Financial institutions have witnessed numerous episodes of financial crises all over the world during the last four decades. The researchers, academicians and policy makers in the field of finance studied these episodes extensively and to mitigate the risk involved in these crises have proposed several measures in the financial literature, but Value at Risk (VaR) has emerged as a more popular risk measurement technique. Although a number of studies have been undertaken in this area of research for developed markets but very few studies have been conducted in developing and emerging market economies. This study makes an attempt to evaluate the performance of VaR in emerging markets namely Brazil, Russia, India and China by considering Historical, Monte Carlo and GARCH Simulations to calculate VaR for the period 1998 to 2015. The study found that GJRGARCH Simulation is more suitable for Brazil and China while Historical Simulation for Russian and Indian Stock Markets based on the back-testing experiment.
Day: June 25, 2019
Relationship between Code of Corporate Governance and Corporate Financial Performance (An Empirical Study of Food Companies Listed on KSE)
The crucial role that implementation of Code of Corporate Governance plays on protecting the rights of minorities, shareholders, local as well as foreign investors cannot be denied. Companies all over the world are required to implement their respective Code of Corporate Governance for avoiding agency conflicts between companies management and stakeholders and for assuring transparency in accountability. This paper aims at exploring the impact of implementation of corporate governance practices (designed by Securities and Exchange Commission of Pakistan) have on the financial position of companies. For explanatory variables of the study, composition of the board as per the Code of Corporate Governance that comprises of presence of independent, executive and non-executive directors has been taken into consideration. Return on equity has been taken as an indicator of firms profitability i.e. the dependent variable. For this study, companies listed on food producing sector of Karachi Stock Exchange have been screened for excogitation of the relationship. It is an empirical research based on nine years data from 2007–2015. Using Hausman Test for selecting the data analysis technique between Fixed or Random, Fixed Cross Sectional Panel Analysis has been used for analysis of the data collected. Findings indicate that presence of independent, executive and non-executive directors as per the code requirements levies a significant impact on the profitability of companies indicated by return on equity. It is, thus concluded that companies should ensure compliance with code of governance practices to reduce not only the agency issues but also to increase their profitability.
Static Systematic Risk Profile of Nifty 100 Stocks: A Year on Year Analysis of Beta
Beta Coefficient, as a measurement statistic of systematic risk of securities, was initially explained by Sharpe as a slope of simple linear regression function using rate of return on a market index as independent variable and a securitys rate of return as dependent variable. National Stock Exchange (NSE), the leading stock exchange of India, practice this ordinary least square (OLS) regression based single index market model for disseminating beta coefficients of prominent NIFTY 100 stocks. OLS regression based index model presumes that beta coefficients of securities should remain stable for accuracy of predicted returns. Brenner and Smidt (1977) emphasized the importance of having accurate beta forecast mainly because of (i) understanding risk-return relationships in capital market theory and (ii) extensive usage of beta in making investment decisions. The objective of this paper is to examine year on year stability of beta coefficients of NIFTY 100 index stocks.
Exploratory Factor Analysis for the Identification of Dimensions Which Cause Non-Performing Assets in Non-Banking Financial Institutions
According to Reserve Bank of India (RBI) Governor, public sector banks are having stressed accounts equivalent to over Rs.7 lakh Crores including non-performing assets (NPA) and restructured loans (News Asia, 2016). RBI has also pointed out that gross NPA of public sector banks has risen to 6.03% during June 2015 from 5.20% during March 2015. As banks have growing huge bad debts, steps are being laid down by the RBI and the government to help lending banks clean up their balance sheet by 2017. NPAs impact bank growth or stability and deteriorate profits, increase provisions, reduce reserves, affect capital adequacy, increase market borrowings, drop share values, build negative image about the economy and high interest rates. In order to compensate for the money lost in the form of interest in NPAs, banks have to charge high interest rate from other borrowers. This will have indirect impact on inflation and results in negative impact on development. Overall development of the country will also get affected due to NPA by way of unemployment, business exit due to inability to meet its loan repayment obligations, instability of the banking system, and liquidity crisis. A detailed analysis on the factors which cause NPA has become a high priority research agenda in the present day context. A questionnaire is developed for the purpose to acquire and analyse data to identify factors which cause NPA. Also, an exploratory factor analysis has been carried out to identify factors which contribute to growing NPA in financial institutions. Purpose: The purpose of this paper is to identify factors which cause non-performing assets in non-banking financial institutions. Design or methodology or approach: A questionnaire has been developed to gather data from 120 professionals who are involved in the process of granting or recovering loans in non-banking financial institutions in India and appropriate statistical techniques have been used to test for statistical significance. Findings: As a result of exploratory factor analysis, three components with corresponding factors are identified for the cause of non-performing assets in non-banking financial institutions. These are component 1 which is professional incapability of the borrower in running the firm leading to NPA, component 2 related to borrower nature in wilful default and his or her influential nature on financial institution and government resulting in NPA and, component 3 due to weak internal policy of the firm or external environment which aid non-repayment of loan. Component 1, component 2, and component 3 have nine factors, seven factors, and six factors associated with them, respectively, as explained in the paper. Research limitations or implications: The study identified the factors which are to be critically analysed prior to granting loan so that chance of the loan becoming NPA can be minimised. The success of this finding depends on suitably designed electronic credit worthiness evaluation system that evaluate the borrower. Originality or value: The identification of various factors which contribute to non-performing assets and to take suitable measures to control them is a high priority agenda for any financial institution and this research is directly oriented towards that direction.
Assessing the Inter Bank Disparity in Non-Performing Assets (NPAs) Management in Indian Public Sector Banks
In a bank-dominated financial system like India, the strength of the overall financial system or financial stability highly depends on the soundness of banks. Indian Banking system proved to be strong and resilient during the global financial crisis of 2008. But of late, there has been increased concerns about the continued deterioration in the stability of the banking sector. Financial stability report of RBI confesses to the fact that the risks to Indian banking sector have been increasing in the post-recession period particularly the risk of accumulating NPAs. This study attempts to analyse the trend in profitability, NPAs, and the effectiveness of recovery mechanisms and interbank disparity in NPA management with respect to public sector banks. We found that the profitability of public sector banks is declining in the post-crisis period and the amount of NPA has been on the rise. Further, the recovery mechanisms have proved to be ineffective in containing the problem of bad debts.
Lead Lag Relationship between Futures and Spot Prices in Select Nifty Companies
The equity derivatives market in India has undergone remarkable changes in terms of instruments introduced. Introduction of single stock futures, amidst great misgivings, was solely responsible for placing Indian exchanges in the topmost position in the global scenario. Till 2006-07, single stock futures were the most traded instruments in the Indian equity derivative segment. But, post-Global Financial Crisis, there has been a continuous drift in favour of index options from single stock futures. There has been a continuous decline in the share of single stock futures, the gain being that of index options. This is considered as a clear indication towards mature stock market. Even though the inception of derivative trading has significantly influenced the trading volatility in the capital market segment, it is yet to be seen whether the introduction of derivatives has achieved its purpose or not. The present study is an attempt to study the impact of volatility on the stock market after the introduction of derivatives in Indian segment. The study takes into account a period of thirteen years, from 9th November 2001 to 31st March 2014. A bunch of Nifty companies which satisfy the set criteria are selected for the study. The study reveals that there exists causality between the futures and spot prices of these companies. These companies are found to be co-integrated in the long run as well as in the short run.
Examining the Fisher Effect in Short and Long Run: A Study of NSE Sectoral Indices
The belief that stock market provides hedge against inflation has been put to test by many researchers over the past few decades. The present study aims at testing the Fisher effect in the Indian context. We have used monthly data, from July 2006 to June 2016, of the National Stock Exchange sectoral indices and consumer price index. The ordinary least square regression and Johansen cointegration approach have been used to test whether or not Indian sectoral indices provide hedge against inflation in short and long run respectively. The weak exogenity test under VECM has been used to establish the hedge hypothesis in the Indian stock market. The present study has established results in support to the hedge hypothesis that stock market provides hedge against inflation.
Do IPOs in Cold Markets Provide Better Returns
Significant listing day returns for IPOs is a phenomenon that is observed when companies go public. Using a larger timeframe (1999-2014), we attempt to determine the long-run performance of underpriced IPOs issued in an emerging economy such as India during the hot and cold IPO markets for 36-months. The results indicate that IPOs perform significantly better when issued during cold markets. We find that the distribution of returns is the same across cold and hot markets at specific periods during the 36-month period of study.
An Empirical Analysis of Foreign Exchange Exposure of CNX 100 Companies
The present study has empirically examined the level of foreign exchange exposure and its determinants of CNX 100 companies. For the purpose of study, the relationship between exchange rate changes and stock returns for a sample of 82 companies was determined for the period April 2011-March 2016. The study finds that 49% of the sample companies had significant positive foreign exchange rate exposure and the found that the companies could be exporters or net importers. To explore factors determining foreign exchange rate exposure, variables such as export ratio, import ratio, size of a company, hedging activities were regressed against the exchange exposure and the study found that none of the factors was influencing the exchange rate exposure. The study concludes that the reasons for insignificant influence of the variables could be the natural hedging practices of companies, offsetting of exports and imports and heterogeneous of the sample size. The study offers few directions for future research in this area.
Liquidity Gap Report for Stress Testing Structural Liquidity Risk
The need to focus on banks funding structure and stress testing in an explicit way arose as a consequence of the crisis of past decades. Liquidity risks usually occur as a consequence of other kinds of risks, hence analysing scenarios in a prospective manner is essential for the assessment if the bank can fulfill its obligations as they come due and if its funding costs are appropriate. The structural liquidity risk and the degree of the liquidity mismatch can be measured based on the liquidity gap analysis, where expected cash-in- and outflows, divided in different time-buckets are depicted. The liquidity gap report (LGR) shows if a liquidity shortcoming appears in the future and how high is the amount a bank would have to pay, if any hedging were not possible. This paper shows how to build a comprehensive LGR which is the base for both, liquidity and wealth risk evaluation. To improve the accuracy of the forecast, the counterbalancing capacity will be incorporated into the LGR. This tool is a methodological basis for quantitative and qualitative risk assessment and stress testing.
Financial Factors Determining CAREs Ratings
Rating agencies evaluate a number of qualitative and quantitative factors while assigning rating to a particular company. Standard mathematical formulas do not exist for determining credit ratings. Instead, credit rating agencies use their experience and judgement in assigning ratings. What factors rating agencies consider significant in providing ratings to the companies is an important question. The present study aims to contribute to the above mentioned area by identifying the financial determinants of credit ratings assigned to Indian companies by CARE, one of the top rating agencies of India. Ordered probit analysis is used on unbalanced panel data with credit rating as the dependent categorical variable and six financial factors viz. size, liquidity, profitability, interest coverage, leverage, and growth as the independent variables. Results from ordered probit analysis indicate that the likelihood of credit ratings to be on higher side is more with increase of size, liquidity, profitability, interest coverage, growth and with a decrease in leverage. Further, size, profitability, and leverage are found to be statistically significant factors at the 1% level, liquidity and growth at the 5% level and interest coverage at the 10% level.
Determinants of Investment Decision Making: An Empirical Study
India as a developing country is becoming economically more powerful and requires huge capital for various developmental activities. In order to boost the investment among individual investors, it is necessary to study the investment behaviour of individuals and identify the factors that motivate them to invest, so that idle savings can be channelised into investment. Investment decisions are influenced by many reasons. It is a tolerable fact that the financiers are the central position in the financial market. Behaviour of investors is not fixed. It changes from position to position and from security to security. Hence, it is necessary to identify the factors which influence the investment decisions. In order to increase investment and formulate appropriate theories and policies, it is necessary to understand how individuals invest in the securities and other financial options available.
An Examination of Asymmetric Relation between Implied Volatility Index and Its Underlying Asset
The volatility index is the measure of 30-day expected volatility. Its association with stock index returns provides an insight to the volatility traders to launch derivatives products so that it can be used as a hedging tool. The aim of the present study is to empirically examine the relationship between the implied volatility indices and its underlying asset in context of developed and developing markets (like U.S., Japan, Germany, and China). The empirical findings report the asymmetric behaviour which indicates that a larger impact on implied volatility indices are from negative return shocks as compared to positive returns. This evinced that the investors and traders respond highly to negative returns in low volatile period by demanding more options at high premium which makes the implied volatility high. Therefore, the negative relationship between IVIX and stock index returns makes the index relevant for investors to diversifying their portfolio so that they can mitigate the investment risk associated with the volatility.
Relationship between Foreign Portfolio Investments (FPI), Domestic Institutional Investors, and Stock Market Returns in India
The present article attempts to understand the relationship between foreign portfolio investment (FPI), domestic institutional investors (DIIs), and stock market returns in India using high frequency data. The study analyses the trading strategies of FPIs, DIIs and its impact on the stock market return. We found that the trading strategies of FIIs and DIIs differ in Indian stock market. While FIIs follow positive feedback trading strategy, DIIs pursue the strategy of negative feedback trading which was more pronounced during the crisis. Further, there is negative relationship between FPI flows and DII flows. The results indicate the importance of developing strong domestic institutional investors to counteract the destabilising nature FIIs, particularly during turbulent times.
Integration of Stock Market – Evidence from India and Major Global Indices
In designing portfolio diversification plays an important role and diversifying into international market is one of important ingredient in it. High integration among the markets across the globe however also have its own risk of spillover effect of one country into another geography which will have cascading effect across entire globe. For this study has been done to identify interdependency among ten indices of market spread across Asia, Europe and America. The study has been done by measuring co-integration among various indices and also determining causality among the indices by Granger Causality. The study reveals to large extent presence of strong dependency across various markets. Among the indices studies SHANGAI from China showed low dependency across various geographies.
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