Dr. Mohd Shahid Ali is an Assistant Professor of Finance at the School of Management, IILM University, Gurugram, with over a decade of academic experience. He holds a Ph.D., MBA, and M.Com. from Jamia Millia Islamia, and has qualified UGC-NET with JRF along with CMA-Inter. His research spans behavioural finance, financial inclusion, taxation, green finance, and AI in business analytics, with over 15 research papers, 4 books, 2 edited volumes, and multiple Scopus-indexed chapters and conference proceedings to his credit. He is currently the Project Director of an ICSSR Major Project worth ₹84 lakhs and has also published a copyrighted AI-powered entrepreneurial ecosystem platform. Alongside teaching subjects in finance, analytics, and accounting, he has contributed to leadership roles in academic societies, IQAC, incubation cells, and research clusters.
EDUCATION
PhD, MBA, M.Com, B.Com. (Hons.), CMA (I)
RESEARCH, TEACHING, or OTHER INTERESTS
Finance, Accounting, Tourism, Leisure and Hospitality Management, Business, Management and Accounting
8
Scopus Publications
38
Scholar Citations
4
Scholar h-index
1
Scholar i10-index
Scopus Publications
Workforce Shocks and Financial Markets: Asset Pricing Perspectives Samreen Akhtar, Jyoti Agarwal, Alam Ahmad, Refia Wiquar, Mohd Shahid Ali International Journal of Financial Studies, 2026 Workforce adjustments, such as mass layoffs, are significant corporate events that can influence stock returns and volatility, yet their broader asset-pricing implications remain underexplored. We examine the impact of such workforce shocks on stock performance from an asset-pricing perspective. Grounded in production-based asset-pricing theory, incorporating labor adjustment costs and search-and-matching frictions, our study posits that disruptions in the labor force significantly affect firm risk and value. This focus addresses a clear gap. Previous research has not comprehensively evaluated workforce shocks as systematic risk factors in a cross-sectional asset-pricing model. Using an extensive dataset spanning 1990–2023 and covering thousands of layoff events, we construct a novel “workforce shock” factor and conduct the first large-scale empirical tests of its pricing relevance. Our analysis reveals that workforce shocks lead to lower stock returns and heightened volatility, effects especially pronounced in labor-intensive firms. Moreover, exposure to workforce shock risk carries a significant premium, indicating that these disruptions act as a systematic risk factor priced in the cross-section of equity returns. Overall, our study provides the first comprehensive evidence linking labor force disturbances to equity risk premia, underscoring the importance of incorporating labor market considerations into asset-pricing models.
A STOCHASTIC BEHAVIORAL–FINANCIAL FRAMEWORK FOR MODELING RESPONSIBLE TOURISM DYNAMICS ANTON VORINA, MAHAK MANZOOR, HABIBUR RAHMAN LASKAR, NAVEEN SIRIMAN, DATAR SINGH, SHADAB MOHD KHAN, MOHD SHAHID ALI, MD OBAIDUL OLA, TAUFEEQUE AHMAD SIDDIQUI, SUNAYANA, STUTI AS THANA Global and Stochastic Analysis, 2025 This paper proposes a mathematical framework for modelling the dynamic interface between financial factors and tourism sustainability using a nonlinear Structural Equation Modelling (SEM) approach. Based on a survey of Slovenian leisure travellers, the behavioural equation system includes environmental awareness (η₁), authentic sustainability (η₂), evolving traveller mindset (η₃), digital well-being (η₄), sustainable financial commitment (η₆), and integrated sustainable behaviour (η₅). The model demonstrates strong predictive validity with R 2 =0.73. Results confirm a nonlinear, inverted-U relationship between η₆ and η₅, where behavioural effectiveness peaks at an optimal financial threshold and declines beyond it. This validates the role of quadratic effects and highlights the saturation point of financial influence. The framework integrates cognitive (η₃) and digital (η₄) dimensions, showing that moderate financial engagement aligned with psychological and digital readiness yields optimal sustainability outcomes. The study contributes to sustainable tourism theory by offering a multidimensional behavioural-economic model for designing cost-effective, motivation-sensitive policy interventions.
Understanding Financial Inclusion Through Social and Behavioural Lenses Taufeeque Ahmad Siddiqui, Mohd Shahid Ali, Sunayana ., Naushad Alam, Prashant Ranjan Prabandhan Indian Journal of Management, 2025 Purpose : The present study focused on assessing the behavioral and societal factors of financial inclusion and aimed to develop a working model from a demand-side perspective. Methodology : This study utilized the structural equation modeling (SEM) technique to analyze the relationships between different constructs, such as financial literacy, government scheme awareness, behavioral biases, social norms, social trust, subjective norms, social networks, and financial inclusion. Findings : The study found that three out of six paths for behavioral biases, 21 out of 30 paths for social factors, and 11 out of 12 paths for financial literacy demonstrated significant impacts. This underscored the utmost significance of financial literacy, followed by social factors and behavioral biases. This study is limited to the Nuh (Mewat) district of Haryana, which might have influenced the applicability of the findings to other regions. Future research could be expanded to other geographic areas and incorporate longitudinal data to validate and refine the proposed model. Practical Implications : Actionable insights are offered by this study for policymakers and financial service providers to design and implement more effective financial inclusion strategies and tailored products. Enhancing financial inclusion could have led to improved economic stability and empowerment of individuals in marginalized communities, fostering overall societal development. Originality : This research proposed a unique demand-side approach to financial inclusion by combining several societal and behavioral constructs into a comprehensive model, offering a deeper insight into the factors inducing financial inclusion in the special context of backward regions of the country.
Social and behavioural influences on financial inclusion: Insights from a regional study Taufeeque Ahmad Siddiqui, Mohammad Naushad, Mohd Shahid Ali, Sunayana Asian Economic and Financial Review, 2025 The research explores financial inclusion through a novel demand-side perspective, combining behavioral and societal elements to study their impact on financial inclusion, especially in underdeveloped economic areas. The primary data for the study was obtained from 1,050 participants. The research used Structural Equation Modeling (SEM) to analyze financial inclusion in relation to behavioral biases, social norms, social networks (financial and social), social trust, and subjective norms. The findings indicate that subjective norms are the most significant factor for financial inclusion, followed by social networks, social norms, and behavioral biases. The higher-order model offers a clearer understanding, highlighting the positive impact of behavioral biases and social factors on financial inclusion. The research demonstrates that behavioral and social elements strongly determine the outcomes of financial inclusion. Financial inclusion strategies need to focus on local socio-behavioral dynamics because subjective and social norms prove to be essential drivers. The research provides useful guidance for both policymakers and financial service providers. Understanding behavioral and social factors in financial inclusion enables the development of specific and culturally appropriate strategies to build inclusive financial systems in underserved areas.
Quantum-Inspired AI for Predictive Financial Modeling: Unlocking the Next Frontier in Algorithmic Trading Mohd Shahid Ali, Taufeeque Ahmad Siddiqui, Afzalur Rahman, Mohsina Hayat, Refia Wiquar Proceedings of the 2025 International Conference on Artificial Intelligence and Emerging Technology Global AI Summit 2025, 2025 The fast-moving nature of financial markets has increased the need for predictive models that are not only accurate but also robust in volatile environments. Classical machine learning and deep learning-based methods have demonstrated potential in algorithmic trading; however, they are often limited by overfitting, latency, and a lack of agility in ultra-dynamic environments. In this paper, we present a Quantum-Inspired Artificial Intelligence (QIAI) template for predictive financial modelling, drawing on the principles of quantum annealing and evolutionary search to optimize feature subset selection and improve learning within time-series forecasting models. Applying both stock index and cryptocurrency data sets, benchmarking results demonstrate that the proposed QIAI-optimized LSTM outperforms various traditional AI models. The results demonstrate strong outperformance in terms of root mean square error (RMSE), mean absolute percentage error (MAPE), and trading strategy returns, accompanied by substantial enhancements to Sharpe ratios and drawdown control. The results show QIAI to be a scalable way toward the next level of advancement in algorithmic trading.
Neuromorphic Computing and AI-Driven Risk Assessment: Toward Ultra-Low Latency Financial Decision Systems Mohd Shahid Ali, Mohd Atif, Naveen Siriman, Afzalur Rahman, Taufeeque Ahmad Siddiqui Proceedings of the 2025 International Conference on Artificial Intelligence and Emerging Technology Global AI Summit 2025, 2025 As financial systems mature, decision-making systems that strike a beneficial spot between accuracy and ultralow latency are required. Although traditional AI approaches deliver state-of-the-art performance, they rely on computational ‘brute-forcing.’ These models are energy-intensive and computationally costly relative to real-time learning about high-dimensional financial time series. Additionally, high energy costs result in non-real-time adaptive systems based on trading. The current work proposes a novel approach, consisting of the neural and AI components, integrated with the Spiking Neural Networking, Reinforcement learning, and Deep Ensemble modules for financial risk assessment. Financial data time series are cast into spike trains and accumulated into Eligibility Trace on-chip neuro-memories to track the volatility and detect the anomalies. Experiments on barbarity financial bits including ctypto-currencies, stocks and quantitative-credited show the systems achieve low inference latency of ~35 micro-second, 30 x faster compared to baseline deep learning models with well-competitive accuracy power than 0.91. We also experiment back-testing and achieve enhanced 12% Sharpe ratio. Moreover, the neuromorphic hardware demonstrates almost two orders of magnitude lower in energy. These results in the potential of such neuromorphic-AI structures towards real-time high-frequency trading, fraud detection, and sustainable risk monitoring.
Reinforcement Learning in Decentralized Exchanges: Adaptive Market-Making and Liquidity Management Mohd Shahid Ali, Alam Ahmad, Mohd Atif, Monika Mittal, Afzalur Rahman Proceedings 2025 7th International Conference on Artificial Intelligence and Speech Technology Aist 2025, 2025 Decentralized exchanges (DEXs) are one of the keystones of decentralized finance (DeFi). Instead of booking the order under centralized system, you have straight peer-to-peer trades via Automated Market Makers (AMM). AMMs like Uniswap and Curve have actually been developed to reduce the friction of liquidity provisioning. Nevertheless, they still experience impermanent loss, deadweight loss, compartmentalization of market liquidity, in addition to suboptimal operation in volatile environments. This paper explains an RL-based algorithm that can regulate liquidity and flexible market-making in DEXs. RL agents has been trained to maximize capital allowance, liquidity rebalancing, and spread adjusting in live trading information from SushiSwap and Uniswap in addition to synthetically created cardiovascular test. DQN, PPO, and A3C are three RL algorithms that we have actually contrasted versus constant-product AMM standards. With risk-adjusted returns of as much as 1.6 vs. 0.9, an impermanent loss reduction of 15-20%, and test-set revenues of 12.5 -15.7% vs. 8, it seems that RL-poured method is considerably much better. The stability and scalability of RL models under different swimming pool dimensions and volatility regimes are further made certain by level of sensitivity analysis. Actually, PPO is the most effective in high-volatility circumstances, DQN assembles more quickly in moderate scenarios, and A3C offers a trade-off. Our results open up the design of flexible monetary AI systems and are right away appropriate to enhancing liquidity rewards, stability, and performance in DeFi. The result of the experiment shows that RL can be made use of to improve the rationality of liquidity administration in DEXs. The integration of administration systems right into multi-agent RL and the gas-efficient migration of these algorithms from off-chain to on-chain ought to be the primary tasks of future research study.
Optimizing Venture Capital Allocation with Deep Learning-Based Sentiment Analysis and Financial Data Fusion Techniques MohdShahid Ali, Piyush Mehta, S. Umamaheswari, Claudio Paya Santos, K S Srinivas, Saif Siddiqui Proceedings of 2025 10th International Conference on Science Technology Engineering and Mathematics Iconstem 2025, 2025 This research offers a new idea of optimizing the allocation of venture capital by a Hybrid Deep Learning Model which incorporates Sentiment Analysis and Financial Data Fusion Techniques. This approach enhances the accuracy of predictions and efficiency of decision-making when investing in venture capital by integrating the use of the sentiment analysis using LSTM with the use of traditional financial models. The advanced functionality of the AWS SageMaker has been utilized in the model to provide the means of processing real-time data, scalable training, and scalable deployment to ensure high performance in large-scale datasets. Moreover, the explainable AI methods bring transparency and interpretability, so that the predictions of the model can be trusted by the investor. The suggested system addresses the drawbacks of the conventional approaches, namely, the lack of data and overfitting, perfectly integrating the financial data and the sentiment-based insight. The findings prove that this hybrid model has the potential to improve the allocation of venture capital, which has provided a solid and data-driven solution to make informed investment decisions in moving markets.
RECENT SCHOLAR PUBLICATIONS
Neuromorphic Computing and AI-Driven Risk Assessment: Toward Ultra-Low Latency Financial Decision Systems M. S. Ali, M. Atif, N. Siriman, A. Rahman and T. A. Siddiqui 025 2nd Global AI Summit - International Conference on Artificial … , 2026 2026
Quantum-Inspired AI for Predictive Financial Modeling: Unlocking the Next Frontier in Algorithmic Trading M. S. Ali, T. A. Siddiqui, A. Rahman, M. Hayat and R. Wiquar 2025 2nd Global AI Summit - International Conference on Artificial … , 2026 2026
Optimizing Venture Capital Allocation with Deep Learning-Based Sentiment Analysis and Financial Data Fusion Techniques M. S. Ali, P. Mehta, S. Umamaheswari, C. P. Santos, K. S. Srinivas and S ... 2025 Tenth International Conference on Science Technology Engineering and … , 2026 2026
AI-Powered Fraud Detection Systems in Online Banking: Enhancing Security through Anomaly Detection MS Reddy, ... International Conference on Sustainable Engineering and Technology … , 2026 2026
Workforce Shocks and Financial Markets: Asset Pricing Perspectives S Akhtar, J Agarwal, A Ahmad, R Wiquar, MS Ali International Journal of Financial Studies 14 (1), 12 , 2026 2026
Circular Economy and Financial Strategies: Driving Sustainable Growth and Achieving Financial Synergy in Supply MS Ali, R Jha 19th ISDSI-Global Conference 2025 on Tech for Net Zero: Digital Solutions … , 2025 2025
Rise of financial technology and emerging theme in the green finance research : A systematic literature review towards future research prospects MS Ali, GP Kulkarni, N Siriman, R Gaddam, A Rahman, SR Balabantaray Journal of Information & Optimization Sciences 46 (8), 2563-2572 , 2025 2025
Testing The Long Run Relation Between Health Investments And Economic Growth In India R Gaddam, MS Ali, N Siriman, KR Rao, M Hayat Journal of Information and Optimization Sciences 46 (8), 2531-2541 , 2025 2025
Measuring Financial Inclusion Multidimensionally: Evidence From Marginalized Communities in Haryana MS Ali, M Mittal, TA Siddiqui IMRC2025 - IIM Ahmedabad on conference theme: The Future of the Economy … , 2025 2025
Social and behavioural influences on financial inclusion: Insights from a regional study T Ahmad, M Naushad, MS Ali, Sunayana Asian Economic and Financial Review 15 (7), 1098-1110 , 2025 2025
Unveiling the Impact of Digitalization on Indian Banking Operations M Imran, MS Ali, SN Nallapati, SM Kothapalli, Dedeepya & Ishaq Interdisciplinary Pathways tо Sustainable Development 1, 76-84 , 2025 2025
Man-Dog Conflict Result of Fractured System and Apathetic Governance A Pandey, Ali, Mohd Shahid Journal of Lifestyle and SDGs Review 5 (6), 1-18 , 2025 2025
Green Finance and AI in India: A Synergistic Approach to Sustainable Development and Climate Resilience N Siriman, MS Ali, TA Siddiqui, G Rohin, B Vejju, N Cherupelly International Journal of Environmental Sciences 11 (1), 207-216 , 2025 2025 Citations: 9
Understanding Financial Inclusion Through Social and Behavioural Lenses TA Siddiqui, MS Ali, Sunayana, N Alam, P Ranjan Prabandhan Indian Journal of Management 18 (4), 52-71 , 2025 2025 Citations: 4
Book: Mastering Marketing and Finance for Business Success DA Mahadule, S Singathurai, RKV Reddy, K Thote, MS Ali Paradox International Publications (http://dx.doi.org/10.25215/934870107X) 1 … , 2025 2025
Rethinking Risk Management: The Role of AI and Big Data in Financial Forecasting VS Rao, GV Radhakrishnan, PR Mukkala, TC Thomas, MS Ali Advances in Consumer Research 2 (1), 178 - 185 , 2025 2025 Citations: 4
Edited Book: Contemporary Trends in Commerce, Management & Economics S Thilaka, A Kalaiya, MS Ali, AK Joan, R Gupta A2Z EduLearningHub (https://doi.org/10.5281/zenodo.14777879) 1, 106 , 2025 2025
Book: Integrated Approaches to Research Methodology: Concepts and Applications D Gabhane, SR Sahu, MS Ali, TS Haokip, S Diwakar Redshine Publication (http://dx.doi.org/10.25215/934870107X) 1, 213 , 2024 2024
Edited Book: Unified Visions: Collaborative Paths In Multidisciplinary Research, G Chaudhary, H Qudsi, Shivakumar, PVH Prasad, U Shankar, MS Ali, ... Redshine Publication (http://dx.doi.org/10.25215/8198189815) 2, 355 , 2024 2024
An AI-powered Entrepreneurial Ecosystem Platform for Start-up Support V Deshmukh, B. B., M P, M., Sajitha, S., Ali, M. S., Shunmugasundaram, M ... CA Patent 1,228,038 , 2024 2024
MOST CITED SCHOLAR PUBLICATIONS
Theories of capital structure: Analysis of capital structure determinants MS Ali, R Yadav, A Jamal International Research Journal of Management Science and Technology 4 (3 … , 2013 2013 Citations: 14
Green Finance and AI in India: A Synergistic Approach to Sustainable Development and Climate Resilience N Siriman, MS Ali, TA Siddiqui, G Rohin, B Vejju, N Cherupelly International Journal of Environmental Sciences 11 (1), 207-216 , 2025 2025 Citations: 9
Understanding Financial Inclusion Through Social and Behavioural Lenses TA Siddiqui, MS Ali, Sunayana, N Alam, P Ranjan Prabandhan Indian Journal of Management 18 (4), 52-71 , 2025 2025 Citations: 4
Rethinking Risk Management: The Role of AI and Big Data in Financial Forecasting VS Rao, GV Radhakrishnan, PR Mukkala, TC Thomas, MS Ali Advances in Consumer Research 2 (1), 178 - 185 , 2025 2025 Citations: 4
Capital Structure Theories: A Review MS Ali, R Yadav, MA Khan International Research Journal of Commerce Arts and Science , 2013 2013 Citations: 4
Analysis of Determinants of Capital Structure: With Special Reference to Indian Listed Non-Financial Companies in S and P CNX Nifty MS Ali, HW Akram, MA Khan Business Dimensions 1 (2), 147-155 , 2014 2014 Citations: 2
The Impact of Corporate Governance on Firm Valuation in Financial Markets M Chakraborty, B Nanda, PVH Prasad, MS Ali, D Sant Library Progress International 44 (3), 17892-17900 , 2024 2024 Citations: 1
Neuromorphic Computing and AI-Driven Risk Assessment: Toward Ultra-Low Latency Financial Decision Systems M. S. Ali, M. Atif, N. Siriman, A. Rahman and T. A. Siddiqui 025 2nd Global AI Summit - International Conference on Artificial … , 2026 2026
Quantum-Inspired AI for Predictive Financial Modeling: Unlocking the Next Frontier in Algorithmic Trading M. S. Ali, T. A. Siddiqui, A. Rahman, M. Hayat and R. Wiquar 2025 2nd Global AI Summit - International Conference on Artificial … , 2026 2026
Optimizing Venture Capital Allocation with Deep Learning-Based Sentiment Analysis and Financial Data Fusion Techniques M. S. Ali, P. Mehta, S. Umamaheswari, C. P. Santos, K. S. Srinivas and S ... 2025 Tenth International Conference on Science Technology Engineering and … , 2026 2026
AI-Powered Fraud Detection Systems in Online Banking: Enhancing Security through Anomaly Detection MS Reddy, ... International Conference on Sustainable Engineering and Technology … , 2026 2026
Workforce Shocks and Financial Markets: Asset Pricing Perspectives S Akhtar, J Agarwal, A Ahmad, R Wiquar, MS Ali International Journal of Financial Studies 14 (1), 12 , 2026 2026
Circular Economy and Financial Strategies: Driving Sustainable Growth and Achieving Financial Synergy in Supply MS Ali, R Jha 19th ISDSI-Global Conference 2025 on Tech for Net Zero: Digital Solutions … , 2025 2025
Rise of financial technology and emerging theme in the green finance research : A systematic literature review towards future research prospects MS Ali, GP Kulkarni, N Siriman, R Gaddam, A Rahman, SR Balabantaray Journal of Information & Optimization Sciences 46 (8), 2563-2572 , 2025 2025
Testing The Long Run Relation Between Health Investments And Economic Growth In India R Gaddam, MS Ali, N Siriman, KR Rao, M Hayat Journal of Information and Optimization Sciences 46 (8), 2531-2541 , 2025 2025
Measuring Financial Inclusion Multidimensionally: Evidence From Marginalized Communities in Haryana MS Ali, M Mittal, TA Siddiqui IMRC2025 - IIM Ahmedabad on conference theme: The Future of the Economy … , 2025 2025
Social and behavioural influences on financial inclusion: Insights from a regional study T Ahmad, M Naushad, MS Ali, Sunayana Asian Economic and Financial Review 15 (7), 1098-1110 , 2025 2025
Unveiling the Impact of Digitalization on Indian Banking Operations M Imran, MS Ali, SN Nallapati, SM Kothapalli, Dedeepya & Ishaq Interdisciplinary Pathways tо Sustainable Development 1, 76-84 , 2025 2025
Man-Dog Conflict Result of Fractured System and Apathetic Governance A Pandey, Ali, Mohd Shahid Journal of Lifestyle and SDGs Review 5 (6), 1-18 , 2025 2025
Book: Mastering Marketing and Finance for Business Success DA Mahadule, S Singathurai, RKV Reddy, K Thote, MS Ali Paradox International Publications (http://dx.doi.org/10.25215/934870107X) 1 … , 2025 2025
