Systematic Skewness Research Articles

Skewness risk and the cross-section of cryptocurrency returns

This paper investigates whether investors can achieve higher returns by holding cryptocurrencies with lower asymmetry risk. First, using a non-parametric bootstrap resampling method, we found that cryptocurrencies with larger market capitalizations exhibit more left-skewed performance, while those with smaller market capitalizations display more right-skewed performance. This finding is consistent with the results of Jiang et al. (2020) in the stock market. Second, both portfolio-level analyses and cross-sectional regressions at the cryptocurrency level reveal a negative cross-sectional relationship between asymmetry risk and future returns in the cryptocurrency market. Additionally, our findings indicate that skewness in the cryptocurrency market is driven by idiosyncratic risk rather than systematic risk. This contrasts with Langlois (2020), who found that systematic skewness risk outweighs idiosyncratic risk in the stock market. Finally, in addition to the risk-return tradeoff theory, the limits-to-arbitrage theory also provides explanatory insight into these results. Collectively, our findings underscore the significant role of asymmetry risk in determining cryptocurrency prices.

Anomalously low-mass core-He-burning star in NGC 6819 as a post-common-envelope phase product

Precise masses of red giant stars enable a robust inference of their ages, but there are cases where these age estimates are very precise but also very inaccurate. Examples are core-helium-burning (CHeB) stars that have lost more mass than predicted by standard single-star evolutionary models. Members of star clusters in the database represent a unique opportunity to identify such stars because they combine exquisite asteroseismic constraints with independent age information (members of a star cluster share a similar age and chemical composition). We focus on the single metal-rich ($Z Li-rich low-mass CHeB star KIC4937011, which is a member of the open cluster NGC 6819 (turn-off mass of $ i.e. an age of $ 2.4$ Gyr). This star has a lower mass by $ than expected for its age and metallicity, which might be explained by binary interactions or mass loss along the red giant branch (RGB). To infer formation scenarios for this object, we performed a Bayesian analysis by combining the binary stellar evolutionary framework binary\_c v2.2.3 with the dynamic nested-sampling approach contained in the dynesty v2.1.1 package. We find that this star probably is the result of a common-envelope evolution (CEE) phase during the RGB stage of the primary star in which the low-mass ($<0.71$ main-sequence companion does not survive. The mass of the primary star at the zero-age main sequence is in the range with a log-orbital period in the range days )$. During the CEE phase, $ of material is ejected from the system, and the final star reaches the CHeB stage after helium flashes as if it were a single star with a mass of $ which is what we observe today. Although the proposed scenario is consistent with photometric and spectroscopic observations, a quantitative comparison with detailed stellar evolution calculations is needed to quantify the systematic skewness of the radius, luminosity, and effective temperature distributions towards higher values than observations.

Systematic Skewness and Stock Returns

Abstract This paper revisits the relation between systematic skewness and returns, showing two main findings. First, the systematic skewness premium in individual stocks is time varying. When either skewness preference or systematic skewness is above rather than below the median, the premium is 4% higher. The combined effect of the two induces time variation in the premium of about 7%. Second, systematic skewness has significant additional explanatory power in explaining returns relative to most common characteristics, except size and momentum. These two results imply that skewness preference is an important determinant of expected returns providing a possible rationale for size and momentum. (JEL G11, G12)

Variations in the relative age effect with age and sex, and over time-Elite-level data from international soccer world cups.

The relative age effect (RAE) is a statistical bias observed across sport contexts and consists of a systematic skewness in birth date distribution within an annual-age cohort. In soccer, January 1st is the common cut-off date when categorizing players in competitions according to their chronological age, which potentially disadvantages those within the cohort who were born later in the year. Thus, relatively older soccer players in their cohort can be favored in talent identification, selection, and development. The aim of the current study was to investigate the variations in RAE in male and female international youth world-cup tournaments (U17 and U20) in the period from 1997–2019 and in international senior world-cup-tournaments from 2006–2019. A total of 20,401 soccer players participating in 47 different tournaments were analyzed. The birthdate distributions were categorized into four quartiles (January-March, Q1; April-June, Q2; July-September, Q3; October-December, Q4) and compared to a uniform distribution using Chi-square analysis with Cramer’s V (Vc) as a measure of effect size. Based on the existing data concerning RAE in elite junior and senior soccer, it was hypothesized that: (I) the RAE is present in youth soccer world cup tournaments but is stronger in male players than in female players; (II) the younger the soccer players, the stronger the RAE; and (III) the RAE in world cup soccer tournaments has strengthened over time. All these hypotheses were supported by the data; novel findings included that the effect has now entered women’s soccer, and in men’s soccer it persists into senior world cup tournaments. Thus, a strong RAE bias occurs in selection among elite soccer players competing in international world cup tournaments.

Stock price crash risk: the role of systematic skewness

This study aims to explore an important determinant of stock price crash risk in an emerging market, Thailand. Our results support an important role of systematic skewness on stock price crash risk over the period of 2000 to 2019. Coskewness is negatively associated to stock price crash risk. The findings are robust when including effects of stock liquidity, earnings management, and opaque financial report. Endogeneity is addressed by performing the two-stage least squares methodology.

Asset Pricing with Systematic Skewness: Then and Now

We reexamine the role of systematic skewness in asset pricing. We begin by replicating Harvey and Siddique (2000) for the extended period of July 1926 to December 2019. Their coskewness measure provides mixed results in pricing the cross-section of U.S. stocks, suggesting the need for less noisy measures. We explore the persistent systematic skewness (PSS) measure of Langlois (2020) and a modified measure (mPSS) that we construct by conditioning only on market data. These measures are better at capturing coskewness and appear to be priced in the data, highlighting the importance of proper measures of systematic skewness.

Stock price crash risk: the role of systematic skewness

Stock price crash risk: the role of systematic skewness

The Determinants of Conditional Skewness in REIT Returns

In this study, it is determined whether changes in a set of financial and macroeconomic state variables explain the variations in the conditional systematic, idiosyncratic, and total skewness of six aggregate Real Estate Investment Trust (REIT) indices. The findings suggest that variations in the idiosyncratic skewness of REIT indices can be explained by monthly changes in the CBOE volatility index (VIX), term spread, unemployment, and industrial production. Contemporaneous variations in the systematic skewness of aggregate REIT indices can be explained by changes in the VIX index, default spread, and private consumption. Two crisis dummy variables, defined as the technology bubble of 2000 (TCD) and the financial crisis of 2007 (FCD), are also considered. The technology bubble has a dampening effect on systematic skewness while the opposite is the case for the financial crisis dummy. Quantile regression is employed in order to determine the robustness of the results. The evidence shows that the findings are robust to various quantile specifications for the distributions of the skewness measures.

On Systematic Skewness and Stock Returns

This paper shows that the premium for systematic skewness in individual stocks is positive on average, has negative realized systematic skewness, and is time varying. When skewness preference is high rather than low, the risk premium is 4% higher. Systematic skewness also has significant explanatory power for returns when controlling for most firm characteristics except size and momentum. Size and momentum risk premia, however, do not improve the investment opportunity set of skewness investors. Taken together, these results strengthen the case for skewness preference as an important determinant of stock returns and reconcile previously documented conflicting evidence.

The representativeness of a semi-random sampling method for animal welfare assessments on mink farms

AbstractIn this study we present a semi-random sampling method developed for the sampling of mink (Neovison vison) for on-farm welfare assessments according to the WelFur-Mink system. The only information required for implementation of this method is the number of cages in use in each shed on the farm. The representativeness of samples selected with this method was evaluated in relation to the physical characteristics of the farm and the mink characteristics by simulated sampling on a farm with a complicated structure in the growth period. The selection of 10,000 samples was simulated. The trueness was, in general, high, ie the method has no systematic skewness. The precision was low for certain factors due to the high variation within sheds. The sampling in sections of six adjacent cages means that it is often not possible to select a sample which is an exact representation of the mink and their housing environment. If accepting a deviation of ± one cage section, the estimated probability of selecting a representative sample was high for most of the individual factors. However, the estimated probability of selecting a sample that is representative according to all factors was rather low. This deviation from exact representativeness ought to be evaluated in the light of the increased feasibility and repeatability offered by the method. Also, we expect that the representativeness of samples selected with this method will be higher on other less-complicated farms. We suggest that this simple method balances feasibility and representative sampling in a way that makes it useful in the WelFur-Mink system.

Measuring skewness premia

We provide a new methodology to empirically investigate the respective roles of systematic and idiosyncratic skewness in explaining expected stock returns. Using a large number of predictors, we forecast the cross-sectional ranks of systematic and idiosyncratic skewness, which are easier to predict than their actual values. Compared to other measures of ex ante systematic skewness, our forecasts create a significant spread in ex post systematic skewness. A predicted systematic skewness risk factor carries a significant and robust risk premium that ranges from 6% to 12% per year. In contrast, the role of idiosyncratic skewness in pricing stocks is less robust.

Measuring Skewness Premia

We provide a new methodology to empirically investigate the respective roles of systematic and idiosyncratic skewness in explaining expected stock returns. Using a large number of predictors, we forecast the cross-sectional ranks of systematic and idiosyncratic skewness which are easier to predict than their actual values. Compared to other measures of ex ante systematic skewness, our forecasts create a significant spread in ex post systematic skewness. A predicted systematic skewness risk factor carries a significant risk premium that ranges from 6% to 12% per year and is robust to the inclusion of downside beta, size, value, momentum, profitability, and investment factors. In contrast to systematic skewness, the role of idiosyncratic skewness in pricing stocks is less robust. Finally, we document how the determinants of systematic and idiosyncratic skewness differ.

An intertemporal CAPM with higher-order moments

We propose an intertemporal asset pricing model that incorporates both preference for higher-order moments and stochastic investment opportunities and encompasses a wide range of existing models. We provide supporting evidence from the U.S. stock market and find that, not only is systematic skewness negatively priced, an extra return premium is also required for accepting high systematic risk associated with a rise in risk aversion. Our findings suggest that considering both skewness preference and intertemporal hedging demands improves the estimated risk-return trade-off, and that cross-sectional anomalies such as value, momentum, and failure probability puzzles can be partially explained by our model.

Conditional Skewness in Asset Pricing Tests

If asset returns have systematic skewness, expected returns should include rewards for accepting this risk. We formalize this intuition with an asset pricing model which incorporates conditional skewness. Our results show that conditional skewness helps explain the cross-sectional variation of expected returns across assets and is significant even when factors based on size and book-to-market are included. Systematic skewness is economically important and commands a risk premium, on average, of 3.60 percent a year. Our results also suggest that the momentum effect is related to systematic skewness. The low expected return momentum portfolios have higher skewness than high expected return portfolios.

Portfolio selection with a systematic skewness constraint

This paper investigates portfolio selection within a mean-variance-systematic skewness framework. We derive the composition of efficient portfolios in our model, and analyze the properties of these efficient portfolios. We show that the required systematic skewness is achieved at the expense of traditional mean-variance efficiency, and that a more stringent systematic skewness constraint induces a greater loss in mean-variance efficiency. Our numerical analysis demonstrates that the presence of the systematic skewness constraint helps improve the skewness of efficient portfolios in our model over the skewness of traditional efficient portfolios.

The Intervaling Effect on Higher-Order Co-Moments

This paper investigates the sensitivity of higher-order co-moments for different return measurement intervals. The levels of systematic skewness and kurtosis are found to be significantly influenced by the length of return interval. An asset preferred because of its positive co-skewness and low co-kurtosis when measured in one particular interval may have negative co-skewness or high co-kurtosis for another interval. We find the intervaling effect varies according to the level of price adjustment delay as proxied by market capitalization and illiquidity. Findings persist for intervals of up to twelve months, and are consistent during both volatile and stable periods.

Higher moments and beta asymmetry: evidence from Australia

AbstractWe examine whether systematic higher moments capture beta asymmetry in an asset pricing model whereby the conditional beta of a risky asset increases (decreases) during a bear (bull) market state. We first provide a simple conceptual outline from the microeconomic literature to show that beta asymmetry is driven by time‐varying higher‐order risk preferences (prudence and temperance) across different market states. We then empirically relate these higher‐order risk preferences to systematic skewness and systematic kurtosis. We find that beta asymmetry in Australian stock returns cannot be explained by Carhart (1997) 4‐factor model but is subsumed by systematic higher moments.

Portfolio Selection with a Systematic Skewness Constraint

This paper focuses on portfolio selection with a systematic skewness constraint within the mean-variance framework. We derive the composition of efficient portfolios in our model, and analyze the properties of these efficient portfolios. We show that the required systematic skewness is achieved at the expense of mean-variance efficiency, and find that the more stringent the constraint, the greater the loss in efficiency. Our numerical analysis indicates that the systematic skewness constraint helps enhance the skewness of efficient portfolios over the skewness of traditional efficient portfolios. In addition, investors with a greater skewness preference impose a more stringent coskewness constraint, and at the same time are willing to accept a higher risk. Finally, we establish the relationship between our model and the three-moment asset pricing model, and analyze the determinants of market prices of systematic variance and skewness implied by our model.

Interpreting a client satisfaction survey on shared agency in plan-based practice at the welfare office

Client satisfaction surveys are criticized for their tendency to generate positive feedback. This is probably due to the prevailing practice of interpreting the results in a routine manner. In this article I compare distance-oriented and method-conscious interpretation. I favour method-conscious interpretation, which utilizes accrued knowledge of the systematic skewness of information collected through a client satisfaction survey. It also pays attention to the way in which the studied phenomenon's special features, situation, and context affect the results. The operationalization of this survey has been guided by the ideal of shared agency in plan-based practice. The concept of plan-based practice refers to goal- and change-oriented, structured, and phased practice. Shared agency emphasizes dialogical, collaborative, and joint agency between the client and the worker in a helping process. When combined, these ideals lead to joint and systematic action by the client and worker. The combination of plan-based practice and shared agency emphasizes the presence of the client's views and actions in the process of getting help. The ideal holds that the client and worker share the assessment, goal-setting, and choice of working methods associated with a change-oriented working mode. I demonstrate that even if client feedback seems to indicate satisfaction, a method-conscious interpretation provides a more viable way to apply the results to organizing services. The study's data includes client satisfaction feedback (3036 instances) received by welfare offices in Lapland. The client feedback is in the form of experiential self-evaluation of received services immediately after the service events.

Dynamic Trading Strategies of Equity Hedge Funds: Empirical Evidence on How They Adapt to Market Conditions

Hedge funds shift investment strategies in response to changing market conditions. We adjust hedge fund returns for their risks in an estimation that accounts for regime-switching effects. Index factors are used to capture the returns from buy-and-hold strategies followed by hedge fund. Besides, in order to capture the nonlinear dependence of hedge fund returns on these market indexes, we construct investable higher-moment factors and option-like strategies. Because our trading factors are mostly based on the equity markets, we focus on the equity-oriented hedge funds from the Hedge Fund Research database. Especially, we test whether these factors can explain the time series behavior of returns of a market neutral, short selling and long/short equity hedge funds. Average exposure sensitivities for systematic skewness are statistically significant for all funds. Equity hedge funds are moreover shown to follow a conservative investment strategy as they reduce their (linear or nonlinear) exposures in down-market regime relative to tranquil- or up-market regimes.