Jose Thoppan

Saintgits Institute of Management, Management, Faculty Member

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Papers by Jose Thoppan

A Method to Select Best Among Multi-Nash Equilibria

Studies in Microeconomics, 2021

A non-zero sum bimatrix game may yield numerous Nash equilibrium solutions while solving the game... more A non-zero sum bimatrix game may yield numerous Nash equilibrium solutions while solving the game. The selection of a good Nash equilibrium from among the many options poses a dilemma. In this article, three methods have been proposed to select a good Nash equilibrium. The first approach identifies the most payoff-dominant Nash equilibrium, while the second method selects the most risk-dominant Nash equilibrium. The third method combines risk dominance and payoff dominance by giving due weights to the two criteria. A sensitivity analysis is performed by changing the relative weights of criteria to check its effect on the ranks of the multiple Nash equilibria, infusing more confidence in deciding the best Nash equilibrium. JEL Codes: C7, C72, D81

The Worrying Trend of Non-performing Loans in Higher Education

Developing an Effective Model for Detecting Trade-based Market Manipulation

Center. Any opinions expressed in the chapters are those of the authors. Whilst Emerald makes eve... more Center. Any opinions expressed in the chapters are those of the authors. Whilst Emerald makes every effort to ensure the quality and accuracy of its content, Emerald makes no representation implied or otherwise, as to the chapters' suitability and application and disclaims any warranties, express or implied, to their use.

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Impact of Improved Corporate Governance and Regulations on Earnings Management Practices—Analysis of 7 Industries from the Indian National Stock Exchange

Journal of Risk and Financial Management, 2021

This study investigates discretionary earnings management practices, tracing the changes over the... more This study investigates discretionary earnings management practices, tracing the changes over the years in selected top performing and highly liquid listed Indian firms. It empirically measures the impact of corporate governance, financial legislation and global reporting standards on the firms’ earnings management practices. The study analyses a sample of 712 firm-year data comprising 89 listed Indian companies across 7 different sectoral indices of the National Stock Exchange of India (NSE) over 8 years (2011–2018). The Modified Jones model was used to compute Discretionary Accruals to measure Earnings Management based on data obtained using Bloomberg terminals. Statistical results and plots generated in Stata offer evidence that instances of earnings management have significantly reduced after the enactment of the Companies Act 2013 and the adoption of Indian Accounting standards which are converged with the IFRS. Findings suggest that services firms are engaging in relatively hi...

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Pricing strategies in the era of digitalisation and the perceived shift in consumer behaviour of youth in Poland

Journal of International Studies, 2019

The advent of industry 4.0 along with the spread of Information and Communication Technology has ... more The advent of industry 4.0 along with the spread of Information and Communication Technology has brought about many pivotal changes in the E-Commerce segment. Technology driven pricing strategies like dynamic pricing has become very common across different industries all over the world. Today, online pricing has evolved into a very efficient and sophisticated pricing strategy where product prices are personalised and tailored to the last conceivable individual buying unit possessing similar characteristics. This study examines various traits exhibited by online consumers in a dynamic pricing environment and figure out the reasons for the display of strategic purchase behaviour by the consumers in response to the dynamic pricing strategy adopted by the sellers. The study was conducted among the Polish millennials as Poland has the median online market size and growth rate among the Central and Eastern European

format_quoteStudy identifies factors influencing strategic purchase behavior, including fair price perception and shopping experience.format_quote

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Factors Influencing Consumer Behavior and Prospective Purchase Decisions in a Dynamic Pricing Environment—An Exploratory Factor Analysis Approach

Social Sciences, 2018

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Detection of Stock Price Manipulation Using Discriminant Analysis

SSRN Electronic Journal, 2012

This paper seeks to define a model based on discriminant analysis to categorize a stock as manipu... more This paper seeks to define a model based on discriminant analysis to categorize a stock as manipulated or non-manipulated based on certain key variables that capture the characteristics of the stock. The model helps identify stocks witnessing activities that are indicative of potential manipulation irrespective of the type of manipulation – action-based, information-based or trade-based. The proposed model helps investigators to arrive at a shortlist of securities that are potentially manipulated and which could be subject to further detailed investigation to detect the type and nature of the manipulation, if any. In a market like India, where there are about 5000 plus securities listed on its major exchanges, it becomes extremely difficult to monitor all securities for potential market abuse. Authors who have earlier used discriminant analysis have used the Linear Classification Function without validating the assumption that governs the model. In this paper we have tested the assumption on data from the Indian capital market and have found that the data does not comply with the assumptions that govern the use of the linear classification function. This resulted in us using the Quadratic Classification Function, which is the appropriate technique for instances where the data does not meet the sated assumptions, to categorise stocks into two categories, namely manipulated and non-manipulated.

Market manipulation and surveillance - a survey of literature and some practical implications

International Journal of Value Chain Management, 2013

Price discovery is the central element of a capital market value chain. Market surveillance becom... more Price discovery is the central element of a capital market value chain. Market surveillance becomes a necessity when any deliberate attempt is made at disrupting a free and fair mechanism for price discovery in a stock market. These attempts may be aimed at creating false and misleading signals with respect to the price or demand for a stock or both. This paper reviews the literature on: 1) efficiency and integrity of markets; 2) theoretical, empirical and experimental literature on manipulation; 3) surveillance systems and techniques.

ANN‐GA based model for stock market surveillance

Journal of Financial Crime, 2012

Purpose-This paper attempts to develop a hybrid model using advanced data mining techniques for t... more Purpose-This paper attempts to develop a hybrid model using advanced data mining techniques for the detection of Stock Price Manipulation. The hybrid model detailed in this article elucidates the application of a Genetic Algorithm based Artificial Neural Network to classify stocks witnessing activities that are suggestive of potential manipulation. Design/methodology/approach-Price, volume and volatility are used as the variables for this model to capture the characteristics of stocks. An empirical analysis of this model is carried out to evaluate its ability to predict stock price manipulation in one of the largest emerging markets-India, which has a large number of securities and significant trading volumes. Further, the article compares the performance of this hybrid model with a conventional standalone model based on Quadratic Discreminant Function (QDF). Findings-Based on the results obtained, the superiority of the hybrid model over the conventional model in its ability to predict manipulation in stock prices has been established. Research limitations/implications-The classification by the proposed model is agnostic of the type of manipulation-action-based, information-based or trade-based. Practical implications-The market regulators can use these techniques to ensure that sufficient deterrents are in place to identify a manipulator in their market. This helps them carry out their primary function, namely, investor protection. These models will help effective monitoring for abnormal market activities and detect market manipulation. Social implications-Implementing this model at a regulator or SRO helps in strengthening the integrity and safety of the market. This strengthens investor confidence and hence participation, as the investors are made aware that the regulators implementing market manipulation detection techniques ensure that the markets they monitor are secure and protects investor interest. Originality/value-This is the first time a hybrid model has been used to detect market manipulation.

format_quoteThe study utilized data from 29 companies, 14 known manipulated, showcasing the model's real-world application in identifying manipulation.format_quote

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Detection of stock price manipulation using quadratic discriminant analysis

International Journal of Financial Services Management, 2012

In this paper, we use a discriminant analysis (DA) based model to identify stocks that are potent... more In this paper, we use a discriminant analysis (DA) based model to identify stocks that are potentially manipulated. Earlier researchers have used Linear Discriminant Function (LDF), a type of DA, without validating the assumption governing the model. We tested the assumptions on data from the Indian capital market and found that the assumptions do not hold good. We identified the Quadratic Discriminant Function (QDF) as the appropriate DA based classification technique for instances where the data does not meet the stated assumptions of LDF. We developed the LDF Classifier equation using key market data variables that capture the characteristics of the stock. In a market like India, where there are about 5000-plus listed securities, it becomes extremely difficult to monitor all for potential market abuse. The proposed model helps investigators to arrive at a shortlist of potentially manipulated securities which could then be subject to further detailed investigation, if required.

Competitive Models to Detect Stock Manipulation

Communications of the IIMA

In this paper, data from the Indian stock market is used to study the prediction accuracy of vari... more In this paper, data from the Indian stock market is used to study the prediction accuracy of various classification techniques that can be used to identify market manipulation. The data contains information regarding price, volume and volatility of various stocks. Techniques like discriminant analysis, a composite model based on artificial neural networkgenetic algorithm (ann-ga) and support vector machine (svm) have been used for classifying stocks into manipulated and non manipulated categories. It is observed that the support vector machine based technique gives the best classification accuracy among the three techniques.

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Factors Influencing Consumer Behavior and Prospective Purchase Decisions in a Dynamic Pricing Environment-An Exploratory Factor Analysis Approach

by Vijay Victor, Jose Thoppan, Robert Nathan, and Maria Farkasné Fekete

MDPI, 2018

The rapid advancements in information and communication technology during the third industrial re... more The rapid advancements in information and communication technology during the third industrial revolution of the late 20th century has marked the beginning of a new era in the retail sector with the introduction of E-commerce. The dawn of the new century witnessed industry 4.0, revolutionizing all areas of online business by bringing in novel opportunities and possibilities. Despite the progress in technology, the determination of correct pricing on online selling platforms still remains a very complex task. The adoption of big data technology has enabled online sellers to make real-time price changes of high magnitude and proximity. However, with increasing awareness among buyers regarding modern pricing strategies, it is necessary to examine probable changes in consumer behavior when exposed to dynamic pricing scenarios. This study investigates the factors that influence consumer behavior, and their prospective online purchase decisions in a dynamic pricing context, through an exploratory factor analysis approach. A primary research survey was conducted, and 178 samples were finalized for data analysis through a series of web surveys completed by respondents in India. This study identifies, measures and classifies 27 research items into variables, namely shopping experience, privacy concerns, awareness about dynamic pricing, buying strategy, fair price perceptions, reprisal intentions and intentions for self-protection. These seven factors could be used to explain consumer behavior in a dynamic pricing situation.

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