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The influence of the “environmental-friendly” character through asymmetries on market crash price of risk in major stock sectors

This paper investigates the impact that the ‛green character’ of stocks generates on their market price of risk. The study covers a spectrum of international large-cap stocks in influential sectors since 1 January 2013 up to 5 July 2022. Focusing on the asymmetric and shape features of price risk, econometric outcomes reveal that wellestablished (Industrials) or highly profitable (Technology) sectors are less affected by the skewness/kurtosis price of risk or the “environmental-friendly” features. On the contrary, sectors vulnerable to alterations in income or wealth, such as Financials and Real Estate are more sizably influenced by negative asymmetry, kurtosis, and the higher volatility in bear markets. The ‛green character’ lowers the market price of stocks, increases risk premia due to higher probability for downwards movements and renders investors more risk-averse and nevertheless, this impact only reflects the initial period of green innovation with high anti-polluting costs as the green label could prove to be greatly beneficial in the future.
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Evaluating the sophisticated digital assets and cryptocurrencies capacities of substituting international currencies in inflationary eras

This study investigates the dynamic nexus that major international currencies (US dollar, Euro, Japanese yen) exhibit with cryptocurrencies and highly innovative digital money (DeFi and NFT assets) during inflationary periods such as the Russia-Ukraine conflict (from 14 December 2021 until 1 March 2024). The Quantile Vector Autoregressive methodology as in Cunado et al. (2023) and daily data are adopted to investigate the net joint extended dynamic connectedness and network connectedness at lower and upper quantiles. Conventional international currencies act as hedgers against shocks while major cryptocurrencies are only modest generators with Ripple being an influential absorber of effects. DeFi mainly serve for counteracting losses from conventional investments in bear or bull markets and Maker is the most prominent generator of spillovers while NFTs mostly rely on a few very strong leaders –Gala being by far the strongest- to have an impact, imitating Bitcoin in the early cryptocurrency era.
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The influential impacts of international dynamic spillovers in forming investor preferences: a quantile-VAR and GDCC-GARCH perspective

This study investigates whether representative sectoral stock indices, gold, oil, Bitcoin, and wheat can mitigate risk and improve portfolio performance during normal times versus crises. The cutting-edge Quantile Vector Auto regressive model and the Generalized Dynamic Conditional Correlations (Generalized-DCC) framework are adopted covering from 9 January 2017 until 30 August 2022.Econometric findings by the Q-VAR reveal that oil presents the strongest connection with commodities and stock indices and that Bitcoin and wheat despite their significant linkages with financial markets fail to act as safe havens. Moreover, GDCC-GARCH indicates that the returns of sector all indices are weakly related but display powerful volatility co-movements. Gold serves efficiently as a hedger and oil follows and both act as better shelters during crises. Nevertheless, Bitcoin partly abides by conventional markets in stressed periods. Notably, wheat reliably works as a hedger overall but does not become a safe haven during crises.
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The Human Negotiation Code

In The Human Negotiation Code, Loizos S. Michael explores the psychology of negotiation and how understanding human behaviour can improve communication and decision-making. Drawing on diplomatic experience, the book presents practical approaches to preparing for negotiations, identifying underlying interests, managing pressure, and reaching agreements while maintaining relationships.

View publication on Academia.edu

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Destination as a Boundary Condition on Penalty–Reward Asymmetry in Luxury Hotel Guest Satisfaction

Guests weight negative and positive attribute performance asymmetrically, and destination and culture shape service expectations. Whether destination alters this asymmetry itself has received little direct testing. Extending stimulus–organism–response theory, we treat destination as an attribute-level boundary condition on penalty and reward effects. We analyze 12,018 English-language reviews of 75 luxury hotels in eleven destinations (22,144 Booking.com and TripAdvisor reviews in total), coded by keyword-based aspect detection and VADER (Valence Aware Dictionary and sEntiment Reasoner) sentiment scoring. Compared with two human coders, a documented re-implementation of this coding detected mentions and positive evaluations well but recovered only 57 percent of negative mentions, with no detectable destination difference in accuracy. Negative mentions carry larger rating penalties than positive mentions carry rewards, including under human coding. Conventional hotel-clustered tests show destination differences in this asymmetry for four of six attributes, but this result is fragile. A hotel-level permutation diagnostic is non-significant; multilevel models giving each hotel its own penalty and reward leave the difference detectable only for Price–Value and Amenities and Facilities; and results for individual attributes change with the keyword lists (two attributes) and with the treatment of mixed-valence mentions (three attributes). With eleven destinations, destination-level variance cannot be estimated precisely. The findings are preliminary evidence of attribute-specific, destination-organized heterogeneity, with much of it indistinguishable from hotel-level variation, not a confirmed destination effect.

Israr Ahmad, Loizos Michael and Saima Abdullah. Tourism and Hospitality 2026, 7, 318.

View publication on MDPI

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