Shivaprasad S. P.
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Choosing the right options trading strategy: Risk-return trade-off and performance in different market conditions
Shivaprasad S. P. , Geetha E. , Raghavendra , Kishore L. , Rajeev Matha doi: http://dx.doi.org/10.21511/imfi.19(2).2022.04Investment Management and Financial Innovations Volume 19, 2022 Issue #2 pp. 37-50
Views: 1124 Downloads: 442 TO CITE АНОТАЦІЯThe investment decisions are subjected to risk and return of the financial asset. Options strategies help employ a suitable strategy to balance the risk-return trade-off. The study analyzes the risk-return trade-off of the long straddle, long strangle, long call butterfly (LCB), short straddle, short strangle, and short call butterfly (SCB) strategies. Moreover, it measures the impact of strategy risk and options premiums on strategy return using panel data analysis. Additionally, the study evaluates the performance of options strategies using the excess returns to risk approach under neutral and volatile market conditions. This paper considered companies of top-six sector indices of the National Stock Exchange from 2009 to 2020 and collected data of 18,720 option contracts and 3,744 observations for each strategy (22,464 observations). The study revealed that risks of long straddle and long strangle strategies have a positive impact, and options premiums negatively influence their payoff. ATM call premiums positively affect LCB payoff, while OTM and ITM call premiums positively influence SCB payoff. However, the risks of butterfly strategy did not influence its payoff. The risk of short straddle and short strangle strategies negatively influenced the payoff and were considered riskier strategies. Moreover, short straddle and short strangle strategies enhanced excess returns under both market conditions. The results would help the investors in choosing the appropriate strategy by analyzing the impact of risk on the payoff and the ability to enhance excess returns to the risk of various options strategies to incorporate in their investment.
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Role of big-five personality traits in predicting behavioral intention: A case of Indian corporate bond investors
Rajeev Matha , Geetha E. , Raghavendra , Kishore L. , Shivaprasad S. P. doi: http://dx.doi.org/10.21511/ppm.20(4).2022.48Problems and Perspectives in Management Volume 20, 2022 Issue #4 pp. 638-652
Views: 517 Downloads: 139 TO CITE АНОТАЦІЯPersonality traits are qualities that make a person distinctive and describe stable behavior patterns. Therefore, understanding the influence of personality traits on behavioral intention will help predict investors’ investment decisions. This study aims to assess the impact of personality traits, i.e., openness to experience, neuroticism, conscientiousness, agreeableness, and extraversion, on investors’ behavioral intentions. Moreover, it assesses the mediating effect of attitude, subjective norms, and perceived behavioral control between investors’ personality traits and behavioral intention. The study employed a structured questionnaire on a sample of 413 retail investors. Further, obtained data were empirically examined on Smart-PLS 3.3 using the PLS-SEM method. The study found that perceived behavioral control, subjective norms, and attitude positively affected behavioral intention. However, the personality traits did not influence the intention directly. Further, mediation analysis revealed that attitude and subjective norm fully mediated the relationship between extraversion, neuroticism, openness, and intention. In contrast, attitude and subjective norms did not exhibit a mediating relationship between agreeableness, conscientiousness, and intention. Finally, perceived behavioral control fully mediated the relationship between personality traits and intention, except for conscientiousness. The study contributes by extending the applicability of the theory of planned behavior by examining the impact of big-five personality traits on behavioral intention and mediating the role of the theory of planned behavior’s dimension between personality traits and intention.
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