This study is the first to test a financing-based misvaluation factor (UMO, undervalued-minus-overvalued), first proposed by Hirshleifer and Jiang (2010), for the Pakistani stock market. I find that the UMO factor, long underpriced (repurchase) stocks and short overpriced (new issue) stocks, earns significant mean and risk-adjusted returns. Further, I jointly examine the performance of UMO-augmented factor models – the Capital Asset Pricing Model, Carhart's four-factor model, and Fama and French's three-, five- and six-factor models – to find out which of these models or their subsets is most pertinent in the Pakistani stock market. A battery of tests – factor spanning regressions, Barillas and Shanken's (2017) maximum squared Sharpe ratio tests, and examination of two-way and one-way sorted portfolios using Gibbons-Ross-Shanken and Fama and French (2015, 2018) performance metrics over the 2003–2018 period – reveals that the UMO factor carries distinctive information that cannot be described by other factors under study. Finally, this study proposes a parsimonious four-factor model that combines the market, UMO, size, and profitability factors and outperforms the other models in Pakistan.

本研究首次测试了由 Hirshleifer 和 Jiang (2010) 首次针对巴基斯坦股票市场提出的基于融资的误估因素（UMO，低估-减-高估）。我发现 UMO 因素，多头低估（回购）股票和空头高估（新发行）股票，获得显着的均值和风险调整后的回报。此外，我还联合检验了 UMO 增广因子模型（资本资产定价模型、Carhart 的四因子模型以及 Fama 和 French 的三因子、五因子和六因子模型）的性能，以找出这些模型中的哪一个或它们的子集在巴基斯坦股市中最为相关。一系列测试——因子跨越回归、Barillas 和 Shanken (2017) 的最大平方夏普比率测试，并使用 Gibbons-Ross-Shanken 和 Fama 和 French（2015 年，2018 年）在 2003-2018 年期间的绩效指标检查双向和单向排序投资组合——揭示了 UMO 因子带有其他无法描述的独特信息正在研究的因素。最后，本研究提出了一个简约的四因素模型，该模型结合了市场、UMO、规模和盈利能力因素，并优于巴基斯坦的其他模型。