Market risk, financial distress and firm performance in Vietnam

Vo, Duc Hong

doi:10.1371/journal.pone.0288621

Cited by 4 publications

(1 citation statement)

References 52 publications

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“…In different models, y it represent the level of firm performance (FP) and business model innovation (BMI). The firm performance is captured by the return on asset (ROA) [70,72,[99][100][101] and earnings per share (EPS) [20,44,54,77,85]. ROA and EPS are the most widely used indicators to measure firm performance, mainly to reflect the efficiency of a company's assets in generating income for the company's shareholders.…”

Section: Methodsmentioning

confidence: 99%

Capital structure, business model innovation, and firm performance: Evidence from Chinese listed corporate based on system GMM model

Tian,

Wang,

Kohar

2024

PLoS ONE

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This paper aims to verify the impact of capital structure on business model innovation and firm performance and the mediating effect of business model innovation. We use the data of the Chinese growth enterprises market (GME) listed high-tech firms from 2016 to 2022 as a dynamic panel data model with the system–generalized method of moments (sys-GMM), adopting return on asset and earning per share as firm performance. Our results show that capital structure has a lag effect on firm performance. The total debt ratio in the last period has a significant non-linear impact on the performance and business model innovation level of nowadays, presenting a U-shaped relationship. The first-order lag short-term debt ratio positively improves firm performance. Business model innovation significantly promotes better firm performance, and business model innovation does exist in the mediating effect between enterprise capital structure and its performance. These results remain robust to different sample sizes or proxy variables. This paper proposes some suggestions for firm operations and government policies based on the findings.

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Section: Methodsmentioning

confidence: 99%

Capital structure, business model innovation, and firm performance: Evidence from Chinese listed corporate based on system GMM model

Tian,

Wang,

Kohar

2024

PLoS ONE

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Market risk spillover and the asymmetric effects of macroeconomic fundamentals on market risk across Vietnamese sectors

Vo,

Nguyen

2024

Financ Innov

Self Cite

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Global economic downturns and multiple extreme events threaten Vietnam's economy, leading to a surge in stock market risk and significant spillovers. This study investigates market risk spillovers and explores the asymmetric effects of macroeconomic indicators on market risk across 24 sectors in Vietnam from 2012 to 2022. We use the value-at-risk (VaR) technique and a vector autoregression (VAR) model to estimate market risks and their spillovers across Vietnamese sectors. We then examine the asymmetric effects of macroeconomic indicators on market risk using a panel nonlinear autoregressive distribution lag (NARDL) model. Our results confirm that Vietnam’s market risk increases rapidly in response to extreme events. Additionally, market risks exhibit substantial inter-connectedness across the Vietnamese sectors. The Building Materials, Technology, and Securities sectors are primary risk transmitters, whereas the Minerals, Development Investment, and Education sectors are major risk absorbers. Our results also confirm that market risk responds asymmetrically to changes in interest rates, exchange rates (USD/VND), trade openness, financial development, and economic growth in the short and long run. Minerals, Oil & Gas, and Rubber are the sectors that are most affected by macroeconomic indicators in the long run. Based on these important findings, implications focused on limiting market risks and their spillovers, along with sustainable investing, have emerged.

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Forecasting Financial Investment Firms’ Insolvencies Empowered with Enhanced Predictive Modeling

Abdul-Kareem,

Fayed,

Rady

et al. 2024

JRFM

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In the realm of financial decision-making, it is crucial to consider multiple factors, among which lies the pivotal concern of a firm’s potential insolvency. Numerous insolvency prediction models utilize machine learning techniques try to solve this critical aspect. This paper aims to assess the financial performance of financial investment firms listed on the Iraq Stock Exchange (ISX) from 2012 to 2022. A Multi-Layer Perceptron predicting model with a parameter optimizer is proposed integrating an additional feature selection process. For this latter process, three methods are proposed and compared: Principal Component Analysis, correlation coefficient, and Particle Swarm Optimization. Through the fusion of financial ratios with machine learning, our model exhibits improved forecast accuracy and timeliness in predicting firms’ insolvency. The highest accuracy model is the integrated MLP + PCA model, at 98.7%. The other models, MLP + PSO and MLP + CC, also exhibit strong performance, with 0.3% and 1.1% less accuracy, respectively, compared to the first model, indicating that the first model serves as a powerful predictive approach.

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Market risk, financial distress and firm performance in Vietnam

Cited by 4 publications

References 52 publications

Capital structure, business model innovation, and firm performance: Evidence from Chinese listed corporate based on system GMM model

Capital structure, business model innovation, and firm performance: Evidence from Chinese listed corporate based on system GMM model

Market risk spillover and the asymmetric effects of macroeconomic fundamentals on market risk across Vietnamese sectors

Forecasting Financial Investment Firms’ Insolvencies Empowered with Enhanced Predictive Modeling

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