ISSN: 2225-8329
Open access
The agriculture sector of Pakistan is regarded as the backbone of the economy as it contributes towards the country's GDP 21.40 percent, where, around 65 percent of the country’s population is involved either direct or indirect. However, little has been researched, mainly focusing on the stock returns behavior during different political parties and caretaker government (CTG) power regimes. The study empirically investigated the issue by applying exploratory data analysis techniques to daily stock returns of Agri-tractor manufacturer companies (i.e. possess 99% market share) listed at the Pakistan Stock Exchange. The study covers seven different power regimes that include four mainstream political parties and three CTGs, starting from 23rd November 2002 to 31st May 2019. Comparing stocks return performance of Pakistan Tehreek-e-Insaaf (PTI) power regime seems to be biased as it is a relatively new political party who the first time is leading the country in its lifetime compared to its counterparts. Moreover, it still has left with its remaining four years to be in power. However, the stock return performances during the PTI power regime show more resemblance to the CTGs than the mainstream political parties. Overall, extreme fluctuation has been observed in Agri-tractor manufacturer companies stocks return during all major political parties' power regimes except PTI. If ranked, the PML-Q could be placed on the high returns’ volatility side and PML-N on the low-volatility, whereas PPP in the mid. However, the variations are minor among the regimes in the context of stock return fluctuations. The study can help investor in their portfolio construction process and may have better returns if they pay attention to these political dynamics.
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To cite this article: Saleem, H. M. N., Ahmad-Zaluki, N. A. (2020). Stock Returns’ Behavior in Different Power Regimes: An Exploratory Data Analysis of Agri-Tractor Manufacturers, International Journal of Academic Research in Accounting, Finance and Management Sciences 10 (1): 297-307.
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