Sanjay Sehgal, Ritesh Kumar Mishra, Florent Deisting and Rupali Vashisht
The main aim of the study is to identify some critical microeconomic determinants of financial distress and to design a parsimonious distress prediction model for an emerging…
Abstract
Purpose
The main aim of the study is to identify some critical microeconomic determinants of financial distress and to design a parsimonious distress prediction model for an emerging economy like India. In doing so, the authors also attempt to compare the forecasting accuracy of alternative distress prediction techniques.
Design/methodology/approach
In this study, the authors use two alternatives accounting information-based definitions of financial distress to construct a measure of financial distress. The authors then use the binomial logit model and two other popular machine learning–based models, namely artificial neural network and support vector machine, to compare the distress prediction accuracy rate of these alternative techniques for the Indian corporate sector.
Findings
The study’s empirical results suggest that five financial ratios, namely return on capital employed, cash flows to total liability, asset turnover ratio, fixed assets to total assets, debt to equity ratio and a measure of firm size (log total assets), play a highly significant role in distress prediction. The study’s findings suggest that machine learning-based models, namely support vector machine (SVM) and artificial neural network (ANN), are superior in terms of their prediction accuracy compared to the simple binomial logit model. Results also suggest that one-year-ahead forecasts are relatively better than the two-year-ahead forecasts.
Practical implications
The findings of the study have some important practical implications for creditors, policymakers, regulators and other stakeholders. First, rather than monitoring and collecting information on a list of predictor variables, only six most important accounting ratios may be monitored to track the transition of a healthy firm into financial distress. Second, our six-factor model can be used to devise a sound early warning system for corporate financial distress. Three, machine learning–based distress prediction models have prediction accuracy superiority over the commonly used time series model in the available literature for distress prediction involving a binary dependent variable.
Originality/value
This study is one of the first comprehensive attempts to investigate and design a parsimonious distress prediction model for the emerging Indian economy which is currently facing high levels of corporate financial distress. Unlike the previous studies, the authors use two different accounting information-based measures of financial distress in order to identify an effective way of measuring financial distress. Some of the determinants of financial distress identified in this study are different from the popular distress prediction models used in the literature. Our distress prediction model can be useful for the other emerging markets for distress prediction.
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Sanjay Sehgal, Wasim Ahmad and Florent Deisting
The purpose of this paper is to examine the price discovery and volatility spillovers in spot and futures prices of four currencies (namely, USD/INR, EURO/INR, GBP/INR and…
Abstract
Purpose
The purpose of this paper is to examine the price discovery and volatility spillovers in spot and futures prices of four currencies (namely, USD/INR, EURO/INR, GBP/INR and JPY/INR) and between futures prices of both stock exchanges namely, Multi-Commodity Stock Exchange (MCX-SX) and National Stock Exchange (NSE) in India.
Design/methodology/approach
The study applies cointegration test of Johansen’s along with VECM to investigate the price discovery. GARCH-BEKK model is used to examine the volatility spillover between spot and futures and between futures prices. The other two models namely, constant conditional correlation and dynamic conditional correlation are used to demonstrate the constant and time-varying correlations. In order to confirm the volatility spillover results, the study also applies test of directional spillovers suggested by Diebold and Yilmaz (2009, 2012).
Findings
The results of the study show that there is long-term equilibrium relationship between spot and futures and between futures markets. Between futures and spot prices, futures price appears to lead the spot price in the short-run. Volatility spillover results indicate that the movement of volatility spillover takes place from futures to spot in the short-run while spot to futures found in the long-run. However, the results of between futures markets exhibit the dominance of MCX-SX over NSE in terms of volatility spillovers. By and large, the findings of the study indicate the important role of futures market in price discovery as well as volatility spillovers in India’s currency market.
Practical implications
The results highlight the role of futures market in the information transmission process as it appears to assimilate new information quicker than spot market. Hence, policymakers in emerging markets such as India should focus on the development of necessary institutional and fiscal architecture, as well as regulatory reforms, so that the currency market trading platforms can achieve greater liquidity and efficiency.
Originality/value
Due to recent development of currency futures market, there is dearth of literature on this subject. With the apparent importance of currency market in recent time, this study attempts to study the efficient behavior of currency market by way of examining the price discovery and volatility spillovers between spot and futures and between futures prices of four currencies traded on two platforms. The study has strong implications for India’s stock market especially at the time when its currency is under great strain owing to the adverse impact of global financial crisis.
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The concept of co-movement has witnessed a resurgence in the international finance literature in recent years after the black swan events. This might be due to a renewed focus on…
Abstract
Purpose
The concept of co-movement has witnessed a resurgence in the international finance literature in recent years after the black swan events. This might be due to a renewed focus on globalization and financial market integration in the world over. The purpose of this paper is to examine the dynamic linkages in the foreign exchange market resulting from recent globalization and financial market integration in Africa.
Design/methodology/approach
A conceptual framework was adapted from the extant literature and was used as the basis of modeling foreign exchange market in Africa. This paper adopts a quantitative research approach and opted for dynamic panel data analysis to empirically unearth the determinants of foreign exchange market co-movement.
Findings
It is interesting to note that exchange rate co-movements were externally determined. Robust support was found for trade intensity, competition and world interest rate on foreign exchange rates co-movement, but regional interest rate differential decreased it. These findings clearly demonstrate the level of financial development and challenges that sometimes exist in exchange rate policy implementation by policy makers in Africa.
Research limitations/implications
Future research might incorporate bilateral investment into the model of exchange rate correlation.
Originality/value
Studies focussing on simultaneous consideration of intensity, trade competition and capital account openness to exchange rate correlations in the contexts of Africa are almost non-existent, and this study makes an important contribution in not only addressing this imbalance but also more importantly improving the relatively parsimonious literature on foreign exchange co-movement.
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Paula Cristina Nunes Figueiredo, Maria José Sousa and Eduardo Tomé
The aim of the paper is to propose an integrative model of the leader competences through the analysis of the several models of competence found in the literature review.
Abstract
Purpose
The aim of the paper is to propose an integrative model of the leader competences through the analysis of the several models of competence found in the literature review.
Design/methodology/approach
The methodology used was qualitative, based partially on an integrative literature review (Torraco 2016). This paper aims to review, update and criticize the literature related to the competences approach in the organizational context and, on the other hand, to review, criticize and synthesize the literature, namely, the models and competences.
Findings
Difficulties in choosing and implementing a leader competency model led to the integration of competencies in a single model, seeking to simplify the choice and implementation process in organizations. The integrative model of leader competences arises from the literature review, more specifically from the analysis of the different approaches found. This model is grouped into four dimensions – intellectual competences, management competences, social competences and emotional competences. This research is a contribution to reduce the fragmentation of leadership and management theories and facilitates the choice and implementation of a leader competence model suited to the organization’s needs, contributing to the leadership effectiveness.
Originality/value
The integrative model of the leader competences allows the choice and implementation of a competence model with a wide range of competences considered as essential in the organizational context by several researchers. This model simplifies the process of identifying the competences that need to be developed, feeding the human resources development process within the organization.