Dec '2020


The IUP Journal of Financial Risk Management

ISSN: 0972-916X

A 'peer reviewed' journal indexed on Cabell's Directory, and also distributed by EBSCO and Proquest Database

It is a quarterly journal that focuses on identifying Financial risk in Capital/Debt/Forex markets and their management models; Derivatives as Price Discovery Tools and Hedging devices; Hedging techniques; Asset-liability management; Organizational culture, Risk-bearing capacity and Leadership role in management of risk. The journal provides a platform for cutting-edge research in the field of financial risk management.

Privileged access to Online edition for Subscribers.

Focus Areas
  • Identifying Financial Risk
  • Risk Management Models
  • Accounting for Derivatives
  • Risk-Hedging Techniques
  • Asset Liability Management
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Article   Price (₹) Buy
A Comparative Analysis of Capital Asset Pricing Model and Arbitrage Pricing Theory in the Indian Stock Market Using Davidson-MacKinnon Equation
50
Decomposing Rating Migration Matrices from Market Prices: Sources of Nonlinearity and Resolve
50
Rainfall Forecasting Announcement and Commodity Spot Price Fluctuation: Evidence from Six Selected Food Commodities with Reference to Indian Commodity Market
50
The Impact of Herd Mentality and Pain of Regret Bias on Investment Decisions
50
     
Contents : (Dec '20)

A Comparative Analysis of Capital Asset Pricing Model and Arbitrage Pricing Theory in the Indian Stock Market Using Davidson-MacKinnon Equation
Shikha Menani

Capital Asset Pricing Model (CAPM) and Arbitrage Pricing Theory (APT) are the two models that assess the risk-return relationship and help in the stock and/or portfolio evaluation. The two models, however, differ in the way factors are priced in the return-generating process. While the CAPM considers a single factor, that is beta, being the determinant of the cross-sectional differences in the asset pricing, APT considers various macroeconomic factors that determine the asset prices. The present study has used Davidson-MacKinnon equation to compare the two models using 221 securities listed on the Indian stock market, covering the period January 2000 to December 2018. The results favor the single-factor model, i.e., CAPM, wherein the additional factors propounded by APT had not improved the explanatory power of the risk-return relationship for the study period.


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Article Price : ? 50

Decomposing Rating Migration Matrices from Market Prices: Sources of Nonlinearity and Resolve
Brian Barnard

This study, a part of a larger work on decomposing rating migration matrices from market prices, investigates the matter of the associated optimization problem, in plain form, yielding multiple possible local solutions. The sources of nonlinearity and complexity of the optimization problem are outlined. This includes the rating category migration variance results of solutions, in terms of values and spacing, and within matrix rating category structures. Plain optimization problem decompositions struggle to surface, and correct both rating category migration variance values and spacing, and rating category matrix structures. Generally, full matrix decompositions require good initial solutions to yield good results. Matrix averaging and matrix sampling are considered. Matrix averaging is based on limited coefficient counts or sets-not using the full coefficient count, but rather grouping coefficients. Matrix sampling forms an approximation of the matrix, in a sense through parsimony. Matrix averaging represents simple(r) optimization problems, and offers easy solutions, with good results and information, but offers poor initial solutions for full matrix decomposition. Matrix sampling can offer good indications, and good initial solutions for full matrix decomposition. Full matrix decomposition from initial solutions sourced through matrix sampling offers good results. Overall, revisiting and re-examining the way that the optimization algorithm searches optimal solutions based on the initial solution provided, can further improve decomposition results.


© 2020 IUP. All Rights Reserved.

Article Price : ? 50

Rainfall Forecasting Announcement and Commodity Spot Price Fluctuation: Evidence from Six Selected Food Commodities with Reference to Indian Commodity Market
Mohd Merajuddin Inamdar, Susanta Datta and Vinayak Karande

The paper evaluates the impact of rainfall forecast announcement on six selected commodity spot price fluctuation with reference to Indian commodity market. Using daily spot price data from January 2, 2017 to December 13, 2017, four research questions have been addressed by considering two rainfall forecasting announcement dates, April 18, 2017 and June 6, 2017, by the Indian Meteorological Department, Government of India. By adopting dummy regression, Bai-Perron (2003) multiple structural break point tests and lagged regression, the empirical results suggest that rainfall forecasting announcement is a very temporary phenomenon and there is no strong evidence of fluctuations in return on commodity spot prices. This observation is also supported by ARIMA modeling, where it has been found that the return on spot price fluctuation behavior can be explained better with the help of lower order moving average models like MA1, MA2, etc. The results are statistically parsimonious because they are consistent with the real-life fact that agriculture product pricing is subject to the matter of seasonality which can persist for a short span of time, and this observation has been supported by the finding from lagged regression that lag 1 is significant at 1% level in maximum cases. The policy suggestions are that there is a need to introduce weather derivatives in Indian market to hedge risk due to weather variability and the meteorological department should improve its penetration of information among traders and farmers to achieve price efficiency.


© 2020 IUP. All Rights Reserved.

Article Price : ? 50

The Impact of Herd Mentality and Pain of Regret Bias on Investment Decisions
Priya Angle and Sasmita Giri

This paper examines how the herd mentality and regret bias of investors impact their investment decisions. Primary data was collected from employees, stock brokers, students and others who are either active investors in the stock market or following it regularly. The questionnaire is divided into two parts, consisting of demographical questions and technical questions on herd mentality and regret bias. Regression analysis and descriptive analysis were done on the data. The approach of this study is different as it uses situation-based questions and demographics to find out how their affect the investor's biases.


© 2020 IUP. All Rights Reserved.

Article Price : ? 50

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