Volume 4 Issue 3 | ESP IJSHMS

ESP International Journal of Science, Humanities and Management Studies [ESP IJSHMS]

Volume 4, Issue 3 [July-September, 2026]

Id	Title & Author	Paper
1	Derivative Pricing Under Complex Stochastic Market Conditions \| Omid Tavakoli, Babak Rostami Derivative pricing under complex market conditions requires valuation frameworks capable of capturing multiple and interacting sources of uncertainty that are not adequately represented by conventional constant-volatility models.
2	Counterfactual Reasoning for Algorithmic Financial Decision Systems \| Emeka Nwosu, Samuel Eze, Ibrahim Musa Counterfactual reasoning is a key approach for enhancing the transparency, accountability and usability of algorithmic decision systems in finance. Machine learning models for credit assessment, fraud detection and investment analysis are used by financial institutions more than ever in addition to portfolio allocation, risk management/optimization automated trading.
3	Large Language Model–Driven Economic Narrative Intelligence for Automated Financial Knowledge Synthesis \| Michael Omondi, Esther Jepchirchir, Catherine Chepkirui, Monica Awino The rapid advancement of Large Language Models (LLMs) has significantly enhanced the ability of computational systems to interpret, synthesize, and generate information from large volumes of heterogeneous financial and economic text.
4	Cross-Modal Economic Reasoning for Integrating Financial Text, Numerical Data, and Market Signals \| Rudi Simanjuntak, Hendra Gunawan Financial decision-making relies more and more on heterogeneous information, dispersed in financial reports, news articles, numerical indicators or time series such as price movements of stocks (stock prices), trading volumes and even planetary signals.
5	Policy-Driven API Security and Governance for Large-Scale Enterprise Financial Ecosystems \| Dr. Sameer Joshi Financial forecasting increasingly requires the integration of heterogeneous information sources, including textual disclosures, financial news, macroeconomic narratives, numerical market indicators, and time-series data.

Id	Title & Author	Paper
1	Derivative Pricing Under Complex Stochastic Market Conditions \| Omid Tavakoli, Babak Rostami Derivative pricing under complex market conditions requires valuation frameworks capable of capturing multiple and interacting sources of uncertainty that are not adequately represented by conventional constant-volatility models.
2	Counterfactual Reasoning for Algorithmic Financial Decision Systems \| Emeka Nwosu, Samuel Eze, Ibrahim Musa Counterfactual reasoning is a key approach for enhancing the transparency, accountability and usability of algorithmic decision systems in finance. Machine learning models for credit assessment, fraud detection and investment analysis are used by financial institutions more than ever in addition to portfolio allocation, risk management/optimization automated trading.
3	Large Language Model–Driven Economic Narrative Intelligence for Automated Financial Knowledge Synthesis \| Michael Omondi, Esther Jepchirchir, Catherine Chepkirui, Monica Awino The rapid advancement of Large Language Models (LLMs) has significantly enhanced the ability of computational systems to interpret, synthesize, and generate information from large volumes of heterogeneous financial and economic text.
4	Cross-Modal Economic Reasoning for Integrating Financial Text, Numerical Data, and Market Signals \| Rudi Simanjuntak, Hendra Gunawan Financial decision-making relies more and more on heterogeneous information, dispersed in financial reports, news articles, numerical indicators or time series such as price movements of stocks (stock prices), trading volumes and even planetary signals.
5	Policy-Driven API Security and Governance for Large-Scale Enterprise Financial Ecosystems \| Dr. Sameer Joshi Financial forecasting increasingly requires the integration of heterogeneous information sources, including textual disclosures, financial news, macroeconomic narratives, numerical market indicators, and time-series data.