Equity Factors Research Articles

Different in Nature, Common in Style: View Commonality of Single Hedge Funds and Funds of Hedge Funds

Using style analysis, the authors show the common factor exposures of single hedge funds and funds of hedge funds (FoHFs). Despite the different nature and characteristics of the two categories, there are significant style similarities through the different business cycles. The authors argue that in general, FoHFs use substantially more leverage than single hedge fund strategies and found a positive trade-off between leverage and style exposure for the former and a negative one for the latter. Furthermore, the style in both category changes according to the business cycle, with single hedge fund strategies having more flexibility in allocation and aggressive style drifts. However, the similarities in style exposure increase in times of financial turmoil. Additionally, the exposure in equity and bond-related factors are significant and identify style drifts from the past. Finally, the authors found that both categories engage most in equity markets related factors—Betting Against Beta factors (BAB), High minus Low (HML) portfolios sorted by book-to-market to indicate value, Small minus Big (SMB) portfolios sorted by market-cap to indicate size, and Conservative minus Aggressive (CMA) portfolios. <b>TOPICS:</b>Real assets/alternative investments/private equity, portfolio construction, factor-based models, performance measurement <b>Key Findings</b> • In spite of their different natures, single funds and FoHFs show striking style similarity with significant exposure to the equity markets. Their style is largely determined by dynamically shifting between long and short exposure to the factors HML, SMB, and BAB. • FoHFs have much stronger absolute factor exposure, which is partly determined by the large amounts of leverage used. • The similar style exposure spikes in times of financial stress. However, single strategies show larger advantages in exploiting business cycles, flexible factor allocation, and excess returns.

Long-term reversals in the corporate bond market

Long-term reversals in corporate bonds are economically and statistically significant in a comprehensive sample spanning the period 1977 to 2017. Such reversals are stronger for bonds with high credit risk and more binding regulatory, capital, and funding liquidity constraints. Bond long-term reversal is not a manifestation of the equity counterpart and is mainly driven by long-term losers. A long-term reversal factor carries a sizable premium and is not explained by long-established equity and bond market factors. Thus, past returns capture investors’ ex-ante risk assessment and the degree of institutional constraints they face, so losing bonds command higher expected returns.

‘Most at risk’ for COVID19? The imperative to expand the definition from biological to social factors for equity

First recognized in December 2019, the Coronavirus Disease 2019 (COVID19) was declared a global pandemic by the World Health Organization on March 11, 2020. To date, the most utilized definition of ‘most at risk’ for COVID19 morbidity and mortality has focused on biological susceptibility to the virus. This paper argues that this dominant biomedical definition has neglected the ‘fundamental social causes’ of disease, constraining the effectiveness of prevention and mitigation measures; and exacerbating COVID19 morbidity and mortality for population groups living in marginalizing circumstances. It is clear - even at this early stage of the pandemic - that inequitable social conditions lead to both more infections and worse outcomes. Expanding the definition of ‘most at risk’ to include social factors is critical to implementing equitable interventions and saving lives. Prioritizing populations with social conditions is necessary for more effective control of the epidemic in its next phase; and should become standard in the planning for, and prevention and mitigation of all health conditions. Reversing disparities and health inequities is only possible through an expansion of our ‘most-at-risk’ definition to also include social factors.

How personalized advertising affects equity of brands advertised on Facebook? A mediation mechanism

This research proposes and tests a conceptual model to address how perceived personalization of a brand’s ad seen on Facebook enhances consumer perception about the brand and subsequent favorable behaviors. Results from two studies indicate that perceived personalization is an antecedent factor of stronger brand equity. Specifically, this research reveals that perceived personalization positively influences consumer brand identification (CBI) and self–brand connection, which in turn enhances brand equity and brand usage intention (BUI). Furthermore, it demonstrates the effect of perceived personalization by both measuring and manipulating this construct.

The Case for Factor Investing in China A Shares

The Chinese A share market has recently attracted great interest from global investors because of its size and increased importance to the global financial market. The A share market has unique market characteristics and a regulatory environment that make it challenging for institutional investors. The article examines the efficacies of factor strategies by applying well-known equity factors in China A. It demonstrates that traditional factor strategies, with proper design, can deliver attractive risk adjusted return relative to the cap-weighted benchmark. From the authors’ review of the past literature along with their empirical study, they find that some characteristics of the Chinese stock market influence factor performance and factor strategy design. Notably, the traditional price momentum factor did not work in China A. Instead, a sentiment factor based on return reversal and analyst information can better capture local investors’ behavioral patterns. In addition to carrying out their empirical study, the authors look into a large body of academic research for economic and behavioral explanations of factor anomalies. Their findings provide strong support for factor-based investment strategies in Chinese A shares. TOPICS:Analysis of individual factors/risk premia, factor-based models, style investing, emerging markets Key Findings • The China A stock market has unique characteristics and a regulatory environment that influence factor performance and factor strategy design. • The authors review the academic research on factor investing, discuss the economic and behavioral fundamentals, and show evidence of the factor anomalies in the China A shares. They show that size, value, low vol, and quality factors can deliver attractive excess returns over the cap-weighted benchmark. • The study also finds that the traditional momentum factor failed to deliver positive excess return in the testing period. A sentiment factor is shown to robustly deliver excess returns and may more accurately capture the behavioral patterns that are unique to local market investors.

Geographic, Equity and Referral Factors in Intensive Care Unit Admissions and Outcomes in Hanoi, Vietnam

Geographic, Equity and Referral Factors in Intensive Care Unit Admissions and Outcomes in Hanoi, Vietnam

The Impact of Korean Professional Volleyball Teams Brand Personality on City Brand

Purpose: The purpose of this study is to provide fundamental information for professional sports and economy activation of cities, to explore mutual cooperative constructive relationship, and to investigate the Impact of Korean professional volleyball teams brand personality on city brand equity. Research design, data, and methodology: The study collected 500 survey responses and analyzed 478 surveys except for 22 which did not complete all items. For analyzing data, frequency, reliability, exploratory factor analysis, t-test, One-Way ANOVA, correlation, Multiple Regression were computed. Results: First, in difference in brand personality and city brand equity, due to gender, age, region of fan, significant difference were shown statistically in team image by gender, in honesty, interest and obdurability of brand personality by age, and in local community contribution, development possibility and sports facility of team image. Also, all factors show significant difference in region of fan. Second, regarding the impact of brand personality on city brand equity, honesty and capacity were shown to affect every factor of city brand equity, interest affected city image, and obdurability affected city perception. Conclusion: Professional teams need to develop win-win relationship with local community and seek to build positve image towards community fans via distinctive strategies for positioning.

Patient and healthcare provider reported barriers and enablers to virtual or remote-only follow-up models for cardiovascular implantable electronic devices: protocol for a qualitative framework synthesis

BackgroundVirtual care models are used to follow-up patients with cardiovascular implantable electronic devices (CIED), including pacemakers, implantable cardioverter defibrillators, and cardiac resynchronization therapy. There is increasing interest in the expansion of virtual, or even remote-only, CIED care models to alleviate resource and economic burden to both patients and specialty device clinics and to maintain or improve equity and access to high-quality cardiovascular care. This qualitative framework synthesis aims to identify barriers and enablers to virtual care models from both the perspective of the patient and device clinics. How setting, context, equity factors or other aspects influence these factors, or satisfaction with care, will also be investigated.MethodsWe will perform a systematic literature search in MEDLINE, Embase, PsycINFO, CINAHL, Proquest Dissertations & Theses, other EBM Reviews, and trial registry databases. Screening will be completed by two independent review authors. Original research articles having a qualitative component (i.e., qualitative, mixed-, or multi-method) are eligible. Study populations of interest are (a) individuals with a CIED or (b) healthcare providers involved in any aspect of virtual or remote follow-up of patients with CIEDs. Eligibility will be restricted to studies published after January 1, 2000 in English or French. Data will be captured using standardized templates based on the domains and constructs of the Theoretical Domains Framework and the Warwick Patient Experiences Framework. The Joanna Briggs Institute Critical Appraisal Checklist for Qualitative Research will be applied to all included studies. The GRADE-CERQual approach will be applied to assess and summarize confidence in key findings. Reporting will follow the enhancing transparency in reporting the synthesis of qualitative research (ENTREQ) statement. Detailed descriptive results will be presented, and summary of qualitative findings tables will be produced.DiscussionWhile a number of trials have captured the clinical effectiveness and safety of virtual follow-up for CIEDs, there has been less attention given to factors affecting use and implementation of remote care by patients and healthcare providers or satisfaction with care. Results from this qualitative framework synthesis will provide important lived experience data from both patients and healthcare providers which will be essential to incorporate in clinical guidelines.Systematic review registrationPROSPERO CRD42020160533.

Stock Picking with Machine Learning

We combine insights from machine learning and finance research to build machine learn-ing algorithms for stock selection. Our study builds on weekly data for the historical constitu-ents of the S&P 500 over the period from January 1999 to March 2021 and includes typical equity factors as well as additional fundamental data, technical indicators, and historical re-turns. Deep neural networks (DNN), long short-term neural networks (LSTM), random forest, gradient boosting, and regularized logistic Regression models are trained on stock characteris-tics to predict whether a specific stock outperforms the market over the subsequent week. We analyze a trading strategy that picks stocks with the highest probability predictions to outper-form the market. Our empirical results show a substantial and significant outperformance of machine learning based stock selection models compared to a simple equally weighted bench-mark. Moreover, we find non-linear machine learning models such as neural networks and tree-based models to outperform more simple regularized logistic regression approaches. The re-sults are robust when applied to the STOXX Europe 600 as alternative asset universe. However, all analyzed machine learning strategies demonstrate a substantial portfolio turnover and trans-action costs have to be marginal to capitalize on the strategies.

One Vol to Rule Them All: Common Volatility Dynamics in Factor Returns

We show that a common component governs volatility dynamics across a wide range of traded equity factors. This `common factor volatility' (CFV) exists even among orthogonal factors. CFV occurs in both cash-flow and discount-rate components of factor returns and derives from market responses to fundamental news rather than underlying commonality in news volatility. Incorporating CFV improves factor volatility forecasts relative to models that include only own-factor volatility. The pervasiveness of CFV helps characterize the dynamics of stochastic discount factor (SDF) volatility. CFV results in conditional SDFs that exhibit procyclical volatility, highlighting an inconsistency between traded factors and prominent macro models.

Digital Health Equity and COVID-19: The Innovation Curve Cannot Reinforce the Social Gradient of Health.

Digital health innovations have been rapidly implemented and scaled to provide solutions to health delivery challenges posed by the coronavirus disease (COVID-19) pandemic. This has provided people with ongoing access to vital health services while minimizing their potential exposure to infection and allowing them to maintain social distancing. However, these solutions may have unintended consequences for health equity. Poverty, lack of access to digital health, poor engagement with digital health for some communities, and barriers to digital health literacy are some factors that can contribute to poor health outcomes. We present the Digital Health Equity Framework, which can be used to consider health equity factors. Along with person-centered care, digital health equity should be incorporated into health provider training and should be championed at the individual, institutional, and social levels. Important future directions will be to develop measurement-based approaches to digital health equity and to use these findings to further validate and refine this model.

Physical distancing, face masks, and eye protection to prevent person-to-person transmission of SARS-CoV-2 and COVID-19: a systematic review and meta-analysis

SummaryBackgroundSevere acute respiratory syndrome coronavirus 2 (SARS-CoV-2) causes COVID-19 and is spread person-to-person through close contact. We aimed to investigate the effects of physical distance, face masks, and eye protection on virus transmission in health-care and non-health-care (eg, community) settings.MethodsWe did a systematic review and meta-analysis to investigate the optimum distance for avoiding person-to-person virus transmission and to assess the use of face masks and eye protection to prevent transmission of viruses. We obtained data for SARS-CoV-2 and the betacoronaviruses that cause severe acute respiratory syndrome, and Middle East respiratory syndrome from 21 standard WHO-specific and COVID-19-specific sources. We searched these data sources from database inception to May 3, 2020, with no restriction by language, for comparative studies and for contextual factors of acceptability, feasibility, resource use, and equity. We screened records, extracted data, and assessed risk of bias in duplicate. We did frequentist and Bayesian meta-analyses and random-effects meta-regressions. We rated the certainty of evidence according to Cochrane methods and the GRADE approach. This study is registered with PROSPERO, CRD42020177047.FindingsOur search identified 172 observational studies across 16 countries and six continents, with no randomised controlled trials and 44 relevant comparative studies in health-care and non-health-care settings (n=25 697 patients). Transmission of viruses was lower with physical distancing of 1 m or more, compared with a distance of less than 1 m (n=10 736, pooled adjusted odds ratio [aOR] 0·18, 95% CI 0·09 to 0·38; risk difference [RD] −10·2%, 95% CI −11·5 to −7·5; moderate certainty); protection was increased as distance was lengthened (change in relative risk [RR] 2·02 per m; pinteraction=0·041; moderate certainty). Face mask use could result in a large reduction in risk of infection (n=2647; aOR 0·15, 95% CI 0·07 to 0·34, RD −14·3%, −15·9 to −10·7; low certainty), with stronger associations with N95 or similar respirators compared with disposable surgical masks or similar (eg, reusable 12–16-layer cotton masks; pinteraction=0·090; posterior probability >95%, low certainty). Eye protection also was associated with less infection (n=3713; aOR 0·22, 95% CI 0·12 to 0·39, RD −10·6%, 95% CI −12·5 to −7·7; low certainty). Unadjusted studies and subgroup and sensitivity analyses showed similar findings.InterpretationThe findings of this systematic review and meta-analysis support physical distancing of 1 m or more and provide quantitative estimates for models and contact tracing to inform policy. Optimum use of face masks, respirators, and eye protection in public and health-care settings should be informed by these findings and contextual factors. Robust randomised trials are needed to better inform the evidence for these interventions, but this systematic appraisal of currently best available evidence might inform interim guidance.FundingWorld Health Organization.

Constructing Daily Equity Momentum Portfolios Using Corporate Bond Data

Do corporate bond return dynamics contain information that is not already fully reflected in equity prices despite the lower liquidity of credit markets? Using a comprehensive dataset of US corporate bond pricing and analytics, the authors show that daily bond returns can be used to construct a high-frequency equity momentum strategy. A long–short portfolio formed by ranking stocks on past daily excess returns of bonds issued by the same firms generated annual returns of 18% on average since 2001 with an information ratio of over 1.8. The performance was consistent over time and across economic states and different geographies and remained significant after controlling for commonly used equity factors. Momentum and mean-reversion strategies applied to the same universe of companies but instead using daily equity data did not generate similar results. TOPICS:Portfolio theory, portfolio construction, equity portfolio management Key Findings • Daily corporate bond pricing data can be used in constructing a high-frequency equity momentum strategy. • A daily trading strategy that buys stocks whose bonds outperformed relative to peers and shorts stocks whose bonds underperformed relative to peers generates an improved risk–return profile compared with a similar trend strategy based on daily equity price dynamics. • The strategy is attractive both in isolation and in combination with other strategies, delivering significant risk-adjusted alpha.

Portfolio Construction Matters

The role of portfolio construction in the implementation of equity market neutral factors is often underestimated. Taking the classical momentum strategy as an example, the authors show that one can significantly improve the main strategy’s features by properly taking care of this key step. More precisely, an optimized portfolio construction algorithm allows one to significantly improve the Sharpe ratio, reduce sector exposures and volatility fluctuations, and mitigate the strategy’s skewness and tail correlation with the market. These results are supported by long-term, worldwide simulations and are shown to be universal. The authors’ findings are also general and hold true for a number of other equity factors. Finally, the authors discuss the details of a more realistic setup in which they also deal with transaction costs. TOPICS:Portfolio management/multi-asset allocation, portfolio theory, portfolio construction Key Findings • Portfolio construction plays a key role in the implementation of equity market neutral strategies. • The Markowitz solution, when the correlation cleaning is correctly taken care of, leads to better results for the most well-known equity factors. • The Markowitz approach furthermore allows for a generalization of the optimization problem, which takes these costs into account.

Expected Investment Premium in China Capital Market

Through a measurement of corporate investment plan, i.e. expected investment cash flow growth (EICFG), which combines historical equity issuance and factors that influence firm’s future investment, this paper studies the impact of investment expectation on firm’s cross-sectional return of stock in China capital market. I document the negative correlation between EICFG and future stock return in A-share market, and find out that stocks of firms with higher growth of investment cash flow performs significantly worse than those with lower growth of investment cash flow in one year. Our long-short EICFG portfolio generates a statistically and economically significant return which cannot be captured by leading factor models. I further disentangle the covariation between EICFG and expected stock return from rational and behavioral perspective. This paper also extends the research of investment premium to investment-based asset pricing model.

The Effect of Team Equity Factors on Sports Fan Evangelism by Ethical Management of Professional Sports Team

The Effect of Team Equity Factors on Sports Fan Evangelism by Ethical Management of Professional Sports Team

Customers’ motivation to engage with luxury brands on social media

Customers engaging with brands on social media is critical to social media managers; however, there is still a lack of in-depth studies on the drivers of consumers’ engagement with luxury brands. Drawing on 25 semi-structured interviews with customers following luxury brands in social media, this study explores what motivates customers to engage with luxury brands on social media. This research develops a theoretical framework for the motivations of customers’ cognitive, emotional and behavioral engagement with luxury brands. The study identifies 13 motivations grouped into six macro-dimensions: perceived content relevancy (brand news, post quality, and celebrity endorsement), brand-customer relationship (brand love, and brand ethereality), hedonic (entertainment), aesthetic (design appeal), socio-psychological (actual self-congruency, status signaling, and enhance and maintain face), brand equity (perceived brand quality), and technology factors (ease of use and convenience). This study helps marketing managers of luxury brands to understand how they can improve engagement with their customers.

Equity Factors: To Short Or Not To Short, That Is The Question

What is the best market-neutral implementation of classical Equity Factors? Should one use the specific predictability of the short-leg to build a zero beta Long-Short portfolio, in spite of the specific costs associated to shorting, or is it preferable to ban the shorts and hedge the long-leg with -- say -- an index future? We revisit this question by focusing on the relative predictability of the two legs, the issue of diversification, and various sources of costs. Our conclusion is that, using the same Factors, a Long-Short implementation leads to superior risk-adjusted returns than its Hedged Long-Only counterpart, at least when Assets Under Management are not too large.

Is Bankruptcy Risk a Systematic Risk? Evidence from Pakistan Stock Exchange

This study empirically investigates the relationship between default risk and cross-section of stock returns in the Pakistan Stock Exchange (PSX). Stock price data from all listed and delisted companies use to calculate monthly returns from 2001-2016. Ohlson's O-score is employed to measure exposure of firm to systematic deviation within bankruptcy risk. Besides, asset-pricing models like the Capital Asset Pricing Model (CAPM) and Fama French (FF) models are employed. Portfolios are sorted in deciles by default probability. This result finds that stocks of firms significantly exposed to not diversified Default Risk yield higher returns. Besides that, the FF models explain cross-sectional stock returns since factors incorporate information on financial distress and default. After that, the book-to-market equity factor is not significant in elucidating returns of distressed firms because of market inefficiency. Results have practical implications for portfolio managers and investors of an emerging economy in developing diversified portfolios during periods of uncertainty and market volatility.JEL Classifications: G12, G15, G33How to Cite:Chhapra, I. U., Zehra, I., Kashif, M., &amp; Rehan, R. (2020). Is Bankruptcy Risk a Systematic Risk? Evidence from Pakistan Stock Exchange. Etikonomi: Jurnal Ekonomi, 19(1), 51 – 62. https://doi.org/10.15408/etk.v19i1.11248.

Does Factor Investing Improve Investor Welfare? A Multi-Asset Perspective

Investment decisions in delegated money management are typically made in two stages. In the first stage, a centralized decision maker allocates capital to the different asset classes. In the second stage, asset managers decide how to allocate available wealth to the individual securities within the corresponding asset class. Although commonly used in investment practice, this approach potentially involves a loss of efficiency compared with a single-step optimization procedure. The authors show that this welfare loss is zero if, and only if, the benchmarks completely explain the cross section of expected returns of the securities. This theoretical proposition justifies factor investing as an investment method that constructs investable proxies for pricing factors. Mean-variance spanning tests confirm that investment opportunities offered by standard equity, bond, and commodity factor benchmarks are not spanned by corresponding broad asset class benchmarks. The authors then conduct out-of-sample tests with these factors and find that they improve the risk-return profile of multiclass portfolios with respect to the case in which these portfolios are invested in broad asset class benchmarks. TOPICS:Wealth management, factor-based models, portfolio theory, portfolio construction Key Findings • A set of benchmark portfolios made of individual securities offers the same investment opportunities as these securities if, and only if, their returns are asset pricing factors, meaning that they collectively explain differences in expected returns. • Mean–variance spanning tests lead the authors to reject the hypothesis that traditional broad equity, bond, and commodity asset class benchmarks generate the same efficient frontier as factor benchmarks drawn from these three classes. • Out of sample, introducing factor benchmarks in multi-asset portfolios that contain traditional asset class benchmarks improves their Sharpe ratio.