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This study investigates whether the disclosure of derivatives is value relevant in emerging markets and evaluates the effects of the 2008/2009 global financial crisis on the value relevance of derivative disclosures.

Panel regression models using sub-samples and a crisis interaction term were applied to a sample of the 200 largest non-financial firms by market capitalization listed on the Johannesburg Stock Exchange (JSE) from 2005 to 2017 to assess the consequences of the financial crisis.

The results suggest that the disclosure of derivatives is value relevant in the hitherto understudied context of emerging markets. The 2008/2009 financial crisis had a significant impact on derivatives use and the value relevance of derivatives disclosure by JSE-listed companies.

Companies should reconsider both how they employ derivatives as part of their risk management practices and how they communicate derivatives use to stakeholders in the financial statements. The findings facilitate a comparative analysis across various market contexts by researchers and assist investors in better decision-making. The findings can influence regulatory practices and can help standard setters to review disclosure requirements.

The benefits of corporate hedging were studied from an emerging market perspective, using an original dataset and approach to investigate the effects of international financial volatility on emerging markets. The authors tested whether companies are valued differently, based on their disclosure of the use of derivatives in the financial statements, and the effect of the financial crisis on the value relevance derivatives disclosures.

Considering the frequency of extreme events, enhancing the global financial system's stability has become crucial. This study aims to investigate the contagion effects of extreme risk events in the international commodity market on China's financial industry. It highlights the significance of comprehending the origins, severity and potential impacts of extreme risks within China's financial market.

This study uses the tail-event driven network risk (TENET) model to construct a tail risk spillover network between China's financial market and the international commodity market. Combining with the characteristics of the network, this study employs an autoregressive distributed lag (ARDL) model to examine the factors influencing systemic risks in China's financial market and to explore the early identification of indicators for systemic risks in China's financial market.

The research reveals a strong tail risk contagion effect between China's financial market and the international commodity market, with a more pronounced impact from the latter to the former. Industrial raw materials, food, metals, oils, livestock and textiles notably influence China's currency market. The systemic risk in China's financial market is driven by systemic risks in the international commodity market and network centrality and can be accurately predicted with the ARDL-error correction model (ECM) model. Based on these, Chinese regulatory authorities can establish a monitoring and early warning mechanism to promptly identify contagion signs, issue timely warnings and adjust regulatory measures.

This study provides new insights into predicting systemic risk in China's financial market by revealing the tail risk spillover network structure between China's financial and international commodity markets.

This study aims to examine the effect of corporate derivatives use on firm value and how the corporate governance index modifies this relationship.

The sample consists of 219 nonfinancial firms on the Pakistan Stock Exchange (PSX) from 2011 to 2019. The study used ordinary least square regression with year and industry dummies for estimations. Multiple estimation models such as fixed/random effect, Fama–MacBeth and two-stage least squares (2SLS) are used for robustness. Finally, the PROCESS macro tool is used to estimate the effect of moderating the role of corporate governance (CG) as robustness.

The findings show that derivatives use has an inverse influence on firm value. The firms did not use derivatives as a risk management tool but for speculation motives. However, the corporate governance index significantly weakens this relationship. However, strong governance forces the managers to use derivatives for hedging purposes. The firm-specific factors, including size, age, leverage, cash, financial distress cost, dividend and growth opportunities, also significantly influence firm value. The findings are robust to the other estimation models.

The findings indicate that emerging economies like Pakistan are more prone to agency problems. The strong corporate governance structure helps firms turn the speculative motive of derivatives use into hedging purposes and mitigate the agency issues.

This empirical evidence suggests that good governance structures can help improve the impact of derivative usage on firm value.

To the best of the author's knowledge, this is the first study that examines the conditional role of corporate governance on the derivatives–value relationship from the viewpoint of agency problem/speculative motive.

This study investigates the effect of auditing industry specialization (AIS) on the relative derivatives use for earnings management.

The sample chosen in this study comprises 30,599 firm-year observations of Chinese public companies from 2005 to 2018. The sample is divided into two time periods (2005–2013 and 2014–2018) according to the year when IFRS 9 was implemented (IFRS 9, first discussed by the International Accounting Standards Board in March 2008, is based on an expected credit loss model for determining new and existing expected credit losses on financial assets. The definition was completed in July 2014 and implemented in 2018). AIS was gauged with respect to audit firms and individual auditors, and measured by market share in number and scale of clients. Linear regression is adopted to test hypotheses. Moreover, two-stage least square model (2SLS) is used to eliminate the concern of possible endogeneity.

When gauged with respect to client scale, the scale-based AIS constrained the level of derivatives use for earnings management in the first period (2005–2013) while increased the level in the second period (2014–2018). The findings sustain for the analysis of audit firms and that of individual auditors, and for different definitions of AIS.

The positive AIS-IN relation after the adoption of IFRS 9 implies the sacrifice audit independence. This could be indebted to the government policy that favors local audit firms to be comparable to international Big 4 audit firms, and therefore results in competition among local auditors/audit firms in securing number rather than quality of clients.

The data of AIS in China are collected using a Python web crawler.

The purpose of this study is to analyse and compile the literature on various option pricing models (OPM) or methodologies. The report highlights the gaps in the existing literature review and builds recommendations for potential scholars interested in the subject area.

In this study, the researchers used a systematic literature review procedure to collect data from Scopus. Bibliometric and structured network analyses were used to examine the bibliometric properties of 864 research documents.

As per the findings of the study, publication in the field has been increasing at a rate of 6% on average. This study also includes a list of the most influential and productive researchers, frequently used keywords and primary publications in this subject area. In particular, Thematic map and Sankey’s diagram for conceptual structure and for intellectual structure co-citation analysis and bibliographic coupling were used.

Based on the conclusion presented in this paper, there are several potential implications for research, practice and society.

This study provides useful insights for future research in the area of OPM in financial derivatives. Researchers can focus on impactful authors, significant work and productive countries and identify potential collaborators. The study also highlights the commonly used OPMs and emerging themes like machine learning and deep neural network models, which can inform practitioners about new developments in the field and guide the development of new models to address existing limitations.

The accurate pricing of financial derivatives has significant implications for society, as it can impact the stability of financial markets and the wider economy. The findings of this study, which identify the most commonly used OPMs and emerging themes, can help improve the accuracy of pricing and risk management in the financial derivatives sector, which can ultimately benefit society as a whole.

It is possibly the initial effort to consolidate the literature on calibration on option price by evaluating and analysing alternative OPM applied by researchers to guide future research in the right direction.

We have developed in this paper a morphological disambiguation hybrid system for the Arabic language that identifies the stem, lemma and root of a given sentence words. Following an out-of-context analysis performed by the morphological analyser Alkhalil Morpho Sys, the system first identifies all the potential tags of each word of the sentence. Then, a disambiguation phase is carried out to choose for each word the right solution among those obtained during the first phase. This problem has been solved by equating the disambiguation issue with a surface optimization problem of spline functions. Tests have shown the interest of this approach and the superiority of its performances compared to those of the state of the art.

Interest rate derivatives (IRDs) are the essential components of financial risk management and are used across various industry sectors. The objective is to analyze the differences in approach to managing interest rate risks between the Indian corporates that execute IRDs and the ones that do not.

Interest rate fluctuations require Indian corporates to hedge their exposures in foreign currency interest rates. This is all the more true for mid-sized corporates because of their balance sheet exposures. Additionally, they may not have the resources to formulate risk management policies. This paper analyzes data collected from financial statements of a diverse set of companies that use IRD and helps in formulating such a strategy.

The results indicate significant differences for some of the parameters like information asymmetry and agency cost between users and non-users of IRDs. The study further suggests causality between users of derivatives and parameters like size, growth and debt.

The study compares users and non-users of IRDs, thereby identifying factors unique to users of IRDs. It also studies causality relations which explain the motivation to do IRDs. Thus, it enables risk managers to use this as a reference point to decide on their strategies.

While there are multiple studies across geographies and sectors including commercial banks in India on the usage of interest rate swaps, this study focuses on Indian mid-tier corporates. Furthermore, the study distinguishes between users and non-users based on financial parameters, which in turn would provide a framework for decision-hedging strategies.

This study aims to propose an aerodynamic force decomposition which, for the first time, allows for thrust/drag bookkeeping in two-dimensional viscous and unsteady flows. Lamb vector-based far-field methods are used at the scope, and the paper starts with extending recent steady compressible formulas to the unsteady regime.

Exact vortical force formulas are derived considering inertial or non-inertial frames, viscous or inviscid flows, fixed or moving bodies. Numerical applications to a NACA0012 airfoil oscillating in pure plunging motion are illustrated, considering subsonic and transonic flow regimes. The total force accuracy and sensitivity to the control volume size is first analysed, then the axial force is decomposed and results are compared to the inviscid force (thrust) and to the steady force (drag).

Two total axial force decompositions in thrust and drag contributions are proposed, providing satisfactory results. An additional force decomposition is also formulated, which is independent of the arbitrary pole appearing in vortical formulas. Numerical inaccuracies encountered in inertial reference frames are eliminated, and the extended formulation also allows obtaining an accurate force prediction in presence of shock waves.

No thrust/drag bookkeeping methodology was actually available for oscillating airfoils in viscous and compressible flows.

The main aim of this study is to characterise and identify specific chemo-sensory profiles of ciders from the Canary Islands (Spain).

Commercial samples of Canary ciders were compared to ciders from the Basque Country and Asturias. In total, 18 samples were studied, six for each region. The analysis comprised their sensory profiling and chemical characterisation of their polyphenolic profile, volatile composition, conventional chemical parameters and CIELAB colour coordinates. In parallel, the sensory profile of the samples from the Canary Islands was first compared with their Basque and Asturian counterparts by labelled sorting task. Then, their specific aroma profile was characterised by flash profile. Further quantification of sensory-active compounds was performed by GC–MS and GC-FID to identify the volatile compounds involved in their aroma profile.

Results show that Canary ciders present a specific chemical profile characterised by higher levels of ethanol, and hydroxycinnamic acids, mainly t-ferulic, t-coumaric and neochologenic acids, and lower levels of volatile and total acidity than their Asturian and Basque counterparts. They also present a specific aroma profile characterised by fruity aroma, mainly fruit in syrup and confectionary, and sweet flavours related to their highest levels of vinylphenols formed by transformation of hydroxycinnamic acids.

An integrated strategy to explore the typicity of the currently existing Canary ciders in the market was developed. The results are important in that they will help other regions to identify specific typical chemo-sensory profiles and to promote the creation of certifications supporting regional typicity.

This paper aims to propose a robust method for non-rigid point set registration, using the Gaussian mixture model and accommodating non-rigid transformations. The posterior probabilities of the mixture model are determined through the proposed integrated feature divergence.

The method involves an alternating two-step framework, comprising correspondence estimation and subsequent transformation updating. For correspondence estimation, integrated feature divergences including both global and local features, are coupled with deterministic annealing to address the non-convexity problem of registration. For transformation updating, the expectation-maximization iteration scheme is introduced to iteratively refine correspondence and transformation estimation until convergence.

The experiments confirm that the proposed registration approach exhibits remarkable robustness on deformation, noise, outliers and occlusion for both 2D and 3D point clouds. Furthermore, the proposed method outperforms existing analogous algorithms in terms of time complexity. Application of stabilizing and securing intermodal containers loaded on ships is performed. The results demonstrate that the proposed registration framework exhibits excellent adaptability for real-scan point clouds, and achieves comparatively superior alignments in a shorter time.

The integrated feature divergence, involving both global and local information of points, is proven to be an effective indicator for measuring the reliability of point correspondences. This inclusion prevents premature convergence, resulting in more robust registration results for our proposed method. Simultaneously, the total operating time is reduced due to a lower number of iterations.