The purpose of this study is to investigate the herding behaviour in Pakistan Stock Exchange with the primary focus on herding sector-wise. Daily and monthly data from January 2008 to December 2019 of 12 sectors namely “Automobile assembler, Cement, Chemical, Fertilizer, Paper and Board, Power Generation & Distribution, Refinery, Sugar & Allied Industries, Textile Composite, Textile Spinning, Textile Weaving and Tobacco” have been utilized for the study. Two models i.e. Cross Sectional Standard Deviation (CSSD) proposed by Christie & Huang (1995) and Cross Sectional Absolute Deviation (CSAD) proposed by Chang et al. (2000) were used to find the existence of herding. Different scenarios are used in order to explore the possibility of herding in the Pakistani stock exchange. Results indicate that during extreme market movements and during non-linearity, no evidence of herding has been found in any sector. Furthermore, during the bullish market conditions, herding exists in the sectors Fertilizers, Paper & Bonds, Power Generation & Distribution, Refiner y, Sugar & Allied Industries and Textile Spinning by using daily returns, however, by using the monthly returns, herding exists in the sectors Fertilizers, Paper & Bonds, Power Generation & Distribution, Textile Weaving and Tobacco. During bearish market conditions, by using daily and monthly data, herding exists in Textile Spinning, Tobacco and Sugar & Allied Industries respectively. During high volatility state, by using daily data, herding exists in the sectors Paper & Bond, Power Generation & Distribution, Textile Spinning, Textile Weaving and Tobacco. However, at low volatility state, by using daily data, herding exists in two sectors i.e. Automobile Assemble and Power General & Distribution and for monthly data herding exists in three sectors i.e. Fertilizer, Textile Spinning and Textile Weaving. This study has important implication for market players, foreign / domestic investors can formulate their strategies for investment by seeing in which sector the herding exists. Supervisor:- Dr. Ahmad Fraz