机器翻译，仅供参考！更多文献获取请关注公众号：量化前沿速递
获取原文请加入知识星球“量化前沿速递”
文献汇总
[1] Risky Corporate Bonds in 2021: A Bubble, or Rational Underwriting in a Low-Rate Environment?
2021年的高风险公司债券：泡沫，还是低利率环境下的理性承销？
[2] Measuring and Managing the Opportunity Cost of Downside Risk Protection
衡量和管理下行风险保护的机会成本
[3] Volatility-Dependent Skewness Preference
波动相关偏度偏好
[4] Fund Success and Assurance Frontiers
基金成功与保证前沿
[5] Should Equity Factors Be Betting on Industries?
股权因素是否应该押注于行业？
[6] The Efficient Frontier: A Note on the Curious Difference between Variance and Standard Deviation
有效前沿：关于方差和标准差之间奇异差异的注记
[7] A Tale of Two Tails: Mortality, Size, Volatility, and EPU
两条尾巴的故事：死亡率、规模、波动性和EPU
[8] Developing Practical Investment Resilience
发展实际的投资弹性
[9] Volatility Timing under Low-Volatility Strategy
低波动策略下的波动时间
[10] The Unreasonable Attractiveness of More ESG Data
更多ESG数据的不合理吸引力
[11] How Much Information Is Required to Time the Market?
市场计时需要多少信息？
[1] Risky Corporate Bonds in 2021: A Bubble, or Rational Underwriting in a Low-Rate Environment?
标题:2021年的高风险公司债券：泡沫，还是低利率环境下的理性承销？
作者:Edward I. Altman and Mike Harmon
链接:https://jpm.pm-research.com/content/48/1/7;https://doi.org/10.3905/jpm.2021.1.292
Abstract : In response to the pandemic, the Federal Reserve and US Treasury aggressively supported the corporate debt markets in 2020, both through easy monetary policy and direct participation. As the economy recovered, the Fed maintained an easy monetary policy in pursuit of more robust employment, gross domestic product growth, and inflation targets. Many observers have asserted that these policy actions and other factors have driven a bubble in risk assets, such as equities, special purpose acquisition companies, real estate, commodities, cryptocurrencies, nonfungible tokens, and risky bonds. Others believe that the valuations for at least some of these assets reflect investors’ rational incorporation of the current interest rate environment and economic outlook into their underwriting assumptions. Here, the authors analyze this question with regard to one of the riskiest classes of debt securities—the CCC-rated portion of the corporate high-yield debt market—to draw broader conclusions about the leveraged credit markets in the United States. Using historical market metrics, this portion of the market at its recent peak offered almost no excess return to compensate investors for the risk taken relative to low-risk alternatives. From this, the authors conclude that investors are underwriting significantly more optimistic outcomes than those reflected in historical averages. Although the authors believe that this segment of the market falls short of a true bubble, as they define it, they warn that current conditions pose key risks to investors and to the broader economy.
Key Finding
- The US high-yield bond market, like other asset classes in the wake of the current easy monetary environment, has reached peak levels.
- Consistent with past bubbles, investors have moved up the risk curve, disproportionately bidding up the riskiest portion of this market.
- Although this reflects excessive risk appetite on the part of investors, it falls short of a true bubble as we define it.
- That said, these conditions pose key risks to investors and to the broader economy.
Abstract:为了应对这一流行病，美联储和美国财政部在2020年通过宽松的货币政策和直接参与积极支持企业债务市场。随着经济复苏，美联储维持宽松的货币政策，以追求更强劲的就业、国内生产总值增长和通胀目标。许多观察家断言，这些政策行动和其他因素导致了风险资产的泡沫，如股票、特殊目的收购公司、房地产、大宗商品、加密货币、不可伪造代币和风险债券。其他人认为，这些资产中至少有一部分的估值反映了投资者将当前利率环境和经济前景合理地纳入其承销假设。在这里，作者就风险最高的债务证券之一——公司高收益债券市场的CCC评级部分——分析了这个问题，以得出关于美国杠杆信贷市场的更广泛结论。使用历史市场指标，这部分市场在其最近的峰值几乎没有提供超额回报来补偿投资者相对于低风险替代品所承担的风险。由此，作者得出结论，投资者承销的结果比历史平均值反映的结果要乐观得多。尽管作者认为，这部分市场还没有形成他们定义的真正泡沫，但他们警告称，目前的状况对投资者和整体经济构成了关键风险。
Key Finding
- 美国高收益债券市场与当前宽松货币环境下的其他资产类别一样，已达到峰值水平。
- 与过去的泡沫相一致，投资者的风险曲线上升，不成比例地抬高了这个市场中风险最高的部分。
- 尽管这反映了投资者过度的风险偏好，但它还没有达到我们定义的真正泡沫
- 尽管如此，这些条件对投资者和整体经济构成了关键风险。
[2] Measuring and Managing the Opportunity Cost of Downside Risk Protection
标题:衡量和管理下行风险保护的机会成本
作者:Nicole Beevers, Hannes Du Plessis, Lionel Martellini and Vincent Milhau
链接:https://jpm.pm-research.com/content/48/1/21;https://doi.org/10.3905/jpm.2021.1.301
Abstract : Portfolio insurance targets the elimination of losses in excess of a predefined threshold while allowing for access to the upside potential of an underlying risky asset. This article studies the implications of the choice of the underlying asset on the frequency and magnitude of floor breaches and on the loss of performance associated with the protection against downside risk; it considers in particular the use of a diversified portfolio of stocks as opposed to a single stock. The authors find that gap risk is more prominent when insurance is applied to a stock than to a portfolio, but it can be reduced by implementing time-invariant portfolio protection or by letting the multiplier decrease when volatility rises. However, option-based insurance with dynamic option replication has a large probability of breaching, no matter the underlying asset. Among diversified portfolios, minimum variance portfolios minimize the opportunity cost of insurance, but the ranking of diversified portfolios in terms of long-term returns does not appear to be disturbed by insurance.
Key Finding
- Floor breaches in a portfolio insurance strategy occur more frequently and larger if the risky asset of the strategy is a single stock than if it is a diversified portfolio of stocks.
- Option-based portfolio insurance with dynamic replication of the option involves large gap risk, whether the risky asset is a single stock or a diversified portfolio.
- The opportunity cost of insurance against downside risk, measured as the long-term return spread between the insured portfolio and its underlying risky asset, is minimized by taking the risky asset to be the minimum variance portfolio.
Abstract:投资组合保险的目标是消除超过预定义阈值的损失，同时允许获得潜在风险资产的上升潜力。本文研究了基础资产选择对下限违约频率和幅度以及与下行风险保护相关的绩效损失的影响；它特别考虑使用多样化的股票组合，而不是单一股票。作者发现，当保险应用于股票时，缺口风险比应用于投资组合时更为显著，但可以通过实施时不变投资组合保护或在波动性上升时让乘数降低来降低缺口风险。然而，无论标的资产是什么，基于期权的动态期权复制保险都有很大的违约概率。在多元化投资组合中，最小方差投资组合最小化了保险的机会成本，但多元化投资组合在长期回报方面的排名似乎不会受到保险的干扰。
Key Finding
- 如果投资组合保险策略中的风险资产是单一股票，则该策略中的下限违约发生的频率更高，规模也更大。
- 无论风险资产是单一股票还是多元化投资组合，动态复制期权的基于期权的投资组合保险都涉及巨大的缺口风险。
- 通过将风险资产作为最小方差投资组合，可将下行风险保险的机会成本（以被保险投资组合与其基础风险资产之间的长期收益差衡量）降至最低。
[3] Volatility-Dependent Skewness Preference
标题:波动相关偏度偏好
作者:Xiang Gao, Kees G. Koedijk and Zhan Wang
链接:https://jpm.pm-research.com/content/48/1/43;https://doi.org/10.3905/jpm.2021.1.295
Abstract : In this article, the authors propose a variance-dependent explanation for the contradiction between skewness preference and low expected return concerning lottery stocks. They emphasize an overlooked aspect of skewness as a risk measure: the return uncertainty of extreme events. They show that, during periods of low market volatility, investors dislike large-skewness securities owing to a fear of uncertain results. Thus, one observes a positive relation between skewness and expected return because the security is currently undervalued. Conversely, negative associations occur in high-volatility environments. This conditional skewness–return nexus is demonstrated to possess return predictability and can help in adjusting portfolios with profitable buying and selling decisions.
Key Finding
- The authors propose variance-dependent skewness to reconcile the skewness preference for lottery stocks with their actual low expected returns.
- They emphasize skewness as a risk measure of the return uncertainty of extreme events.
- The authors construct portfolios based on the return predictability of skewness conditional on volatility and show that these portfolios remain profitable after considering transaction costs and restrictions on short sales.
Abstract:在这篇文章中，作者提出了一个方差相关的解释偏斜偏好和低预期收益之间的矛盾彩票股票。他们强调了偏度作为风险度量的一个被忽视的方面：极端事件的回报不确定性。它们表明，在市场波动性较低的时期，投资者不喜欢大型偏斜证券，因为他们担心结果不确定。因此，我们观察到偏度和预期收益之间存在正相关关系，因为证券目前被低估了。相反，在高波动性环境中会出现负关联。这种条件偏斜-回报关系被证明具有回报的可预测性，并有助于通过有利可图的买卖决策调整投资组合。
Key Finding
- 作者提出了方差相关偏态，以协调彩票股票的偏态偏好与实际低预期收益之间的关系。
- 他们强调偏度是极端事件回报不确定性的风险度量。
- 作者基于波动性条件下偏度的收益可预测性构建了投资组合，并表明在考虑交易成本和卖空限制后，这些投资组合仍然有利可图。
[4] Fund Success and Assurance Frontiers
标题:基金成功与保证前沿
作者:Martin L. Leibowitz and Stanley Kogelman
链接:https://jpm.pm-research.com/content/48/1/59;https://doi.org/10.3905/jpm.2021.1.294
Abstract : Investment fund investment strategies and asset allocations typically are based on a multiplicity of complex (possibly competing) goals that often are incorporated in a simple return target. The challenge is to develop a portfolio whose expected return at least equals the target but has a volatility less than a disaster-avoidance risk limit. However, such a goal-matching return only provides a 50/50 chance of success. Truly important goals may require a higher probability of success, such as 60%. This article focuses on efficient portfolios and the return they can provide with a specified probability of assurance. The key step is to map the efficient frontier into an assurance frontier that plots risk-adjusted returns with a 60% success probability. This frontier typically has a peak return that is the highest available risk-adjusted return. In some cases, this peak portfolio is at the risk limit. In other cases, even with a monotonically rising efficient frontier, the peak may fall well below the maximum volatility limit.
Key Finding
- Portfolios with expected returns that just match a goal-based target may have only a 50/50 assurance of success (even after those targets have been properly revised to account for, e.g., inflation, fund expenses, and geometric effects).
- Portfolios that have the best risk-adjusted return can sometimes be found at a volatility that is well short of a fund’s maximum risk limit.
- Longer horizons generally lead to higher peak returns that can enhance prospects of success.
Abstract:投资基金的投资策略和资产配置通常基于一系列复杂（可能相互竞争）的目标，这些目标通常包含在一个简单的回报目标中。挑战在于开发一个预期回报至少等于目标的投资组合，但其波动性小于灾难避免风险限额。然而，这样的目标匹配回报只提供50/50的成功机会。真正重要的目标可能需要更高的成功概率，比如60%。本文主要关注有效的投资组合以及它们在特定的保证概率下所能提供的回报。关键步骤是将有效边界映射为保证边界，以60%的成功概率绘制风险调整回报。该前沿通常有一个峰值回报，即最高的可用风险调整回报。在某些情况下，该峰值投资组合处于风险极限。在其他情况下，即使有效前沿单调上升，峰值也可能远远低于最大波动极限。
Key Finding
- 预期回报仅与基于目标的目标相匹配的投资组合可能只有50/50的成功保证（即使在适当修改这些目标以考虑通货膨胀、基金费用和几何效应之后）。
- 具有最佳风险调整回报率的投资组合有时可以在远低于基金最大风险限额的波动率下找到。
- 更长的视野通常会带来更高的峰值回报，从而提高成功的前景。
[5] Should Equity Factors Be Betting on Industries?
标题:股权因素是否应该押注于行业？
作者:Krishna Vyas and Michael van Baren
链接:https://jpm.pm-research.com/content/48/1/73;https://doi.org/10.3905/jpm.2021.1.297
Abstract : Asset managers are increasingly incorporating equity factors that deviate from traditional academic definitions in their stock selection process. The authors show that these factors frequently exhibit strong industry biases, making it crucial to understand the interaction between factor exposure and traditional industry exposure. Industry exposure plays a major role in the risk profile of a portfolio, making unintended industry exposures costly. For an extensive set of 21 equity factors, beyond the standard academic factors, the authors examine which equity factors are rewarded for their industry allocation. This set spans the value, quality, momentum, low-volatility, and size investment styles. The authors use a global and liquid investment universe, as is commonly used by large institutional asset managers. They find that equity factors from the same investment style, most notably momentum and quality, exhibit strong differences in their returns from industry allocation. Understanding the interaction between factors and industry exposures can lead to higher return premiums and lower portfolio volatility without harming performance.
Key Finding
- Asset managers are increasingly using nontraditional equity factors to select stocks. Many of these factors have biases toward and away from certain industries.
- Some equity factors are rewarded for industry exposure
- for others, this is an unrewarded risk. We assess industry allocation efficacy for 21 equity factors.
- Industry allocation efficacy differs significantly across equity factors, even among factors associated with the same investment style.
Abstract:资产管理公司越来越多地在选股过程中纳入偏离传统学术定义的股权因素。作者指出，这些因素经常表现出强烈的行业偏见，因此理解因素暴露与传统行业暴露之间的相互作用至关重要。行业风险敞口在投资组合的风险状况中起着重要作用，使得意外的行业风险敞口代价高昂。对于一组广泛的21个公平因素，除了标准的学术因素外，作者还研究了哪些公平因素因其行业配置而获得奖励。该系列涵盖价值、质量、动量、低波动性和规模投资风格。作者使用了一个全球性和流动性投资领域，这是大型机构资产管理公司常用的方法。他们发现，来自同一投资风格的股权因素（最显著的是动量和质量）在行业配置回报方面表现出巨大差异。了解因素和行业风险之间的相互作用可以在不损害业绩的情况下提高回报溢价和降低投资组合波动性。
Key Finding
- 资产管理公司越来越多地使用非传统权益因素来选择股票。这些因素中的许多都对某些行业有偏见。
- 一些股权因素因行业敞口而获得奖励
- 对其他人来说，这是一种未回报的风险。我们评估了21个公平因素的行业配置效率。
- 行业配置效率在不同股权因素之间存在显著差异，甚至在与相同投资风格相关的因素之间也是如此。
[6] The Efficient Frontier: A Note on the Curious Difference between Variance and Standard Deviation
标题:有效前沿：关于方差和标准差之间奇异差异的注记
作者:Richard Roll
链接:https://jpm.pm-research.com/content/48/1/93;https://doi.org/10.3905/jpm.2021.1.300
Abstract : The Markowitz frontier of optimal portfolios is valid in both mean–variance space and in mean–standard deviation space. There are, however, some curious differences because lines in one space become curves in the other. This article explores and explains the curiosity.
Key Finding
- The capital allocation line is a curve in mean–variance space.
- There is a line in mean–variance space that connects the riskless rate with the tangency portfolio, but it is not a capital allocation line.
- Volatility can be either standard deviation or variance, but their efficient frontier geometry is curiously different.
Abstract:最优投资组合的Markowitz前沿在均值-方差空间和均值-标准差空间都是有效的。然而，有一些奇怪的区别，因为一个空间中的直线在另一个空间中变成曲线。本文探讨并解释了好奇心。
Key Finding
- 资本配置线是均值-方差空间中的一条曲线。
- 均值-方差空间中有一条线连接无风险利率和相切投资组合，但它不是一条资本配置线。
- 波动率可以是标准差也可以是方差，但它们的有效前沿几何结构却有着惊人的不同。
[7] A Tale of Two Tails: Mortality, Size, Volatility, and EPU
标题:两条尾巴的故事：死亡率、规模、波动性和EPU
作者:Maggie Copeland, Thomas Copeland and Zhitong Lai
链接:https://jpm.pm-research.com/content/48/1/98;https://doi.org/10.3905/jpm.2021.1.302
Abstract : The firm’s equity can be valued by focusing on two tails that involve optionality. Equity shareholders have two call options on the firm’s value: an upside potential benefit call and a downside risk protection call. An optimal capital structure can be derived from optimizing these two call options. We navigate different size and volatility portfolios by examining their mortality rate for the period between 1960 and 2019. Significantly higher unfavorable mortality rates are associated with the small-cap and high-volatility portfolios. Furthermore, the difference in unfavorable mortality rates among portfolios for size and volatility is exceptionally large. The difference in mortality rates can reach 47% for a 10-year mortality horizon. The differences are not stationary over time and can be best explained by uncertainty indexes such as EPU and vix.
Key Finding
- The shareholders of equity have two call options on the firm’s value: an upside potential benefit call and a downside risk protection call. An optimal capital structure can be derived from optimizing these two call options.
- Significantly higher unfavorable mortality rates are associated with the small-cap and high-volatility portfolios. Furthermore, the difference in unfavorable mortality rates among portfolios for size and volatility is exceptionally large. The difference in unfavorable mortality rates for size and volatility can reach 47% for a 10-year mortality horizon.
- These differences in unfavorable mortality are not stationary over time and can be best explained by uncertainty indexes such as EPU and VIX. During crises and intervals of high uncertainty in the economy, small-cap and high-volatility portfolios suffer much more relative to large-cap or low-volatility portfolios owing to the increase in the future unfavorable mortality.
Abstract:公司的权益可以通过关注涉及期权性的两条尾巴来估值。股权股东对公司价值有两种看涨期权：上行潜在收益看涨期权和下行风险保护看涨期权。优化这两个看涨期权可以得到最优的资本结构。我们通过检查1960年至2019年期间的死亡率来导航不同规模和波动性的投资组合。显著较高的不利死亡率与小盘和高波动性投资组合相关。此外，投资组合规模和波动性之间的不利死亡率差异非常大。在10年的死亡率范围内，死亡率差异可能达到47%。随着时间的推移，这些差异不是平稳的，可以用不确定性指数（如EPU和VIX）来最好地解释。
Key Finding
- 股权股东对公司价值有两种看涨期权：上行潜在收益看涨期权和下行风险保护看涨期权。优化这两个看涨期权可以得到最优的资本结构
- 显著较高的不利死亡率与小盘和高波动性投资组合相关。此外，投资组合规模和波动性之间的不利死亡率差异非常大。在10年死亡率范围内，大小和波动性的不利死亡率差异可达到47%
- 不利死亡率的这些差异并不是随时间而固定的，可以用不确定性指数（如EPU和VIX）来最好地解释。在经济高度不确定性的危机和间隔期间，由于未来不利死亡率的增加，小盘股和高波动性投资组合相对于大盘股或低波动性投资组合遭受的损失更大。
[8] Developing Practical Investment Resilience
标题:发展实际的投资弹性
作者:Jarrod Wilcox
链接:https://jpm.pm-research.com/content/48/1/115;https://doi.org/10.3905/jpm.2021.1.298
Abstract : While seeking practical tools for resilient investors, a myopic ability for single-period decisions to reflect outcomes at multiple time horizons without dynamic programming is developed. It captures tail risk and, with multiple overlapping observations compounded at different frequencies, captures time-series properties as well. These benefits rely on pairing multilevel representation of the utility probability distribution with the use of Rubinstein utility—logarithmic in investor surplus. Other tools demonstrated for practical use include top-down hierarchical cluster analysis to provide qualitative information, simplified shrinkage of observed return means (but not covariances or higher moments), and better measures of potential tail risk. The resulting asset allocation examples drawn from 28 mutual funds and exchange-traded funds vary by investor risk aversion, degree of anticipation of different regimes, and whether they consider short, longer, or multiple time horizons. For single-horizon problems, resilient methods appear most helpful to conservative investors or those who trade infrequently. In contrast, multiple time horizons appear potentially helpful to all investors.
Key Finding
- A toolset for investors seeking greater resilience against systemic risk stemming from nontraditional sources, such as pandemics, revolutionary technology, climate change, and political upheavals, is created, with an example based on the impact of poorly understood derivatives in the financial crisis of 2007–2009.
- Confronting the wavelike character of systemic disruptions with time stages that may include a sudden shock, rolling disruption, or gradual recovery as winners and losers are revealed leads to a method of making single-period allocations that reflect multiple time horizon outcomes while staying within a simple and easily implemented decision-theory framework.
- Other tools for resilient investing include top-down hierarchical cluster analysis, measures of tail risk customized by risk aversion, preserving more useful information by shrinking means but not covariances, and transparent open-source software.
Abstract:在为弹性投资者寻求实用工具的同时，开发了一种短视的能力，即单期决策能够在多个时间范围内反映结果，而无需动态规划。它捕捉尾部风险，并通过以不同频率合成的多个重叠观测，同时捕捉时间序列特性。这些好处依赖于效用概率分布的配对多级表示，以及在投资者盈余中使用鲁宾斯坦效用对数。实际使用的其他工具包括自上而下的分层聚类分析，以提供定性信息，简化观察收益平均值的收缩（但不包括协方差或更高的矩），以及更好地衡量潜在尾部风险。从28个共同基金和交易所交易基金中得出的资产配置实例因投资者的风险厌恶程度、不同制度的预期程度以及是否考虑短期、更长或多个时间跨度而不同。对于单期问题，弹性方法似乎对保守投资者或交易不频繁的投资者最有帮助。相比之下，多个时间范围似乎对所有投资者都有潜在的帮助。
Key Finding
- 建立了一套工具集，供投资者寻求更大的弹性来抵御来自非传统来源（如流行病、革命性技术、气候变化和政治动荡）的系统性风险，并以2007-2009年金融危机中鲜为人知的衍生品的影响为例。
- 面对系统性破坏的波浪式特征，其时间阶段可能包括突然冲击、滚动破坏，或者，随着赢家和输家被揭示，逐渐恢复导致了一种方法，即在保持简单且易于实施的决策理论框架的同时，进行反映多个时间范围结果的单期分配。
- 用于弹性投资的其他工具包括自上而下的层次聚类分析、通过风险规避定制的尾部风险度量、通过收缩手段（而非协方差）保存更多有用信息，以及透明的开源软件。
[9] Volatility Timing under Low-Volatility Strategy
标题:低波动策略下的波动时间
作者:Poh Ling Neo and Chyng Wen Tee
链接:https://jpm.pm-research.com/content/48/1/133;https://doi.org/10.3905/jpm.2021.1.293
Abstract : The authors show that the slope of the volatility decile portfolio’s return profile contains valuable information that can be used to time volatility under different market conditions in the United States. During good (bad) market conditions, the high- (low-) volatility portfolio produces the highest return. The authors proceed to devise a volatility timing strategy based on statistical tests on the slope of the volatility decile portfolio’s return profile. Volatility timing is achieved by being aggressive during strong growth periods and conservative during market downturns. Superior performance is obtained, with an additional return of 4.1% observed in the volatility timing strategy, resulting in a fivefold improvement on accumulated wealth, along with statistically significant improvement in the Sortini ratio and the information ratio. The authors also demonstrate that stocks in the high-volatility portfolio are more strongly correlated compared to stocks in the low-volatility portfolio. Hence, the profitability of the volatility timing strategy can be attributed to successfully holding a diversified portfolio during bear markets and holding a concentrated growth portfolio during bull markets.
Key Finding
- The return profile of the volatility decile portfolio is time-varying. Its slope contains vital information on market condition—high-volatility portfolio outperforms low-volatility portfolio during good market condition, but underperforms during bad market condition. Since market regime and asset price behaviors are persistent, the slope parameter can be used to time volatility exposure.
- Holding the low-volatility portfolio benefits from the higher risk-adjusted return during general market condition. However, when the slope parameter is positive and statistically significant, it is optimal to hold the high-volatility portfolio for the subsequent period. This will ride on the higher return of high-volatility portfolio during strong growth periods. This leads to higher return and increased volatility, but both Sortini ratio and Information ratio exhibit statistically significant improvement.
- Stocks in the low-volatility portfolio are less correlated than stocks in the high-volatility portfolio. The outperformance of the volatility timing strategy formulated in this article can be attributed to holding a concentrated growth portfolio during good market conditions, and holding a diversified portfolio during bad market conditions, thus connecting the literature on low-volatility portfolio with studies on correlation structure and diversification.
Abstract:作者指出，波动率十分位数投资组合回报曲线的斜率包含有价值的信息，可用于在美国不同市场条件下对波动率进行计时。在好（坏）的市场条件下，高（低）波动性投资组合产生最高的回报。作者基于对波动率十分位数投资组合回报曲线斜率的统计测试，继续设计波动率计时策略。通过在强劲增长期采取积极措施，在市场低迷期采取保守措施，可以实现波动时间的选择。获得了卓越的绩效，在波动率计时策略中观察到4.1%的额外回报，从而使累积财富提高了五倍，同时在统计上显著提高了Sortini比率和信息比率。作者还证明，与低波动性投资组合中的股票相比，高波动性投资组合中的股票相关性更强。因此，波动率计时策略的盈利能力可归因于在熊市期间成功持有多元化投资组合和在牛市期间持有集中增长投资组合。
Key Finding
- 波动率十分位数投资组合的回报曲线是时变的。其斜率包含市场条件的重要信息高波动率投资组合在良好市场条件下优于低波动率投资组合，但在不良市场条件下表现不佳。由于市场机制和资产价格行为是持续的，斜率参数可用于确定波动性暴露的时间。
- 在一般市场条件下，持有低波动性投资组合可从较高的风险调整回报中获益。然而，当斜率参数为正且具有统计显著性时，在后续期间持有高波动性投资组合是最佳选择。这将依赖于强劲增长期高波动性投资组合的较高回报。这导致了更高的回报和更高的波动性，但索蒂尼比率和信息比率都表现出统计上的显著改善。
- 与高波动性投资组合中的股票相比，低波动性投资组合中的股票相关性较小。本文中制定的波动性择时策略的优异表现可归因于在良好市场条件下持有集中增长投资组合，在不良市场条件下持有多元化投资组合，因此，将关于低波动率投资组合的文献与相关结构和多样化的研究联系起来。
[10] The Unreasonable Attractiveness of More ESG Data
标题:更多ESG数据的不合理吸引力
作者:Mike Chen, Robert von Behren and George Mussalli
链接:https://jpm.pm-research.com/content/48/1/147;https://doi.org/10.3905/jpm.2021.1.281
Abstract : Sustainable investing is of tremendous interest in both academia and the investment industry. However, despite the interest and the surge in assets under management (AUM) inflow, environment, social, and governance (ESG) data currently remain a fundamental challenge because they are deficient in quantity, consistency, and quality. In light of this data challenge, many investors and academics have come to rely on commercial ESG raters to assess the ESG quality of various corporations. However, the commercial ESG ratings still suffer some notable biases. This article documents one possible bias, termed quantity bias. The authors find that the amount of ESG data available for a given company is positively correlated with the commercial ESG rating of that company and the weighted average cost of its capital. The implication for investors is that they should do their homework and examine what the ESG data actually say rather than simply check the box. For corporations, it implies that they will get favorable treatment in the capital market if they publish more ESG data.
Key Finding
- The current state of ESG data is severely deficient. To get around ESG data challenges, people have come to rely on commercial ESG raters. However, commercial ESG ratings also exhibit various biases. The bias documented in this article is termed the quantity bias.
- The authors found this bias to be statistically significant
- not only does it lead to higher commercial ESG ratings, but more importantly for corporations, it leads to lower cost of funding.
- The implication of this bias is twofold. For corporations, publishing more ESG data helps the bottom line. For investors, one must carefully examine what the ESG data say about the company’s sustainability practices, rather than performing a simple box-ticking exercise.
Abstract:可持续投资在学术界和投资行业都具有巨大的兴趣。然而，尽管人们对管理下资产（AUM）流入的兴趣和激增，但环境、社会和治理（ESG）数据目前仍然是一个基本挑战，因为它们在数量、一致性和质量上都存在缺陷。鉴于这一数据挑战，许多投资者和学者开始依赖商业ESG评级机构来评估各公司的ESG质量。然而，商业ESG评级仍然存在一些明显的偏差。本文记录了一种可能的偏差，称为数量偏差。作者发现，给定公司可用的ESG数据量与该公司的商业ESG评级及其资本加权平均成本正相关。对投资者来说，这意味着他们应该做好准备，检查ESG数据实际上在说什么，而不是简单地勾选复选框。对于企业而言，这意味着如果他们发布更多ESG数据，他们将在资本市场获得优惠待遇。
Key Finding
- ESG数据的当前状态严重不足。为了应对ESG数据挑战，人们开始依赖商业ESG评级机构。然而，商业ESG评级也表现出各种偏见。本文中记录的偏差称为数量偏差。
- 作者发现这种偏差在统计学上是显著的
- 这不仅导致更高的商业ESG评级，更重要的是，对企业而言，它还导致更低的融资成本。
- 这种偏见的含义是双重的。对于企业而言，发布更多ESG数据有助于实现盈利。对于投资者来说，必须仔细检查ESG数据对公司可持续性实践的影响，而不是简单的勾选。
[11] How Much Information Is Required to Time the Market?
标题:市场计时需要多少信息？
作者:Rongju Zhang and Henry Wong
链接:https://jpm.pm-research.com/content/48/1/163;https://doi.org/10.3905/jpm.2021.1.299
Abstract : In this article, the authors present an analytical explanation for why it can be difficult to devise a successful market timing strategy. The authors derive formulas to estimate the minimum required information coefficient for a timing strategy to outperform a buy-and-hold market benchmark, both with and without an alpha target. They show that markets with high Sharpe ratios and those that have low volatility are by nature hard to time. They also show that having high market exposure in a market timing strategy is generally beneficial; however, there can be a critical point beyond which additional market exposure makes timing more difficult. The authors extend the model to cover practical considerations such as transaction costs, skewness and fat tails, and market timing with two correlated assets. Finally, they present a case study to illustrate how investors could apply their framework to choose the optimal market exposure in a market timing strategy using the S&P 500.
Key Finding
- Under a bivariate normal framework, the authors show that the expected return of a timing strategy comes in two additive parts: one part driven by timing information and the other driven by average market exposure.
- There is generally a theoretical nonzero information threshold for a timing strategy to beat a buy-and-hold benchmark. This threshold can serve as a useful guide to determine whether a timing strategy is likely to succeed, complementing historical backtests.
- Although an investor can increase timing strategy return by increasing average market exposure without having more timing information, the difficulty of beating a buy-and-hold benchmark with an alpha target increases dramatically as average market exposure becomes very high.
Abstract:在这篇文章中，作者提出了一个分析性的解释，解释了为什么很难设计出一个成功的市场时机选择策略。作者推导出了估算时间策略的最小所需信息系数的公式，以便在有或无阿尔法目标的情况下，跑赢买入并持有市场基准。它们表明，夏普比率高的市场和波动性低的市场本质上很难把握时机。他们还表明，在市场时机选择策略中拥有较高的市场敞口通常是有益的；然而，可能存在一个临界点，超过该临界点，额外的市场敞口将使时机更加困难。作者对模型进行了扩展，以涵盖交易成本、偏度和厚尾以及两种相关资产的市场时机等实际因素。最后，他们给出了一个案例研究，以说明投资者如何运用其框架，在使用标准普尔500指数的市场时机选择策略中选择最佳的市场敞口。
Key Finding
- 在一个二元正态框架下，作者证明了定时策略的预期收益由两部分组成：一部分由定时信息驱动，另一部分由平均市场敞口驱动
- 通常有一个理论上的非零信息阈值，用于计时策略，以击败买入并持有基准。该阈值可作为确定计时策略是否可能成功的有用指南，以补充历史回溯测试
- 虽然投资者可以通过增加平均市场敞口来增加时间策略回报，而不需要更多的时间信息，但随着平均市场敞口变得非常高，用alpha目标击败买入并持有基准的难度会急剧增加。 |
|
转播
