Are Idiosyncratic Skewness and Idiosyncratic Kurtosis Priced?

This thesis investigates the pricing effects of idiosyncratic moments. We document that idiosyncratic moments, namely idiosyncratic skewness and idiosyncratic kurtosis vary over time. If a factor/characteristic is priced, it must show minimum variation to be correlated with stock returns. Moreover, we can identify two structural breaks in the time series of idiosyncratic kurtosis. Using a sample of US stocks traded on NYSE, AMEX and NASDAQ markets from January 1970 to December 2013, we run Fama-MacBeth test at the individual stock level. We document a negative and significant pricing effect of idiosyncratic skewness, consistent with the finding of Boyer et al. (2010). We also report that neither idiosyncratic volatility nor idiosyncratic kurtosis are consistently priced. We run robustness tests using different model specifications and period sub-samples. Our results are robust to the different factors and characteristics usually included in the Fama-MacBeth pricing tests. We also split first our sample using endogenously determined structural breaks. Second, we divide our sample into three equal sub-periods. The results are consistent with our main findings suggesting that expected returns of individual stocks are explained by idiosyncratic skewness. Both idiosyncratic volatility and idiosyncratic kurtosis are irrelevant to asset prices at the individual stock level. As an alternative method, we run Fama-MacBeth tests at the portfolio level. We find that idiosyncratic skewness is not significantly related to returns on idiosyncratic skewness-sorted portfolios. However, it is significant when tested against idiosyncratic kurtosis sorted portfolios.

Are Idiosyncratic Skewness and Idiosyncratic Kurtosis Priced?

This thesis investigates the pricing effects of idiosyncratic moments. We document that idiosyncratic moments, namely idiosyncratic skewness and idiosyncratic kurtosis vary over time. If a factor/characteristic is priced, it must show minimum variation to be correlated with stock returns. Moreover, we can identify two structural breaks in the time series of idiosyncratic kurtosis. Using a sample of US stocks traded on NYSE, AMEX and NASDAQ markets from January 1970 to December 2013, we run Fama-MacBeth test at the individual stock level. We document a negative and significant pricing effect of idiosyncratic skewness, consistent with the finding of Boyer et al. (2010). We also report that neither idiosyncratic volatility nor idiosyncratic kurtosis are consistently priced. We run robustness tests using different model specifications and period sub-samples. Our results are robust to the different factors and characteristics usually included in the Fama-MacBeth pricing tests. We also split first our sample using endogenously determined structural breaks. Second, we divide our sample into three equal sub-periods. The results are consistent with our main findings suggesting that expected returns of individual stocks are explained by idiosyncratic skewness. Both idiosyncratic volatility and idiosyncratic kurtosis are irrelevant to asset prices at the individual stock level. As an alternative method, we run Fama-MacBeth tests at the portfolio level. We find that idiosyncratic skewness is not significantly related to returns on idiosyncratic skewness-sorted portfolios. However, it is significant when tested against idiosyncratic kurtosis sorted portfolios.

Year 6 students' idiosyncratic notions of unitising, reunitising and regrouping decimal number places

Having flexible notions of the unit (e.g., 26 ones can be thought of as 2.6 tens, 1 ten 16 ones, 260 tenths, etc.) should be a major focus of elementary mathematics education. However, often these powerful notions are relegated to computations where the major emphasis is on "getting the right answer" thus procedural knowledge rather than conceptual knowledge becomes the primary focus. This paper reports on 22 high-performing students' reunitising processes ascertained from individual interviews on tasks requiring unitising, reunitising and regrouping; errors were categorised to depict particular thinking strategies. The results show that, even for high-performing students, regrouping is a cognitively complex task. This paper analyses this complexity and draws inferences for teaching.

The relationship between kurtosis- and envelope-based indexes for the diagnostic of rolling element bearings

The coupling of kurtosis based-indexes and envelope analysis represents one of the most successful and widespread procedures for the diagnostics of incipient faults on rolling element bearings. Kurtosis-based indexes are often used to select the proper demodulation band for the application of envelope-based techniques. Kurtosis itself, in slightly different formulations, is applied for the prognostic and condition monitoring of rolling element bearings, as a standalone tool for a fast indication of the development of faults. This paper shows for the first time the strong analytical connection which holds for these two families of indexes. In particular, analytical identities are shown for the squared envelope spectrum (SES) and the kurtosis of the corresponding band-pass filtered analytic signal. In particular, it is demonstrated how the sum of the peaks in the SES corresponds to the raw 4th order moment. The analytical results show as well a link with an another signal processing technique: the cepstrum pre-whitening, recently used in bearing diagnostics. The analytical results are the basis for the discussion on an optimal indicator for the choice of the demodulation band, the ratio of cyclic content (RCC), which endows the kurtosis with selectivity in the cyclic frequency domain and whose performance is compared with more traditional kurtosis-based indicators such as the protrugram. A benchmark, performed on numerical simulations and experimental data coming from two different test-rigs, proves the superior effectiveness of such an indicator. Finally a short introduction to the potential offered by the newly proposed index in the field of prognostics is given in an additional experimental example. In particular the RCC is tested on experimental data collected on an endurance bearing test-rig, showing its ability to follow the development of the damage with a single numerical index.

Autorregresive conditional volatility, skewness and kurtosis

This paper proposes a GARCH-type model allowing for time-varying volatility, skewness and kurtosis. The model is estimated assuming a Gram-Charlier series expansion of the normal density function for the error term, which is easier to estimate than the non-central t distribution proposed by Harvey and Siddique (1999). Moreover, this approach accounts for time-varying skewness and kurtosis while the approach by Harvey and Siddique (1999) only accounts for nonnormal skewness. We apply this method to daily returns of a variety of stock indices and exchange rates. Our results indicate a significant presence of conditional skewness and kurtosis. It is also found that specifications allowing for time-varying skewness and kurtosis outperform specifications with constant third and fourth moments.

Idiosyncratic psychological aspects in entrepreneurship

Entrepreneurship is having the courage to transform an idea in reality and with it achieve personal, financial and recognition satisfaction. The psychological ability to handle failure has proven essential in success. Goal: Analyse the importance of idiosyncratic psychological aspects in the success of entrepreneurs. Method: Observational study, using a case study, a group of 20 entrepreneurs from the idea presentation phase to company incorporation during a period of two months. Results: During the observation period 4 distinct psychological phases of the entrepreneurs were observed, being it possible to describe them as follows: absorption of information and knowledge; application of the gathered knowledge to their specific cases; frustration generated by criticism, namely from investors who don’t recognize the value of their projects; realism and implementation of the project. Having passed more than 6 months after the analysis period, one can verify the entrepreneurs who have travelled the 4 phases and specially reached the realism of Phase 4, are today developing their projects being that the remaining ones, majority of which weren’t able to overcome Phase 3, are in a similar situation as at the end of the initial two months. Conclusion: The ability to cope with frustration and rejection is a determinant factor in the success of the entrepreneur. The ability to learn from rejection, more than resilience help the entrepreneur to proceed. Therefore, based on the observations, entrepreneurship has a lot to gain if besides technical assistance also coaching assistance is provided.

Consistent patterns and the idiosyncratic effects of biodiversity in marine ecosystems

Revealing the consequences of species extinctions for ecosystem function has been a chief research goal(1-7) and has been accompanied by enthusiastic debate(8-11). Studies carried out predominantly in terrestrial grassland and soil ecosystems have demonstrated that as the number of species in assembled communities increases, so too do certain ecosystem processes, such as productivity, whereas others such as decomposition can remain unaffected(12). Diversity can influence aspects of ecosystem function, but questions remain as to how generic the patterns observed are, and whether they are the product of diversity, as such, or of the functional roles and traits that characterize species in ecological systems. Here we demonstrate variable diversity effects for species representative of marine coastal systems at both global and regional scales. We provide evidence for an increase in complementary resource use as diversity increases and show strong evidence for diversity effects in naturally assembled com-munities at a regional scale. The variability among individual species responses is consistent with a positive but idiosyncratic pattern of ecosystem function with increased diversity.

Idiosyncratic species effects confound size-based predictions of responses to climate change

Understanding and predicting the consequences of warming for complex ecosystems and indeed individual species remains a major ecological challenge. Here, we investigated the effect of increased seawater temperatures on the metabolic and consumption rates of five distinct marine species. The experimental species reflected different trophic positions within a typical benthic East Atlantic food web, and included a herbivorous gastropod, a scavenging decapod, a predatory echinoderm, a decapod and a benthic-feeding fish. We examined the metabolism-body mass and consumption-body mass scaling for each species, and assessed changes in their consumption efficiencies. Our results indicate that body mass and temperature effects on metabolism were inconsistent across species and that some species were unable to meet metabolic demand at higher temperatures, thus highlighting the vulnerability of individual species to warming. While body size explains a large proportion of the variation in species' physiological responses to warming, it is clear that idiosyncratic species responses, irrespective of body size, complicate predictions of population and ecosystem level response to future scenarios of climate change. © 2012 The Royal Society.

Idiosyncratic volatility around information release date

Several papers document idiosyncratic volatility is time-varying and many attempts have been made to reveal whether idiosyncratic risk is priced. This research studies behavior of idiosyncratic volatility around information release dates and also its relation with return after public announcement. The results indicate that when a company discloses specific information to the market, firm’s specific volatility level shifts and short-horizon event-induced volatility vary significantly however, the category to which the announcement belongs is not important in magnitude of change. This event-induced volatility is not small in size and should not be downplayed in event studies. Moreover, this study shows stocks with higher contemporaneous realized idiosyncratic volatility earn lower return after public announcement consistent with “divergence of opinion hypothesis”. While no significant relation is found between EGARCH estimated idiosyncratic volatility and return and also between one-month lagged idiosyncratic volatility and return presumably due to significant jump around public announcement both may provide some signals regarding future idiosyncratic volatility through their correlations with contemporaneous realized idiosyncratic volatility. Finally, the study show that positive relation between return and idiosyncratic volatility based on under-diversification is inadequate to explain all different scenarios and this negative relation after public announcement may provide a useful trading rule.

Exact Skewness-Kurtosis Tests for Multivariate Normality and Goodness-of-fit in Multivariate Regressions with Application to Asset Pricing Models

We study the problem of testing the error distribution in a multivariate linear regression (MLR) model. The tests are functions of appropriately standardized multivariate least squares residuals whose distribution is invariant to the unknown cross-equation error covariance matrix. Empirical multivariate skewness and kurtosis criteria are then compared to simulation-based estimate of their expected value under the hypothesized distribution. Special cases considered include testing multivariate normal, Student t; normal mixtures and stable error models. In the Gaussian case, finite-sample versions of the standard multivariate skewness and kurtosis tests are derived. To do this, we exploit simple, double and multi-stage Monte Carlo test methods. For non-Gaussian distribution families involving nuisance parameters, confidence sets are derived for the the nuisance parameters and the error distribution. The procedures considered are evaluated in a small simulation experi-ment. Finally, the tests are applied to an asset pricing model with observable risk-free rates, using monthly returns on New York Stock Exchange (NYSE) portfolios over five-year subperiods from 1926-1995.

Cross–Sectoral Variation in Firm–Level Idiosyncratic Risk

We estimate firm–level idiosyncratic risk in the U.S. manufacturing sector. Our proxy for risk is the volatility of the portion of growth in sales or TFP which is not explained by either industry– or economy–wide factors, or firm characteristics systematically associated with growth itself. We find that idiosyncratic risk accounts for about 90% of the overall uncertainty faced by firms. The extent of cross–sectoral variation in idiosyncratic risk is remarkable. Firms in the most volatile sector are subject to at least three times as much uncertainty as firms in the least volatile. Our evidence indicates that idiosyncratic risk is higher in industries where the extent of creative destruction is likely to be greater.

Cross-sectoral variation in the volatility of plant-level idiosyncratic shocks

We estimate the volatility of plant–level idiosyncratic shocks in the U.S. manufacturing sector. Our measure of volatility is the variation in Revenue Total Factor Productivity which is not explained by either industry– or economy–wide factors, or by establishments’ characteristics. Consistent with previous studies, we find that idiosyncratic shocks are much larger than aggregate random disturbances, accounting for about 80% of the overall uncertainty faced by plants. The extent of cross–sectoral variation in the volatility of shocks is remarkable. Plants in the most volatile sector are subject to about six times as much idiosyncratic uncertainty as plants in the least volatile. We provide evidence suggesting that idiosyncratic risk is higher in industries where the extent of creative destruction is likely to be greater.

Cross-sectional dependence in idiosyncratic volatility

This paper introduces a framework for analysis of cross-sectional dependence in the idiosyncratic volatilities of assets using high frequency data. We first consider the estimation of standard measures of dependence in the idiosyncratic volatilities such as covariances and correlations. Next, we study an idiosyncratic volatility factor model, in which we decompose the co-movements in idiosyncratic volatilities into two parts: those related to factors such as the market volatility, and the residual co-movements. When using high frequency data, naive estimators of all of the above measures are biased due to the estimation errors in idiosyncratic volatility. We provide bias-corrected estimators and establish their asymptotic properties. We apply our estimators to high-frequency data on 27 individual stocks from nine different sectors, and document strong cross-sectional dependence in their idiosyncratic volatilities. We also find that on average 74% of this dependence can be explained by the market volatility.