Martin Boďa, Vladimír Úradníček
The paper notices troublesome aspects of compiling industry statistics for the purpose of inter-enterprise comparison in corporate financial analysis. Whilst making a caveat that this issue is unbeknownst to practitioners and underrated by theorists, the goal of the paper is two-fold. For one thing, the paper demonstrates that financial ratios are inclined to frequency distributions characteristic of power-law (fat) tails and their typical shape precludes a simple treatment. For the other, the paper explores different approaches to compiling industry statistics by considering trimming and winsorizing cleansing protocols, and by confronting trimmed, winsorized as well as quantile measures of central tendency. The issues are empirically illustrated on data for a great number of Slovak construction enterprises for two years, 2009 and 2018. The empirical distribution of eight financial ratios is studied for troublesome features such as asymmetry and power-law (fat) tails that hamper usefulness of traditional descriptive measures of location without considering different possibilities of handling atypical values (such as infinite and outlying values). The confrontation of diverse approaches suggests a plausible route to compiling industry statistics that consists in reporting a 25% trimmed mean alongside 25% and 75% quantiles, all applied to trimmed data (i.e. data after discarding infinite values). The paper also highlights the sorely unnoticed fact that the key ratio of financial analysis, return on equity, may easily attain non-sense values and these should be removed prior to compiling financial analysis; otherwise, industry statistics is biased upward regardless of what measure of central tendency is made use of.
Bogdan Włodarczyk, Ireneusz Miciuła
Risk management is one of the most dynamically developed areas in economic sciences. One of the main driving forces for this development has been the practical challenge resulting from increasing financial risk. Risk management is a process in which key role is played by risk measurement (Jajuga, 2016). Comparison of various forecasting models and selection of the best ones for particular markets is of key importance in many fields of economics and finance. Theoretic aspects concerning commodity markets very often concentrate on relations between changes in commodity prices and on the news impact on rates of return. However, up until now studies concerning conditional volatility of returns on commodity markets and market risk have been less comprehensive than those concerning conditions affecting prices and rates of return. Nevertheless, studies concerning market volatility are becoming increasingly popular due to the growth of market volatility itself and
the significance of commodities as investment assets (Kang, 2013; Thuraisamy, 2013; Vivian, 2012). The growing interest also results from the fact that commodity rates of return have some empirically verifiable features such as non-normal distribution, asymmetry, structural breaks and fat tails (Aloui, 2010; Cheng, 2011).
Pengshi Li, Wei Li, Haidong Chen
The collar option is one kind of exotic options which is useful when institutional investors wish to lock in the profit they already have on the underlying asset. Collar options can be implemented by investors on the stock they have already own. Usually investors will obtain the collar when they have enjoyed a decent gain on their investment but they want to hedge against potential downside in their shares. Collar options are very useful and practical instruments in revenue management and project management. Shan et al. (2010) study the use of collar options to manage revenue risks in real toll public-private partnership transportation projects, in particular how to redistribute the profit and losses in order to improve the effectiveness of risk management and fulfill the stakeholder’s needs. Under the constant volatility assumption, the pricing problem of collar option can be solved in the classical Black Scholes framework. However, the smile-shaped pattern of the Black Scholes implied volatilities which extracted from options has provided evidence against the constant volatility assumption in the Black Scholes model.
Gentjan Çera, Quyen Phu Thi Phan, Armenia Androniceanu, Edmond Çera
The Internet plays a vital role in our daily life in that people can easily access our world and open international borders. Meanwhile, online shopping has been widely accepted as a way of purchasing products and services. It provides a dominant alternative to traditional retail shopping. Consumers can search for more information and select to compare product and price, more options, convenience. Online shopping offers more satisfaction to consumers save time (Katawetawaraks & Wang, 2011). However, the investigation of online consumer behaviour is relatively underdeveloped (Smith et al., 2013). Although online shopping behaviour is not a new topic, the unanswered question that what determines consumers’ willingness to purchase a product online have attracted many researchers. In this line of study, researchers identified factors influencing on purchase behaviour of the consumer based on Theory Planned Behavior (Ajzen, 1991), Technology Acceptance Model (Davis, 1989), Stimulus–Organism–Response (Mehrabian & Russell, 1974). The first approach focused on the direct impact on consumer behaviour. For example, Wu and Ke (2015) integrated a model of personality traits, perceived risk and technology acceptance in online shopping behaviour.