Purpose The authors target the interrelationships between non-fungible tokens (NFTs), decentralized finance (DeFi) and carbon allowances (CA) markets during 2021–2023. recent shift of crypto DeFi miners from China (the People's Republic China, PRC) green hydro energy to dirty fuel energies elsewhere induces investments in offsetting instruments; this is a backdrop authors’ investigation. Design/methodology/approach quantile vector autoregression (VAR) approach employed examine...

This paper examines the quantile connectedness between energy transition metals, defined as those needed for from dirty to clean energy, and global economic financial sentiment benchmarks. Using data five - namely, aluminum, cobalt, copper, lithium, nickel, two indices over 2019–2022, we empirically demonstrate that US Economic Sentiment Index (ESI) Societe Generale Global (SGGSI) are found be net receivers of shocks across all four extreme quantiles: 0.05, 0.10, 0.90, 0.95. Thus, it is...

The complex interplay between agricultural and energy commodities has been a subject of interest in past research, gaining more relevance recently due to geopolitical events such as the conflict Ukraine Russia. This systematically driven up prices both commodities. Deeply understanding dynamic interconnections these cascading resulting from war is crucial for comprehensive market analysis. Our study leverages connectedness or risk spillover based on Quantile Vector Autoregression (QVAR)...

This study finds interesting outcomes regarding the interlinkage between food, energy, and water sectors. The UN's Food Agriculture Organization data from January 1961 till 2023 are employed for six variables, namely Total Renewable Water resources per capita (TRW), Internal (TIRW), Withdrawal (TWW), Global Consumption (GFC), Crop Production (GCP), Electricity (GEC). Employing Quantile Vector Auto-Regression (QVAR) methodology, we observe asymmetry in connectedness across quantiles. Positive...

The Bitcoin mining process is energy intensive, which can hamper the much-desired ecological balance. Given that persistence of high levels consumption could have permanent policy implications, we examine presence long memory in daily data Energy Consumption Index (BECI) (BECI upper bound, BECI lower and average) covering period 25 February 2017 to January 2022. Employing fractionally integrated GARCH (FIGARCH) multifractal detrended fluctuation analysis (MFDFA) models estimate order...

Bubbles are usually chaotic but can be predictable, provided their formation matches the log periodic power law (LPPL) with unique stylized facts. We investigated Green Bubble behaviour in stock prices of a selection stocks during COVID-19 pandemic, namely, those highest market capitalization from basket North American and European green energy or clean tech companies S&P Global Clean Energy Index. Moreover, biggest Exchange Traded Fund (TAN) by was also considered. The examined period...

In this study we examine the relationship between corporate green bonds and commodities (both perishable & non-perishable) that attracts very little attention in relative literature. For first time, investigate a long-term including significantly higher number of observations. Furthermore, adopt novel methodology, VaR (value at risk) based copulas, to describe asymmetric risk spillover by considering tail distribution. Our results reveal an insignificant effect from commodity market...

<span lang="EN-US">Predicting equities market trends is one of the most challenging tasks for participants. This study aims to apply machine learning algorithms aid in accurate Nifty 50 index trend predictions. The paper compares and contrasts four forecasting methods: artificial neural networks (ANN), support vector machines (SVM), naive bayes (NB), random forest (RF). In this study, eight technical indicators are used, then deterministic layer used translate indications into signals....

Agri commodities have been investigated in the past to determine their inter-relationships. However, no study has checked risk spillover/connectedness for six decades using extreme quantiles. Various shocks (positive/negative) often pose challenges these over decades. Such shocks' impact is usually observed quantiles or tails. Therefore, we fourteen agri (namely Coffee, Cocoa, Soyabean, Wheat, Sugar, Orange, Chicken, Beef, Maize, Tea, Coconut Oil, Groundnut Palm Oil & Rice) from January 1,...

Unlike previous studies that consider the Chicago Board of Options Exchange (CBOE) implied volatility index (VIX), we examine long memory and fractality in universe nine CBOE indices. Using daily data from October 5, 2007, to 2020, covering calm crisis periods, find evidence all indices a change degree persistence, which points inefficiency. The SKEW is strong before onset three but eases afterwards. findings provide new insights matter investment decisions trading strategies.

We investigate the connectedness of automated market makers (AMM) that play a pivotal role in liquidity and ease operations decentralized exchange (DEX). By applying TVP-VAR model, our findings show higher level connectivity during periods turmoil (such as Delta, Omicron variants SARS-Covid, Russia Ukraine conflict). Furthermore, risk transmission/reception is found to be independent platform on which they typically run (Ethereum based AMMs were both emitters well receivers). Pancake (a...

This study delves into the herding and bubble detection in volatility domain of a capital market underlying. Furthermore, it focuses on creating heuristics, so that common investors find relatively easy to understand state volatility. Hence, can be termed this is focused specific financial innovation regarding coupled with investor awareness. The traces possible emerge when positioned against its own lags (both lag1 lag2). trigger indicated clear an embedded parabola function. Continuous...

The financial markets are found to be finite Hilbert space, inside which the stocks displaying their wave-particle duality. Reynolds number, an age old fluid mechanics theory, has been redefined in investment finance domain identify possible explosive moments stock exchange. CNX Nifty Index, a known index on National Stock Exchange of India Ltd., put test under this situation. number (its version) predicted, as well connected with plausible behavioral rationale. While predicting, both...

A growing body of research work on Log Periodic Power Law (LPPL) tries to predict market bubbles and crashes. Mostly, the fitment parameters remain confined within certain specific ranges. This paper examines these claims robustness reformulated LPPL model Filimonov & Sornette (2013) for capturing large falls in S&P BSE Sensex, an Indian heavyweight index over period 2000–2019. Thirty-five mid large-sized crashes are identified during this period, forming a clear signature. confirms...

Tweets seem to impact diverse assets, especially during stressful periods. However, their interrelations events may change. Cryptos are apparently more sensitive the sentiment spread by tweets. Therefore, a construct could be formed study such complex interrelation events. This found an interesting outcome while investigating three major asset classes (namely, Equity, Gold and Bond) alongside negative (derived from tweets of Elon Musk) Dogecoin (an emerging class) 1 June 2015 20 February...

Incentivizing businesses to lower carbon emissions and trade back excess allowances paved the way for rapid growth in credit ETFs. The use of as a hedging alternative fueled this rally further, causing shift speculation forming repetitive bubbles. Speculative bubbles are born from euphoria, yet, they relatively predictable, provided their pattern matches log periodic power law (LPPL) with specific stylized facts. A “Minsky moment” identifies clear speculative bubble signal financial system...

We herein employ an alternative approach to model the financial bubbles prior crashes and fit a log-periodic power law (LPPL) IIGPS countries (Italy, Ireland, Greece, Portugal, Spain) during Brexit. These represent five financially troubled economies of Eurozone that have suffered most Brexit referendum. It was found all 77 across nations from 19 January 2015 until 17 February 2020 strictly followed or other LPPL signature. They had speculative bubble phase (following growth) then by sudden...