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The study investigates the impact of higher moments on cross-sectional returns in the Indian equity market.

Using the daily data of 3,085 Bombay Stock Exchange-listed stocks spanning over 20 years from January 2000 to December 2019, the study evaluates the relationship between higher moments (skewness and kurtosis) and stock returns at individual stock and portfolio levels. The variations in the returns of the equal-weighted and the value-weighted portfolios are analysed, where the portfolios are constructed by sorting the stocks on skewness and kurtosis. The returns are adjusted for five common factors – market excess-returns, size, value, momentum and illiquidity, to controls other cross-sectional effects. Besides, the study employs Fama-MacBeth cross-sectional regression and time-series tests of higher moments as robustness measures.

The study presents higher moments anomaly in the Indian equity market. Contrary to what is expected based on a risk-averse rational agent model, a robust positive relationship is observed between the skewness and stock returns. The relationship between the kurtosis and stock returns is negative, albeit statistically weak. These results are robust for the Fama-MacBeth cross-sectional regression and time-series tests.

It is among the earlier attempts to investigate the pricing impact of higher moments at different levels of asset prices in an emerging market. Besides the standard portfolio methodology for explaining cross-sectional variations, the study also employs the time-series tests for higher moment factors, hence provides more robust results. Results have wider implications for asset pricing in emerging markets and highlight many issues for further research.

The purpose of this paper is to examine the relationships between the higher moments of returns (realized skewness and kurtosis) and subsequent returns at the industry level, with a focus on both empirical predictability and practical application via trading strategies.

Daily returns for 48 US industries over the period 1970–2019 from Kenneth French’s data library are used to calculate the higher moments and to construct short- and medium-term single-sort trading strategies. The analysis adjusts returns for common risk factors (market, size, value, investment, profitability and illiquidity) to confirm whether conventional asset pricing models can capture these relationships.

Past skewness positively relates to subsequent industry returns and this relationship is unexplained by common risk factors. There is also a time-varying effect in which the predictive role of skewness is much stronger over business cycle expansions than recessions, a result consistent with varying investor optimism. However, there is no significant relationship between kurtosis and subsequent industry returns. The analysis confirms robustness using both value- and equal-weighted returns.

The calculation of realized moments conventionally uses high-frequency intra-day data, regrettably unavailable for industries. In addition, the chosen portfolio-sorting method may omit some information, as it compares only average group returns. Nonetheless, the close relationship between skewness and future returns at the industry level suggests variations in returns unexplained by common risk factors. This enriches knowledge of market anomalies and questions yet again weak-form market efficiency and the validity of conventional asset pricing models. One suggestion is that it is possible to significantly improve the existing multi-factor asset pricing models by including industry skewness as a risk factor.

Given the relationship between skewness and future returns at the industry level, investors may predict subsequent industry returns to select better-performing funds. They may even construct trading strategies based on return distributions that would generate abnormal returns. Further, as the evaluation of individual stocks also contains industry information, and stocks in industries with better performance earn higher returns, risks related to industry return distributions can also shed light on individual stock picking.

While there is abundant evidence of the relationships between higher moments and future returns at the firm level, there is little at the industry level. Further, by testing whether there is time variation in the relationship between industry higher moments and future returns, the paper yields novel evidence concerning the asymmetric effect of stock return predictability over business cycles. Finally, the analysis supplements firm-level results focusing only on the decomposed components of higher moments.

By using higher moments, this paper extends the quadratic local risk-minimizing approach in a general discrete incomplete financial market. The local optimization subproblems are convex or nonconvex, depending on the moment variants used in the modeling. Inspired by Lai et al. (2006), the authors propose a new multiobjective approach for the combination of moments that is transformed into a multigoal programming problem.

The authors evaluate financial derivatives with American features using local risk-minimizing strategies. The financial structure is in line with Schweizer (1988): the market is discrete, self-financing is not guaranteed, but deviations are controlled and reduced by minimizing the second moment. As for the quadratic approach, the algorithm proceeds backwardly.

In the context of evaluating American option, a transposition of this multigoal programming leads not only to nonconvex optimization subproblems but also to the undesirable fact that local zero deviations from self-financing are penalized. The analysis shows that issuers should consider some higher moments when evaluating contingent claims because they help reshape the distribution of global cumulative deviations from self-financing.

A detailed numerical analysis that compares all the moments or some combinations of them is performed.

The quadratic approach is extended by exploring other higher moments, positive combinations of moments and variants to enforce asymmetry. This study also investigates the impact of two types of exercise decisions and multiple assets.

This paper aims to test three parametric models in pricing and hedging higher-order moment swaps. Using vanilla option prices from the volatility surface of the Euro Stoxx 50 Index, the paper shows that the pricing accuracy of these models is very satisfactory under four different pricing error functions. The result is that taking a position in a third moment swap considerably improves the performance of the standard hedge of a variance swap based on a static position in the log-contract and a dynamic trading strategy. The position in the third moment swap is taken by running a Monte Carlo simulation.

This paper undertook empirical tests of three parametric models. The aim of the paper is twofold: assess the pricing accuracy of these models and show how the classical hedge of the variance swap in terms of a position in a log-contract and a dynamic trading strategy can be significantly enhanced by using third-order moment swaps. The pricing accuracy was measured under four different pricing error functions. A Monte Carlo simulation was run to take a position in the third moment swap.

The results of the paper are twofold: the pricing accuracy of the Heston (1993) model and that of two Levy models with stochastic time and stochastic volatility are satisfactory; taking a position in third-order moment swaps can significantly improve the performance of the standard hedge of a variance swap.

The limitation is that these empirical tests are conducted on existing three parametric models. Maybe more critical insights could have been revealed had these tests been conducted in a brand new derivatives pricing model.

This work is 100 per cent original, and it undertook empirical tests of the pricing and hedging accuracy of existing three parametric models.

Tapered section can resist maximum stress at a single location while the stresses are considerably lower at the rest of the member; therefore, it could have higher structural efficiency compared to conventional section. It could also satisfy functional requirements while reducing weight and cost in many fields of civil construction. Perforation in the steel section also eases the integration of Mechanical and Electrical (M&E) services such as ventilation pipes and electrical cables within the structural depths of the beam. In this analysis, the structural efficiency of tapered steel section with perforation under lateral-torsional buckling behaviour is investigated.

A total of 81 models are analysed using LUSAS software and five variables are investigated which involved perforation sizes, perforation shapes, perforation layout, tapering ratio and flange and Web thickness. Buckling moment is obtained from the analysis results in LUSAS software, while self-weight and structural efficiency are manually calculated.

Perforation size of 0.75 D has the highest structural efficiency, although it can withstand a smaller buckling load. This is due to its lower self-weight compared to other perforation sizes. The square perforation shape also has the highest structural efficiency compared to circular perforation and diamond perforation. An increment of percentage in structural efficiency of the square perforation shape with 0.75 D is the highest at 3.07%. The circular perforation shape with 0.75 D (Open-Open-Open perforation layout) has the highest increment of percentage in structural efficiency which is 2.37%. The tapering ratio of 0.3 is the most efficient and an increment of percentage in structural efficiency is 114.36%. The flange thickness of 0.02 m and Web thickness of 0.015 m has the highest structural efficiency at 45.756 and 29.171, respectively.

In conclusion, a section should be able to resist the large buckling moment and has a lower self-weight to achieve high structural efficiency.

A common feature of certain kinds of data is a high level of statistical dependence across space and time. This spatial and temporal dependence contains useful information that can be exploited to significantly reduce the uncertainty surrounding local distributions. This chapter develops a methodology for inferring local distributions that incorporates these dependencies. The approach accommodates active learning over space and time, and from aggregate data and distributions to disaggregate individual data and distributions. We combine data sets on Kansas winter wheat yields – annual county-level yields over the period from 1947 through 2000 for all 105 counties in the state of Kansas, and 20,720 individual farm-level sample moments, based on ten years of the reported actual production histories for the winter wheat yields of farmers participating in the United States Department of Agriculture Federal Crop Insurance Corporation Multiple Peril Crop Insurance Program in each of the years 1991–2000. We derive a learning rule that combines statewide, county, and local farm-level data using Bayes’ rule to estimate the moments of individual farm-level crop yield distributions. Information theory and the maximum entropy criterion are used to estimate farm-level crop yield densities from these moments. These posterior densities are found to substantially reduce the bias and volatility of crop insurance premium rates.

Basically, connections are used to transfer the force supported by structural members to other parts of the structure. The flush end-plate bolted beam to column connection is one type that has been widely used because of its simplicity in fabrication and rapid site erection. The purpose of this study is to determine the moment-rotation curve, moment of resistance (MR) and mode of failure, and the results were compared with existing results for normal flat web connections.

In this study, the connection modeled was the flush end-plate welded with triangular web profile (TriWP) steel beam section and then bolted to a UKC column flange. The bolted flush end-plate semi-rigid beam to column connection was modeled using finite element software. The specimen was modeled using LUSAS 14.3 finite element software, with dimensions and parameters of the finite element model sizes being 200 × 200 × 49.9 UKC, 200 × 100 × 17.8 UKB and 200 × 100 with a thickness of 20 mm for the endplate.

It can be concluded that the MR obtained from the TriWP steel beam section is different from that of the normal flat web steel beam by 28%. The value of MR for the TriWP beam section is lower than that of the normal flat web beam section, but the moment ultimate is higher by 21% than the normal flat web. Therefore, it can be concluded that the TriWP section can resist more acting force than the normal flat web section and is suitable to be used as a new proposed shape to replace the normal flat web section for a certain steel structure based on the end-plate connection behavior.

As a result, the TriWP section has better performance than the flat web section in resisting MR behavior.

The purpose of this paper is to perform a relative assessment of performance benchmarks based on alternative asset pricing models to evaluate performance of mutual funds and suggest the best approach in Indian context.

Sample of 237 open-ended Indian equity (growth) schemes from April 2003 to March 2013 is used. Both unconditional and conditional versions of eight performance models are employed, namely, Jensen (1968) measure, three-moment asset pricing model, four-moment asset pricing model, Fama and French (1993) three-factor model, Carhart (1997) four-factor model, Elton et al. (1999) five-index model, Fama and French (2015) five-factor model and firm quality five-factor model.

Conditional version of Carhart (1997) model is found to be the most appropriate performance benchmark in the Indian context. Success of conditional models over unconditional models highlights that fund managers dynamically manage their portfolios.

A significant α generated over and above the return estimated using Carhart’s (1997) model reflects true stock-picking skills of fund managers and it is, therefore, worth paying an active management fee. Stock exchanges and credit rating agencies in India should construct indices incorporating size, value and momentum factors to be used for purpose of benchmarking.

The study adds new evidence as to applicability of established asset pricing models as performance benchmarks in emerging market India. It examines role of higher order moments in explaining mutual fund returns which is an under researched area.