Abstract
. Time- series data of 36 years was used, from year 1980 to 2016. For seizing the impact of Exchange rates on Returns in Share Market: A Case of Pakistan, a theory based model, consisting of six submodels is planned with intention to estimate through Recursive Simultaneous-equations econometric estimation technique. Since, the data is time series, the Augmented Dickey-fuller (ADF) tests were used to assess the stationary of the considered variables. The study used autoregressive distributed lag (ARDL) model because some of the study’s variables were found at different levels, such as I(0) and I(1). The results of bounds tests specify that the value of F-statistics is 5.545058, indicating that long-run relationships exist in variables. The results of the approach revealed that Exchange rate has a positive significant influence on Share Market Returns.The results of the approach revealed that Foreign Portfolio Investment (FPI) has a positive significant influence on Share Market Returns with the value of 0.284864 with a ƿ-val of 0.0008. The result also demonstrates that National Savings (NS) has a positive and significant association with Share Market Returns (SMR) with the value of 0.843564 with the ƿ-val of 0.0000. Outcomes of the study also exemplify that (NI) has a positive and significant influence on SMR with the value of 3.039655 with a ƿ-val of 0.0067. This thesis has encompassed well-expanded details and estimation techniques of the various estimation models and measures needed in this type of research, especially when using time-series data. Based on research findings, it was suggested that, using this research as a guiding base, potential researchers should reproduce this research for achieving a better and relatively well-conceived, well-estimated model on the topic; it was further recommended that public and private sector planners and researchers take guidance, not only on the statistically significant exogenous variables but also of the other explanatory variables for their effects on the endogenous variables.
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