Tanupa Chakraborty

Bio: Tanupa Chakraborty is an academic researcher from University of Calcutta. The author has contributed to research in topics: Risk management & Financial market. The author has an hindex of 2, co-authored 8 publications receiving 12 citations.

Foreign Portfolio Investment and Stock Market Volatility in India

Abstract: Although, it is a generally held belief that foreign portfolio flows benefit the economies of recipient countries, policy-makers worldwide have perennial discomfort about such investments. Such portfolio flows are widely termed as "hot money," given its notorious volatility compared to other forms of capital flows as foreign investors make sudden and concerted withdrawals of portfolio investments at the faintest smell of trouble in the host country, thereby accelerating and magnifying the inconspicuous problem of the downfall in stock prices, often leading to disastrous consequences to the host economy. The discussion is often emphasized by the financial press due to the visible evidence of their contemporaneous nature at times of economic crisis. Relationship between foreign institutional ownership and volatility is largely inconclusive. Although the literature in business newspapers and also some previous empirical studies suggest that institutions tend to destabilize prices by increasing turnover levels, there are some good reasons to believe that higher levels of institutional ownership could be negatively related to volatility. In this present study, using firm-level Indian panel data from 2003 to 2013, we analyzed the association between stock's return volatility and their FII holdings in a VAR framework. The results showed that no significant causal relationship exists between the two variables.

Perceptions of Bankers and Researchers Towards Effectiveness of Basel Norms in Banking Risk Management: A Survey

Abstract: Basel norms are designed to ensure safety and stability of the banking system at an international level. The norms were introduced in 1988 in the name of Basel I, which through subsequent and continuous modification has now taken the shape of Basel III. Indian banks being internationally active, are well preparing themselves to comply with the new Basel III norms. The paper tries to collect and investigate the views of bankers, researchers and experts in the field of banking risk management about the effectiveness of Basel norms for risk management in Indian banking industry.

The Relationship Between Fair Values in Banks’ Trading Books and Volatility in Share Price Returns in the Indian Context

Abstract: ‘Fair value’ of an asset or a liability refers to the amount at which such an asset could be exchanged, or the liability settled, between knowledgeable, willing parties, in an arm’s length transaction. Although the growing irrelevance of historical cost-based accounting numbers in the financial statements, in the wake of developments in financial markets and advancements in technology, has triggered off the debate on fair value accounting a decade and a half ago, some issues still stand in the way of extensive application of fair value accounting framework. One such issue is the excessive level of volatility in the financial statements induced by fair valuations and its resultant impact on the flight of capital from the firm’s equity. In accordance with the series of guidelines issued by the Reserve Bank of India between 1995-2000, fair value accounting has been applied only on the ‘held for trading’ securities in banks’ investment portfolio in India till today. Accordingly, this research paper makes a modest attempt to examine whether fair valuations in banks’ trading books bring about an increased volatility in banks’ stock returns over the time period 1994-1995 to 2007-2008, using a sample of Indian banks and bank index, i.e., BSE BANKEX, and autoregressive and multiple linear regression techniques.

Weather risk assessment of Indian power sector: A conditional value-at-risk approach:

Abstract: This paper aims to assess the weather risk exposure of Indian power sector from both generation and demand sides. The study considers two representative firms – firstly, Damodar Valley Corporation ...

Asset Liability Management in Commercial Banks in India

Abstract: Globalization and liberalization of the Indian economy has brought many changes in the Indian financial markets. There is an increase in the level of competition in the financial market due to deregulation of interest rate, technological and operational reforms. The Indian banking sector is facing a variety of risks such as credit risk, capital risk, market risk, interest rate risk and liquidity risk etc. The nature and magnitude of these risks have changed over time and it is very important to understand and control these risks as they directly affect the bank’s efficiency and profitability. Banks have come up with new methods and techniques to measure and control these risks. Asset-Liability Management (ALM) is one such important technique which is now widely being applied in the banks. ALM is a mechanism to address the risk faced by banks due to mismatch in assets and liabilities It is a comprehensive and dynamic method for measuring, monitoring and managing the various risks of a bank. It involves identification of risk parameters, risk measurement and management and framing of risk policies and tolerance levels. This study is undertaken to understand the concept of ALM and application of ALM in Commercial Banks in India.

Taming financial capital : the role and limitation of Basel Capital Regulation in Pakistan

Abstract: The study investigates the role of International Basel Capital Regulation in taming the financial capital via improving risk management in banking. The study examines if capital adequacy ratios of commercial banks calculated under Basel Capital Accord reflect credit risk, market risk, operational risk, liquidity risk, and economic impact in Pakistan. The study employed dual methodology utilising both primary and secondary data. A Liker-scale questionnaire was administered in addition to deploying panel data approach. The results of the study show that Credit risk and operational risk along with the size of bank and bank profitability show significant impact on capital requirements of the commercial banks of Pakistan. Credit risk showing significant negative relationship with the capital adequacy ratio of the commercial banks of Pakistan.

MERC Global's International Journal of Social Science & Management

Abstract: MERC Global's International Journal of Social Science & Management (MERC Global’s IJSSM) is an international, peer-reviewed, bimonthly journal of social science and management, being brought out for offering efficacious propagation of the latest reckoning and research pertaining to the various aspects of social science and management relevant for practitioners as well as for academicians & researchers working in the field of social science and management around the globe. MERC Global’s IJSSM publishes articles, research papers, abstracts of doctoral dissertations, book reviews, case studies, short communications and bibliography that are interdisciplinary in nature as well as those within the major disciplines i.e. Social Science and Management.

Canonical Correlation Analysis of Asset-Liability Management of Indian Banks

Abstract: The present study analyses asset-liability management in Indian banks using the methodology of Ranjan and Nallari (2004). The study covers all scheduled commercial banks except regional rural banks (RRBs), in the five-year period 2003-08. The banks are grouped on the basis of ownership structure: viz. public sector banks (including SBI & associates), private sector banks, and foreign banks.

Weather Derivative Valuation: The Meteorological, Statistical, Financial and Mathematical Foundations

Abstract: Read any paper in statistical meteorology or climatology since 1995 and you are nearly certain to find a citation of the first edition of this book (Wilks 1995). This is for good reason. The book is an excellent and complete introduction to applied statistics in the atmospheric sciences. The examples are all current, and the explanations of methods are transparently clear. The original has been used successfully as a textbook. The new edition contains many new topics, including density estimation, the bootstrap, and numerical methods in parameter fitting. Many of the examples are new, and there are several new problems at the end of each chapter. The most substantial additions come in the new Section 3, “Multivariate Statistics.” All of the standard topics are covered: a review of matrix algebra, multinomial distributions, principal components (called “empirical orthogonal functions” in meteorology), canonical correlation analysis, discrimination and classification, and cluster analysis. A regular, applied multivariate course could be (and has been) taught with this part of the book. Multidimensional statistics and massive datasets are meteorology nowadays, and this is the only book that presents a complete summary of the methods in common use. What makes this book specific to meteorology, and not just to applied statistics, are its extensive examples and two chapters on statistical forecasting and forecast evaluation. Most weather forecasts start as output from dynamical models, which are essentially enormous sets of partial differential equations and parameterizations that describe the physics of the atmosphere. The models are fed initial conditions, which are observations that go through a process called analysis that synchronizes the observations and model physics. Then the models are integrated forward in time. What comes out is a rough prediction of the future. Statistical models take these rough guesses and make them better. Naturally, there are many ways to do this, and many ways yet to be discovered. Wilks does a good job explaining what is known and what is not known. The newest twist in the forecast process, and one that recognizes the chaotic nature of the atmosphere, is called ensemble forecasting. The initial conditions are not without uncertainty, and so they are perturbed (in another complicated process of analysis) in such a way as to represent this uncertainty, and the dynamical models are rerun many times, each time with different perturbed initial conditions. The resulting ensemble of forecasts must be statistically postprocessed to produce (and display) a usable forecast. How to best do this is an open question, but again the book lays out the common strategies now in use. Once the forecasts (of any type) are in hand, they must be evaluated for accuracy using statistical methods. How to do this for point forecasts is now fairly well understood; the concepts of skill, proper probability forecasts, economic value, and graphical methods are all given here. But another big open question is how to do evaluation for multidimensional multivariate forecasts, a problem that few have yet tried to tackle, although some progress is being made. Actually, meteorologists have led the way in the statistical evaluation of predictions, and it would be wise for statisticians to take notice of these methods and begin to apply them routinely to their own models. For example, in how many applied papers in, say, sociology journals, can you recall that the model touted by the authors was actually verified and evaluated or just taken as finally proved (with an acceptably low p value)?

Response of stock market volatility to foreign equity investments

Abstract: This study evaluates the response of stock market volatility to foreign equity investments. Specifically, the study examines how foreign portfolio investment and foreign direct equity investment influence stock market volatility in Nigeria, using monthly data from January 2007 to July 2017. Results of preliminary analyses of stock market returns series show evidence of negative skewness, leptokurtosis, non-normal distribution, and average positive monthly return. Estimates from the GARCH-X (1,1) model show evidence of volatility clustering in the stock market returns. The estimates also show that stock market volatility responds to changes in foreign portfolio investment. On the other hand, changes in foreign direct equity investment do not influence stock market volatility. The key implication is for investors to adjust their portfolio to changes in the foreign portfolio investment, in order to mitigate stock market volatility, and for stock market regulators to encourage more inflow of foreign direct equity investment as a more stable source of foreign equity investment.