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Rastogi, Shailesh
- Long-Term Association in Time Series and Simultaneous Equation Modelling:A Case Study
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Authors
Affiliations
1 Symbiosis Institute of Business Management, Pune – 412115, Maharashtra, IN
1 Symbiosis Institute of Business Management, Pune – 412115, Maharashtra, IN
Source
SAMVAD: International Journal of Management, Vol 17 (2019), Pagination: 46-64Abstract
Simultaneity (Endogeneity) is a normal phenomenon observed in financial data. Modelling of more than one endogenous variable in a single equation using OLS (Optimum Lead Square) is faulty due to the violation of the assumptions of OLS estimator. Therefore, systems of equation (Simultaneous equation modelling) is used instead to OLS. Two stage least square (TSLS) or Generalized method of moments (GMM) is used to estimate systems of equation. This case study highlights the usage of TSLS to estimate systems of equations.
Keywords
Call, Futures, Put, TSLS, VolatilityFull Text
References
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- Rastogi, S., & Athaley, C. (2019). Volatility Integration in Spot, Futures and Options Markets: A Regulatory Perspective. Journal of Risk and Financial Management, 12(2), 1-16
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- Long-term Association in Time-Series through Cointegration Analysis: A Case Study
Abstract Views :207 |
PDF Views:95
Authors
Affiliations
1 SIBM Pune, Symbiosis International University, Pune, IN
1 SIBM Pune, Symbiosis International University, Pune, IN
Source
SAMVAD: International Journal of Management, Vol 18, No SP (2019), Pagination: 25-28Abstract
The association among variables, especially when endogeneity is not defined, can be modelled using Optimum Least Square. In the case of endogeneity, Two Stage Least Square Method (TSLS) can be deployed. However, presence of Cointegration can jeopardise the existing association among the variables in both the cases. Even if, either Optimum Least Square (OLS) or TSLS can be estimated but the estimated coefficients in the presence of Cointegration will not be appropriate and may be misleading. Testing of cointegration is done by any of the three methods, which is further elaborated by Error Correction Models (ECM) to explore the nature of Cointegration relation.Keywords
Cointegration, Endogeneity, Error Correction Model (ECM), Stationarity, Vector Auto Regression (VAR).Full Text
References
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- Factors Accountable for Non-Participation in the Stock Market: Identification and Ranking
Abstract Views :112 |
PDF Views:62
Authors
Affiliations
1 Assistant Professor, Symbiosis Institute of Business Management, Symbiosis International (Deemed University), Pune, IN
2 Ph.D. Scholar, Symbiosis International (Deemed University) Pune, IN
3 Professor, Symbiosis Institute of Business Management, Symbiosis International (Deemed University), IN
1 Assistant Professor, Symbiosis Institute of Business Management, Symbiosis International (Deemed University), Pune, IN
2 Ph.D. Scholar, Symbiosis International (Deemed University) Pune, IN
3 Professor, Symbiosis Institute of Business Management, Symbiosis International (Deemed University), IN
Source
SAMVAD: International Journal of Management, Vol 23, No 0 (2021), Pagination: 50-64Abstract
Non-Participation in the Stock (NPS) market is a serious concern especially with the rising burden of debt in general and NPA in particular in the Indian economy. This paper is an attempt to address the problem of NPS. Identification of factors accountable for NPS is the first step to resolve the problem. Ranking is obviously the second step so that the problem can be resolved in the sequential manner. The current study identifies: willingness to invest, cash availability, knowledge of the equity market, expectation of returns, trust on the market and risk in the market. The factors are delineated in the order of the priority. Willingness to invest in the stock market come out to be more important reason for NPS and risk in the market happens to be the least important factor in the pecking order of factors for NPS. A multi-criteria decision making tool, Analytical Hierarchical Process (AHP) is applied to set the identified factors into the order of their relevance for NPS. The findings of the study have unique attributes in terms of newer set of factors and the method of ranking them. The relevant factors for NPS identified in the current study can be responded with the appropriate change or revision in the guidelines and policies to address the problem of NPS. Moreover, one of the major implications of the study is that the factors can be taken care of in the step wise manner as compared to taking up all at the same time.Keywords
Analytical Hierarchical Process (AHP), Equity Market, Factor Analysis, Investors, Mutual Funds.Full Text
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