Saba Haider
Dr. Saba Haider is a Lecturer at the University of Gujrat, Pakistan. She holds a PhD in Finance from COMSATS University Islamabad and an MS in Banking and Financial Economics from GC University Lahore. A gold medalist in her BBA (Hons.), she has published research in reputable journals. Her expertise includes financial Markets, investment banking, and corporate finance. Passionate about academic excellence, she actively mentors students and contributes to research in the field of finance
- PhD,Comsats I.I. Technology Lahore
- M.Phil,Goverment College University , Lahore
- BBA (Hons),University of Punjab
- Merit Scholarship BBA (Hons.)
- Gold-Medalist BBA (Hons.)
- Faculty Development Scholarship Holder HEC
| Student Name | Degree | Title | Status / Completed Year |
|---|---|---|---|
| Muhammad Umer | MS | FORECASTING STOCK RETURNS THROUGH FINANCIAL STRESS INDEX: A COMPARATIVE ANALYSIS OF LINEAR AND NON-LINEAR MODELS This paper’s focus is to analyze the level of prediction of stock returns through the lens of the FSI (Financial Stress Index) by utilizing linear and non-linear models. The study employs panel data analysis and examines the selected Pakistan stock exchange market from 1997 to 2023; data for FSI is collected from the Alternative Regional Integration Centre, and Stock returns are collected from the Pakistan stock exchange website. The first objective is to identify whether the FSI and stock returns link follows a linear or non-linear pattern to shed light on the severity of financial stress effects on stock returns. As quantitative research, the given study analyzes financial information using mathematical tools. The Correlation results point towards a negative and statistically significant though poor association between FSI and stock returns with the calculated rho equal to -0.1154. A regression analysis to greater knowledge displays that the FSI coefficient equals (-0.17478), And the t-statistic is equal to (-4.72274) for the regression line. The number and the probability of it are equal to 0.0000. the r-square value is 0.639785, meaning these factors explain approximately 64% of the model. The comparison is then between linear models, namely Vector Autoregressive (VAR) and Auto-Regressive Integrated Moving Average (ARIMA), and Non-linear models that include Autoregressive Conditional Heteroskedasticity (ARCH) and Generalized ARCH (GARCH). The measures of skill scores RMSE, MAE, and Theil inequality coefficient depicting the non-linear models, just like ARCH and GARCH, are superior to the linear models regarding forecasting errors. More specifically, the GARCH model performs better than the ARCH Model, indicating a better capacity for modeling the undertakings underlying the relationship between FSI and stock returns. This research makes a threefold contribution: First, it prolongs the time frame in which the correlation between financial pressure and stock returns may be observed. Second, it compares the linear and non-linear models, such as VAR, ARIMA, ARCH, and GARCH, under different levels of financial stress. Third, the paper contributes to understanding the predictability of stock returns with enhanced emphasis on the effects of financial stress on turnover. | 2024 |
| Umme Farwa | MS | FORECASTING STOCK RETURNS THROUGH FINANCIAL STRESS INDEX: A COMPARATIVE ANALYSIS OF LINEAR AND NON-LINEAR MODELS This study examine the relationship of commodity price model and technical analysis model in predicting exchange rate to determine which model is more effective in forecasting exchange rate within commodity dependent developed and developing economies. Therefore, using a quantitative approach that fits a positivist paradigm, the work utilizes time series analysis to evaluate the disparities in the price of the commodity as well as the technical analysis models. The sample includes a developed country group including Australia, New Zealand, Canada, South Africa Russia and developing country group including Nigeria, Ghana, Peru, Paraguay, and Pakistan with free float exchange rates from 1995 to 2023. Data of exchange rate is collected from international financial statistic while commodity price is collected from IMF’s commodity term of trade. These results depict a closeness between the variables under study; that is, exchange rates and commodity prices, while exchange rates present strong persistence or high dependence on previous values as well as effects from the commodity prices differing at different intervals. Therefore, the findings of the study are that commodity prices are not decisive in model prediction, but that other factors and the historical values of the exchange rates are more influential. Possible future studies should advance the sample size, use more sophisticated models, incorporate more macro economy indicators into the system and conduct cross sectional analysis of different technical analysis indicators. The effects of exchange rate risks should be in harmony to a combination of both prices of the different commodities which include the use of technical analysis indicator. | 2024 |
| Shawaiz Shoukat | MS | Determinants of Interest Rate Spread and its impact on Bank’s Profitability; Evidence from Pakistan This study examines the determinants of interest rate spread (IRS) and its impact on bank profitability in Pakistan’s banking sector. Using panel data from commercial banks over a specified period, the research identifies key factors influencing IRS, including macroeconomic variables, bank-specific characteristics, and regulatory policies. The study employs econometric techniques to analyze the relationship between IRS and profitability, measured through return on assets (ROA) and return on equity (ROE). The findings suggest that higher IRS, driven by factors such as inflation, monetary policy stance, and operational inefficiencies, significantly affects bank profitability. The study provides policy recommendations to enhance banking sector efficiency and financial intermediation in Pakistan. | 2016 |
- Co-coordinator of Departmental Society (SPEAKS) for 1 year
- Interview Panelist of Graduate Admission Committe
- Member of Under Graduate Admission Committe
- Time Table Coordinator of Management Sciences
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1. Sohrab & Haider “Impact of Exchange Rate Risk exposure and Derivative Usage on Firm Value, Evidence from Non-financial Firms of Pakistan” 1st International Conference on Management and Commerce (ICMC) “Sustainable Entrepreneurship: from knowledge to venture”, April 2018 _DOI:
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2. Raza, Rasib & Haider “Effect of political shocks on working capital management of Firms: Evidence from Pakistan” 8th International Conference on Management Research (ICMR) “Entrepreneurial Mindset: Challenges, opportunities and Strategies in emerging markets”, November 2017 _DOI:
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3. Eshaq, Afshan & Haider “Determinents of Derivative Usage in Banking Sector: Evidence from Pakistan using Probit Model” in 8th International Conference on Management Research (ICMR) “Entrepreneurial Mindset: Challenges, opportunities and Strategies in emerging markets, November 2017 _DOI:
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4. Sohrab & Haider “Impact of Exchange Rate Risk exposure and Derivative Usage on Firm Value, Evidence from Non-financial Firms of Pakistan” 8th International Conference on Management Research (ICMR) “Entrepreneurial Mindset: Challenges, opportunities and Strategies in emerging markets”, November 2017 _DOI: