DOI•
Tuning Trend-Following Strategies with Macro ESG Data
25 Oct 2021-Vol. 2, Iss: 2, pp 117-136
TL;DR: In this paper, the authors seek to tilt traditional macro trend-following strategies toward countries with high Environmental, Social, and Governance (ESG) scores by reweighting cross-country and cross-asset momentum-based strategies.
Abstract: This article seeks to tilt traditional macro trend-following strategies toward countries with high Environmental, Social, and Governance (ESG) scores. The integration incorporates both ESG levels and changes (improvements or deteriorations in sustainability). Notably, the authors find that the international ESG exposure of the macro portfolios can be substantially increased without any cost in performance for both long-only and long–short portfolios. In some cases, transaction cost–adjusted Sharpe ratios can even benefit from a minor shift toward more ESG exposure. Key Findings ▪ Cross-country and cross-asset momentum-based strategies are reweighted to favor countries with high or improving ESG ratings. ▪ All portfolios can sustain small tilts toward sustainability without any impact on their Sharpe ratios, with up to 70% increase in ESG exposure. ▪ For long-only portfolios small tilts increase the overall Sharpe ratio, while larger tilts can become detrimental.
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01 Jan 2013TL;DR: In this paper, the authors propose to compute the implied expected returns from several candidate mean-variance efficient portfolios, exploiting the fundamental relation between the expected returns, covariance matrix and the corresponding set of mean variance efficient portfolios.
Abstract: We propose to compute the implied expected returns from several candidate mean-variance efficient portfolios, exploiting the fundamental relation between the expected returns, covariance matrix and the corresponding set of mean-variance efficient portfolios. Over the 1987-2012 period and for the universe of S&P 100 stocks, we find that a mean-variance efficient investor would have been willing to pay between a 1.7% and 4.2% management fee to switch from mean-variance investing using implied expected returns from the market capitalization weighted portfolio to mean-variance investing using the implied expected returns from the equal-risk-contribution portfolio.
10 citations
TL;DR: In this paper, the authors review the sovereign credit rating methodologies of three credit rating agencies (Moody's, S&P and Fitch) and analyze how they currently accommodate climate change risk and ESG considerations.
Abstract: We review the sovereign credit rating methodologies of three credit rating agencies (Moody’s, S&P and Fitch) and analyze how they currently accommodate climate change risk and ESG considerations. We elaborate on the differences between the three rating methodologies and critically evaluate their suitability and limitations. We propose lines of improvement with respect to the indicator selection, normalization, aggregation and weighting procedures as well as the use of the sovereign rating indicator in connection with climate change scenarios.
6 citations
TL;DR: In this article , the authors quantify equity and bond market sensitivity to sovereign ESG scores and their variations which, theoretically, is equivalent to evaluating the demand for ESG at the global scale.
Abstract: We quantify equity and bond market sensitivity to sovereign ESG scores and their variations which, theoretically, is equivalent to evaluating the demand for ESG at the global scale. We do so by estimating a longitudinal model, at the issue level, that captures exposures to sovereign ESG factors for both equity and fixed income indices. In spite of the surging interest in ESG investing, our results do not support a strong impact of ESG factors on the returns of international markets, implying that the demand for ESG at the country level is not a significant driver of prices. Nevertheless, we document a strong association between GDP growth and ESG scores at the country level.
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TL;DR: Using a sample free of survivor bias, this paper showed that common factors in stock returns and investment expenses almost completely explain persistence in equity mutual fund's mean and risk-adjusted returns.
Abstract: Using a sample free of survivor bias, I demonstrate that common factors in stock returns and investment expenses almost completely explain persistence in equity mutual funds' mean and risk-adjusted returns Hendricks, Patel and Zeckhauser's (1993) "hot hands" result is mostly driven by the one-year momentum effect of Jegadeesh and Titman (1993), but individual funds do not earn higher returns from following the momentum strategy in stocks The only significant persistence not explained is concentrated in strong underperformance by the worst-return mutual funds The results do not support the existence of skilled or informed mutual fund portfolio managers PERSISTENCE IN MUTUAL FUND performance does not reflect superior stock-picking skill Rather, common factors in stock returns and persistent differences in mutual fund expenses and transaction costs explain almost all of the predictability in mutual fund returns Only the strong, persistent underperformance by the worst-return mutual funds remains anomalous Mutual fund persistence is well documented in the finance literature, but not well explained Hendricks, Patel, and Zeckhauser (1993), Goetzmann and Ibbotson (1994), Brown and Goetzmann (1995), and Wermers (1996) find evidence of persistence in mutual fund performance over short-term horizons of one to three years, and attribute the persistence to "hot hands" or common investment strategies Grinblatt and Titman (1992), Elton, Gruber, Das, and Hlavka (1993), and Elton, Gruber, Das, and Blake (1996) document mutual fund return predictability over longer horizons of five to ten years, and attribute this to manager differential information or stock-picking talent Contrary evidence comes from Jensen (1969), who does not find that good subsequent performance follows good past performance Carhart (1992) shows that persistence in expense ratios drives much of the long-term persistence in mutual fund performance My analysis indicates that Jegadeesh and Titman's (1993) one-year momentum in stock returns accounts for Hendricks, Patel, and Zeckhauser's (1993) hot hands effect in mutual fund performance However, funds that earn higher
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Abstract: The random walk problem has a long history. In fact, its application to the movement of security prices predates the application to Brownian motion.' And now it is generally accepted that, at least to a good approximation, ln (S), where S is the price of a common stock, follows a random walk.2 The diffusion constant characterizing that walk for each stock thus becomes an important quantity to calculate. In Section II, we describe the general random walk problem and show how the diffusion constant is traditionally estimated. In Section III, we discuss another way to estimate the diffusion constant, the extreme value method. In Section IV, we compare the traditional and extreme value methods and conclude that the extreme value method is about 21/2-5 times better, depending on how you choose to measure the difference. In Section V, we discuss the use of this method for the estimation of the variance of the rate of return of a common stock. If S is the price of a common stock, it is now generally accepted that In (S) follows a random walk, at least to a very good approximation. The diffusion constant characterizing that walk, which is the same as the variance of the rate of return, thus becomes an important quantity to calculate and is traditionally estimated using closing prices only. It is shown that the use of extreme values (the high and low prices) provides a far superior estimate.
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