Journal of Asset Management最新文献

We investigate how changes in demand for Environment, Social and Governance (ESG) characteristics affect stock prices. We consider three scenarios: increased demand for ESG characteristics by investors, shifts in assets under management from institutions with low demand for ESG characteristics to those with high demand, and changes in the ESG characteristics of the stocks themselves. To compute the effects of the scenarios, we use a demand-based asset pricing model which is calibrated to individual stock-level holdings of institutional investors. We find that these scenarios lead to significantly different returns of stocks with different ESG characteristics.

At the beginning of factor investing research, the investment universe concentrated on developed markets and transaction costs were paid little attention. Expensive trading costs of factor investing in emerging equity markets influence optimal portfolio decisions. Based on a total costs estimate of factor-based portfolio tilts, a simple cost-mitigation approach increases net performance. Exploiting the structure of market impact, we indirectly control the costs by limiting order sizes relative to their underlying stocks’ short-term liquidity. This cost-efficient strategy yields better implementability and lower-priced turnover while a possible negative effect on gross performance is more than offset.

Core-satellite strategies are often implemented to combine the benefits of passive and active investing. Our study analyzes a particularly attractive and quasi-frictionless core-satellite approach: Adding active commodity futures momentum satellites to passive cores diversified across traditional asset classes. We show that momentum portfolios, enhanced by long-term reversal and skewness information, are highly valuable satellites. Considering them with low fixed weights, as suggested by popular strategic allocations, leads to significant improvements in investment performance and reduces portfolio sensitivities to shocks in investor fear. In contrast, using time-varying optimized weights based on satellite alphas or tail risk minimization turns out to be less advantageous. Interestingly and regardless of the considered weighting scheme, momentum satellites shine primarily by lowering portfolio risk (instead of increasing portfolio return) which supports modern interpretations of the role of active management.

Environmental, social, and governance (ESG) scores are a key tool for asset managers in designing and implementing ESG investment strategies. They, however, amalgamate a broad range of fundamentally different factors, creating ambiguity for investors as to the underlying drivers of higher or lower ESG scores. We explore the feasibility and performance of more targeted investment strategies based on specific ESG categories by deconstructing ESG scores into their granular components. We implement “best-in-class” strategies by excluding firms with the lowest category scores and reinvesting the proceeds in firms with the highest scores, maintaining the same regional and sectoral composition. These approaches reduce the portfolio’s tracking error and slightly improve its risk-adjusted performance, while still yielding large gains in targeted ESG scores.

We extend proxies of several popular asset allocation approaches—U.S. and Global 60/40, Diversified Multi-Asset, Risk Parity, Endowment, Factor-Based, and Dynamic asset allocation—using long-run return data for a variety of sub-asset classes and factors to test their long-term performance. We use equity and debt assets, commodities, alternatives, and indices to reconstruct the returns on allocation portfolios from 1926 to the present, the entire period for which comprehensive asset pricing data are available. We contribute to the existing literature by developing a laboratory for testing the performance of popular asset allocation strategies in a wide range of scenarios. We also aim to test the importance of the behavioral aspect of investment decisions for portfolio outcomes. In our framework, Factor-Based portfolios exhibit the best traditionally measured risk-adjusted returns over the long run. However, Dynamic asset allocation is most likely to reduce the risk of abandonment of the strategy by an investor and selling the portfolio in panic when they experience losses over their tolerance threshold, because the dynamic strategy exhibits lower expected drawdowns, even during severe market downturns. Across all strategies, risk-tolerant investors who rely on a longer history to set their expectations, whether based upon actual or extrapolated data, experience significantly better outcomes, particularly if their investment horizon includes times of crisis. This study informs portfolio managers, investment analysts, and advisors, as well as investors themselves, of the impact of information, persistence, and properties of various portfolio allocation methods on investment returns.

Reducing portfolio carbon footprints (Exit) and voting in favor of climate-related shareholder proposals (Voice) are among the main actions that investors can take to promote an accelerated transition toward a low-carbon economy. This paper studies three important investor groups that can be instrumental in driving the transition and evaluates their Exit and Voice behavior. I find that the five largest asset managers perform poorly on Exit and Voice over the full sample period but improved on both in more recent years. Only a small fraction of signatories to sustainable investor initiatives are supportive of the transition. Counterintuitively, investors who perform poorly on Exit, perform well on Voice. Finally, I examine the financial consequences of employing Exit and Voice and find that Exit is positively related to risk-adjusted fund returns; however, this is not necessarily attributable to superior skill of fund managers.

We investigate portfolio pumping around quarter-ends by ESG equity mutual funds domiciled in the largest European markets in sustainable investments, i.e., the UK, France and Germany, for the period from January 2010 to December 2022. We find strong evidence that the UK funds inflate quarter-end returns, with price spikes being stronger at year-ends; nevertheless, the magnitude of price inflation is less than that of their conventional counterparts. On the contrary, results indicate that German and French funds do not engage in portfolio pumping. The COVID-19 pandemic strengthened the propensity of fund managers to cause a profound artificial enhancement to the performance of the investment portfolio. Further analysis shows that portfolio pumping is more prominent among the worst-performing funds, funds that charge investors with lower fees and achieve a poor ESG rating. However, managers that pump fund returns do not attract significantly more flows. Our results have produced valuable insights for regulators and investors participating in ESG markets, highlighting the necessity for a rigorous surveillance of the UK ESG equity market.

This paper generalizes the concept of capacity from the portfolio level to the investment process for systematic equity strategies. Capacity is often understood as the maximum asset under management, above which additional inflows would have too great a negative impact on performance. The concept of capacity is often limited to the study of a given portfolio. However, setting up a capacity management framework must consider what the portfolio might look like in the future. This is obviously complicated for discretionary portfolios but theoretically conceivable for portfolios implementing systematic strategies, if we can simulate all possible scenarios. In our framework, we extend the traditional definition of capacity from a number to a random variable, allowing portfolio managers to integrate it into their risk considerations. We provide examples of how portfolio managers can approach this problem, with full-search or modelling methods. Our framework includes several capacity metrics that can be used jointly or selected to align better with the features of each strategy.

Utilities with hard coal and lignite power plants, manufacturers, and aviation companies in the EU that emit greenhouse gases must invest in emission allowances to run their operations. The buy side of the capital market (e.g. hedge funds, insurers, and pension plans) can invest in these allowances to realise an investment asset which is uncorrelated to traditional market-risk investments. Given the high volatility of the price of emission allowances, all investors in emission allowances face a challenging risk-return situation that requires a thorough risk analysis. We show that this analysis can be undertaken using extreme value theory. For the analysed extreme emission allowance price returns, we identified saliently good fits between the empirical and theoretical Pareto distributions. We further show that emission allowances present an interesting investment case.

There are significant differences in the performance of Target Date Funds (TDFs) with the same target year. Using a unique dataset from Morningstar, we show that within the same target year, funds with lower than the average expense ratio, or higher than average allocation to equities, outperform similar funds. This outperformance exists across all target year groups and is economically meaningful. Furthermore, deviations in the equity allocation have a greater impact on performance than does expense ratio. Using bootstrap simulations to investigate the impact over a longer horizon, we show that deviations from the average allocations or expense ratios have a meaningful impact on the retirement savings of an average investor.