to construct high ESG portfolio with large momentum. The approach resulted in a strategy with high ESG score and compared to pure momentum or momentum-ESG strategy, with significantly reduced volatility. Therefore, the ESG-momentum strategy has the best risk-adjusted return, the lowest drawdown, the lowest volatility and the most consistent returns.
Other papers
Lars Kaiser: ESG Integration: Value, Growth and Momentum
Abstract: This study provides finer-grained results about the financial effectiveness of ESG integration when combined with mainstream active investment styles. Specifically, we demonstrate that U.S. and European value, growth and momentum investors can raise their portfolio’s sustainability performance without sacrificing financial performance. By constructing size and industry-adjusted sustainability ratings, we provide the basis for a successful ESG integration and contribute to the evidence on ESG materiality from a risk perspective. Findings add to the growing demand for sustainable products in the traditional investment industry and overcome the notion of sustainability being a burden to classical investment practices.
Varmaz, Armin and Fieberg, Christian and Poddig, Thorsten, Portfolio optimization for sustainable investments
Abstract: Investments in firms related to environment, social responsibility and corporate governance (ESG) aspects have recently grown, attracting interest from both academic research and investment fund practice. This paper develops a simple new portfolio optimization approach to include ESG in portfolio formation. In addition to technical and practical advantages over a traditional mean--variance approach that incorporates ESG preferences, our approach allows us to follow competing explanations of the relation among risk, return and ESG. An extension of our portfolio optimization approach can even help distinguish competing explanations from the literature, i.e., between the preferences of investors for ESG firm characteristics and exposure to a common ESG risk factor. The proposed portfolio optimization approach is flexible enough to include additional risk factors and/or characteristics. We demonstrate the application of our approach to empirical data.
Coqueret, Guillaume and Stiernegrip, Sascha and Morgenstern, Christian and Kelly, James and Frey-Skött, Johannes and Österberg, Björn: Boosting ESG-Based Optimization With Asset Pricing Characteristics
Abstract: This article investigates the usefulness of combining traditional factors with ESG data when building optimal equity portfolios. Our contribution departs from the traditional literature by focusing on allocations designed to adjust benchmark policies. We allow compositions to be embedded in a general factor framework in which firm characteristics are the main drivers of the portfolio weights. In line with much of the literature, our results suggest that it is feasible to improve the ESG score of a portfolio without it being detrimental to its out-of-sample performance. However, pure sustainable attributes alone do not allow to fulfil this objective: they need to be boosted by non-ESG predictors to deliver their full potential.
Larcker, David F. and Tayan, Brian and Watts, Edward: Seven Myths of ESG
Abstract: The trend to incorporate Environmental, Social, and Governance (ESG) matters into corporate boardrooms and capital markets is pervasive. Nevertheless, considerable uncertainty exists over what ESG is, how it should be implemented, and its financial and nonfinancial impacts on corporate outcomes and fund performance. In this Closer Look, we explore seven commonly accepted myths surrounding ESG, many of which are not supported by empirical evidence.We ask:• What is ESG expected to solve: short-termism by corporate managers or a deeper problem of corporations profiting at the expense of stakeholders?• Does ESG increase corporate value, or does it represent an incremental cost incurred for society?• How much ESG investment is new (incremental) investment, and how much repackaging of existing spending?• Why is governance included as the G in ESG?• Is it possible to develop a reliable measure of ESG quality?• Can standardized ESG reporting be done in an informative and cost-effective manner?