Faheem Aslam

Scopus Publications

Tracking oil price shocks and airline stock reactions using entropy-based approaches
Faheem Aslam, Paulo Ferreira, Márcia Oliveira, Dora Almeida
International Review of Economics and Finance, 2026
The relationship between oil prices and the airline industry is economically important yet empirically complex, presenting significant challenges, with prior research yielding conflicting evidence on the nature, strength, and direction of their interaction. This study contributes to the literature moving beyond traditional linear assumptions, applying Shannon and Rényi transfer entropy to evaluate the nonlinear and state-dependent information flow between oil, oil volatility, and six international airline indices. The empirical findings reveal a significant but heterogeneous information flow between West Texas Intermediate (WTI) and airline indices, suggesting a relationship of mutual influence, where the directional information flow from WTI to airline indices consistently surpasses the reverse flow. In the case of the Crude Oil Volatility Index (OVX), results show a dominant flow of information from each airline index to the OVX index, indicating that sector-specific shocks can shape market expectations of oil volatility. The Rényi entropy analysis further uncovers tail-driven dynamics: at low orders of Rényi entropy, the entropy values remained predominantly negative between WTI and airline indices, while they remained predominantly positive, particularly from OVX to airline indices. However, at very high orders of entropy, there is a more traditional flow of information from WTI to airline indices. These findings enable policymakers to develop more effective, targeted, and economically sound energy policies for the transportation sector and the wider economy.
THE EFFICIENCY OF SIN STOCKS: A MULTIFRACTAL ANALYSIS OF DRUG INDICES
Faheem Aslam, Paulo Ferreira, Fahd Amjad, Haider Ali
Singapore Economic Review, 2026
This study provides the first evidence of market efficiency of drug indices, especially cannabis and tobacco, which are known in finance as sin markets. The multifractal detrended fluctuation analysis (MFDFA) is employed on the daily data of six cannabis and one tobacco indices in order to measure efficiency by quantifying the intensity of self-similarity. The findings confirm multifractality in all sample series. Interestingly, Dow Jones Tobacco (DJUSTB) Index shows the highest multifractality, demonstrating the lowest efficiency, whereas S&P/TSX Cannabis (SPTXCAN) Index is the most efficient of all the time series under analysis, with the lowest multifractality levels. Only the North American Marijuana (NAMMAR), Cannabis World Index Gross Total Return (CANWLDGR) and DJUSTB show persistent behavior. These findings could be of interest to policymakers and regulators to establish new reforms to improve the efficiency of these markets, as well as for actual and potential investors.
Risk without borders: A transfer entropy analysis of geopolitical spillovers in low- and lower-middle-income markets
Dora Almeida, Paulo Ferreira, Faheem Aslam
Economics and Business Letters, 2026
How geopolitical risk affects stock markets in low and lower-middle-income countries remains an area often overlooked. This study analyzes daily data from 2014 to 2025 for 16 stock markets and two geopolitical risk subindices, acts and threats. The transfer entropy is applied in a dynamic framework to measure asymmetric and time-varying information flows. The findings reveal a heterogeneous influence of acts and threats, varying by country-income level, geographic region, and over time. Stock market sensitivity increased after 2020, particularly in response to acts rather than threats. This highlights distinct geopolitical risk transmission, requiring tailored investment strategies and policy responses.
The impact of oil market volatility on the airline-tourism: quantile VAR approach
Wahbeeah Mohti, Ayesha Rehan, Faheem Aslam, Paulo Ferreira
Cogent Economics and Finance, 2026
This study investigates the quantile-specific connectedness between global airline indices, tourism indices, oil prices and oil volatility. Quantile Vector Autoregressive (QVAR) framework is employed across three quantiles (5th, 50th and 95th) to capture the dynamic connectedness under bearish, normal and bullish market conditions with particular emphasis on COVID-19 pandemic and Russia-Ukraine war period. To understand the sector-wise behavior and to identify the shock transmission patterns across sectors, group-level net spillovers are also estimated. Results indicate that airlines consistently act as dominant shock transmitters, tourism primarily absorbs shocks and oil and oil volatility function as reactive receivers, particularly under downside stress. The findings provide valuable insights for policymakers, investors and industry stakeholders in managing systemic risk and enhancing sectoral resilience under extreme market conditions.
Time-frequency connectedness and volatility spillovers among green equity sectors: A novel TVP-VAR frequency connectedness approach
Nasir Nadeem, Imran Abbas Jadoon, Faheem Aslam, Paulo Ferreira
Energy, 2025
Investment in green equity market is growing more specifically after COVID-19 due to rising awareness of climate and environmental issues. Investors and policymakers require updated information about the connectedness and shock spillover pattern among green sectors to manage portfolios effectively. The novel TVP–VAR frequency connectedness approach is applied to daily volatility series of green equity indices to explore the volatility spillover dynamics in the time-frequency domain. The findings demonstrate strong interlinkages among green sectors that have become more pronounced during crisis events, with water, energy efficiency, green building and recycling as the largest transmitters of volatility shocks, being considered as systemically important sectors. In contrast, bio-clean fuels, healthy living, advanced materials and natural resources are primary risk absorber sectors. The dynamic analysis reveals the heterogeneous behavior of sectors during turmoil periods. Additionally, the frequency decomposition analysis reveals that volatility spillover is mainly concentrated in the short run, suggesting diversification opportunities for investors in the long run. Empirical findings help investors and policymakers to manage risk in the green equity market. Understanding how sectors influence market instability is crucial. Policymakers must closely and systematically monitor important sectors to prevent systemic risk, as shocks in these sectors can spread to others.
Information flow between asset classes during extreme events
Dora Almeida, Andreia Dionísio, Paulo Ferreira, Faheem Aslam, Derick Quintino
Physica A Statistical Mechanics and Its Applications, 2025
The interconnectedness between asset classes becomes particularly relevant during extreme events, as market stress amplifies risk spillovers and impacts asset relationships, influencing risk transmission and financial market stability. While existing studies often examine financial interdependencies, including extended periods, they frequently focus on specific markets or asset classes, limiting the understanding of cross-asset contagion effects. Thus, it is crucial to grasp the interconnectedness among asset classes and how they communicate information under different economic conditions. This research bridges the gap by applying the transfer entropy approach to analyze the evolving connections among various asset classes from April 2017 to September 2024, spanning the COVID-19 pandemic and the Russia–Ukraine war. The findings reveal that stocks and cryptocurrencies consistently are net information transmitters to the system. Currency benchmarks and gold tend to receive information from the system during increased tension, reflecting their role in absorbing risk-driven capital flows. This study challenges the idea that cryptocurrencies are separate from traditional financial markets and shows how they are becoming more integrated. By employing net transfer entropy within a financial network analysis framework, this study uncovers time-varying shifts in market interdependencies and, thus, an enhanced description of financial contagion dynamics. The dynamic nature of such relationships highlights the need for adaptive portfolio strategies and enhanced risk assessment models. Our results have direct implications for portfolio management and risk assessment. Investors can use this study’s findings to recognize assets that are sources of systemic risk or safe haven assets, facilitating adaptative changes in their portfolios. Policymakers and regulators can use these findings to forecast systemic vulnerabilities and implement strategies aiming to reduce financial instability in times of crisis.
Return connectedness and portfolio implications of green equities: A comparison of green and conventional investment modes
Nasir Nadeem, Imran Abbas Jadoon, Faheem Aslam, Paulo Ferreira
Journal of Environmental Management, 2025
The notable expansion of the green equity market has opened up new avenues for investment for market participants. This study looks at return connectedness, and the implications for portfolio management of green sector equities, and compares the performance of green and traditional investments. To achieve the research objectives, this study uses the TVP-VAR model along with portfolio strategies such as minimum variance portfolio (MVP), minimum correlation portfolio (MCP), and minimum connectedness portfolio (MCoP). Results demonstrate that the energy efficiency sector leads all others in information spillover while the bio/clean fuels sector is the largest net information absorber. Overall, energy efficiency, water, recycling and green building are found to be closely connected sectors, whereas bio/clean fuels, healthy living, natural resources and advanced materials are the least integrated industries in the system. However, a dynamic analysis demonstrates that inter-sector connectedness is time-varying and event-dependent. The MVP approach excels in the full and pre-COVID-19 sample, whilst the MCoP outperforms other methods in the post-COVID-19 scenario. In general, the portfolio exercise shows that green portfolios outperformed commodities but underperformed conventional equity and cryptocurrency portfolios. In contrast, following the COVID-19 pandemic, green portfolios have shown a greater return performance than all other conventional portfolios. The findings not only provide valuable insights to investors and policymakers in the effective management of investments and the green equity market, but also aid the achievement of objectives of environmental policies such as SDGs and the Paris Agreement.
Information theory approach to explain crisis moments in financial markets
Paulo Ferreira, Faheem Aslam
Encyclopedia of Monetary Policy Financial Markets and Banking, 2025
Do trade openness and derivative markets nexus play vital role on economic development? Empirical investigation from developed and emerging economies
Wajid Shakeel Ahmed, Faheem Aslam
Cogent Economics and Finance, 2025
The persistent global risks make the situation more challenging for the economies to show progression in economic growth. A well-functioning derivative market makes it feasible for firms to share risk effectively by means of financial development which contributes immensely in overall economic development. This study focuses on evaluating the financial growth and economic development nexus through trade openness in developed and emerging economies. The study dataset comprises of upper- and middle-income group economies and applied the Granger causality test along with panel regression fixed effect (FE) and panel corrected standard error (PCSE) model techniques. The findings reveal that bidirectional homogenous Granger causality exists universally among derivative markets and economic development. The study establishes that derivative markets are integrated with economic development and macroeconomic variables in countries with high income compared to the upper-middle-income group. The findings favour the PCSEs model over the FE model with conclusive evidence. Furthermore, openness to trade significantly contributes more to financial development compared to macroeconomic variables. Results based on the IRF test statistics confirm that the derivative market response of shocks is statistically significant to GDP and trade openness for upper-middle-income economies. This study makes an original contribution by considering trade openness, derivative markets and macroeconomic factors play vital role in the growth nexus especially for emerging economies.
Integrating Macroeconomic and Technical Indicators into Forecasting the Stock Market: A Data-Driven Approach
Saima Latif, Faheem Aslam, Paulo Ferreira, Sohail Iqbal
Economies, 2025
Forecasting stock markets is challenging due to the influence of various internal and external factors compounded by the effects of globalization. This study introduces a data-driven approach to forecast S&P 500 returns by incorporating macroeconomic indicators including gold and oil prices, the volatility index, economic policy uncertainty, the financial stress index, geopolitical risk, and shadow short rate, with ten technical indicators. We propose three hybrid deep learning models that sequentially combine convolutional and recurrent neural networks for improved feature extraction and predictive accuracy. These models include the deep belief network with gated recurrent units, the LeNet architecture with gated recurrent units, and the LeNet architecture combined with highway networks. The results demonstrate that the proposed hybrid models achieve higher forecasting accuracy than the single deep learning models. This outcome is attributed to the complementary strengths of convolutional networks in feature extraction and recurrent networks in pattern recognition. Additionally, an analysis using the Shapley method identifies the volatility index, financial stress index, and economic policy uncertainty as the most significant predictors, underscoring the effectiveness of our data-driven approach. These findings highlight the substantial impact of contemporary uncertainty factors on stock markets, emphasizing their importance in studies analyzing market behaviour.
Exploring the connection between geopolitical risks and energy markets
Dora Almeida, Paulo Ferreira, Andreia Dionísio, Faheem Aslam
Energy Economics, 2025
Inner Multifractal Dynamics in the Jumps of Cryptocurrency and Forex Markets
Haider Ali, Muhammad Aftab, Faheem Aslam, Paulo Ferreira
Fractal and Fractional, 2024
Influence of the Russia–Ukraine War and COVID-19 Pandemic on the Efficiency and Herding Behavior of Stock Markets: Evidence from G20 Nations
Bilal Ahmed Memon, Faheem Aslam, Hafiz Muhammad Naveed, Paulo Ferreira, Omonjon Ganiev
Economies, 2024
Enhanced prediction of stock markets using a novel deep learning model PLSTM-TAL in urbanized smart cities
Saima Latif, Nadeem Javaid, Faheem Aslam, Abdulaziz Aldegheishem, Nabil Alrajeh, Safdar Hussain Bouk
Heliyon, 2024
Interplay of multifractal dynamics between shadow policy rates and energy markets
Faheem Aslam, Ahmed Imran Hunjra, Bilal Ahmed Memon, Mingda Zhang
North American Journal of Economics and Finance, 2024
Navigating Choppy Waters: Interplay between Financial Stress and Commodity Market Indices
Haji Ahmed, Faheem Aslam, Paulo Ferreira
Fractal and Fractional, 2024
On the Dynamic Changes in the Global Stock Markets’ Network during the Russia–Ukraine War
Kashif Zaheer, Faheem Aslam, Yasir Tariq Mohmand, Paulo Ferreira
Economies, 2024
Bitcoin’s multifractal influence: deciphering the relationship with conventional and renewable energy markets
Ayesha Rasool Malik, Faheem Aslam, Paulo Ferreira
Cogent Economics and Finance, 2024
Are clean energy markets efficient? A multifractal scaling and herding behavior analysis of clean and renewable energy markets before and during the COVID19 pandemic
Bilal Ahmed Memon, Faheem Aslam, Shakhnoza Asadova, Paulo Ferreira
Heliyon, 2023
The dynamics of market efficiency of major cryptocurrencies
Faheem Aslam, Bilal Ahmed Memon, Ahmed Imran Hunjra, Elie Bouri
Global Finance Journal, 2023
Interplay of multifractal dynamics between shadow policy rates and stock markets
Faheem Aslam, Wahbeeah Mohti, Haider Ali, Paulo Ferreira
Heliyon, 2023
Investigating efficiency of frontier stock markets using multifractal detrended fluctuation analysis
Faheem Aslam, Paulo Ferreira, Wahbeeah Mohti
International Journal of Emerging Markets, 2023
ASYMMETRIC RESPONSE OF DISAGGREGATED IMPORT DEMAND TO EXCHANGE RATE MOVEMENTS: A SMALL OPEN ECONOMY PERSPECTIVE
KHURRUM S. MUGHAL, SADDAM ILYAS, YASIR TARIQ MOHMAND, FAHEEM ASLAM, MUKHTAR UL HASAN
Singapore Economic Review, 2023
Temporal changes in global stock markets during COVID-19: an analysis of dynamic networks
Kashif Zaheer, Faheem Aslam, Yasir Tariq Mohmand, Paulo Ferreira
China Finance Review International, 2023
The footprints of Russia–Ukraine war on the intraday (in)efficiency of energy markets: a multifractal analysis
Faheem Aslam, Skander Slim, Mohamed Osman, Ibrahim Tabche
Journal of Risk Finance, 2023
On the inner dynamics between Fossil fuels and the carbon market: a combination of seasonal-trend decomposition and multifractal cross-correlation analysis
Faheem Aslam, Ijaz Ali, Fahd Amjad, Haider Ali, Inza Irfan
Environmental Science and Pollution Research, 2023
The nexus between twitter-based uncertainty and cryptocurrencies: A multifractal analysis
FAHEEM ASLAM, ZIL-E-HUMA, RASHIDA BIBI, PAULO FERREIRA
Fractals, 2023
Dependence structure across equity sectors: Evidence from vine copulas
Faheem Aslam, Ahmed Imran Hunjra, Elie Bouri, Khurrum Shahzad Mughal, Mrestyal Khan
Borsa Istanbul Review, 2023
Islamic vs. Conventional Equity Markets: A Multifractal Cross-Correlation Analysis with Economic Policy Uncertainty
Faheem Aslam, Paulo Ferreira, Haider Ali, Arifa, Márcia Oliveira
Economies, 2023
Analysis of the Impact of COVID-19 Pandemic on the Intraday Efficiency of Agricultural Futures Markets
Faheem Aslam, Paulo Ferreira, Haider Ali
Journal of Risk and Financial Management, 2022
Insurance fraud detection: Evidence from artificial intelligence and machine learning
Faheem Aslam, Ahmed Imran Hunjra, Zied Ftiti, Wael Louhichi, Tahira Shams
Research in International Business and Finance, 2022
The use of transfer entropy to analyse the comovements of European Union stock markets: a dynamical analysis in times of crises
Revista Galega De Economia, 2022
Interplay multifractal dynamics among metal commodities and US-EPU
Leonardo H.S. Fernandes, José W.L. Silva, Fernando H.A. de Araujo, Paulo Ferreira, Faheem Aslam, Benjamin Miranda Tabak
Physica A Statistical Mechanics and Its Applications, 2022
Classification of m-payment users’ behavior using machine learning models
Faheem Aslam, Tahir Mumtaz Awan, Tayyba Fatima
Journal of Financial Services Marketing, 2022
Herding behavior during the Covid-19 pandemic: a comparison between Asian and European stock markets based on intraday multifractality
Faheem Aslam, Paulo Ferreira, Haider Ali, Sumera Kauser
Eurasian Economic Review, 2022
Application of Multifractal Analysis in Estimating the Reaction of Energy Markets to Geopolitical Acts and Threats
Faheem Aslam, Paulo Ferreira, Haider Ali, Ana Ercília José
Sustainability Switzerland, 2022
Calendar Anomalies in Islamic Frontier Markets
Faheem Aslam, Ahmed Imran Hunjra, Tahar Tayachi, Peter Verhoeven, Yasir Tariq Mohmand
Sage Open, 2022
Cross-correlations between economic policy uncertainty and precious and industrial metals: A multifractal cross-correlation analysis
Faheem Aslam, Zil-e-huma, Rashida Bibi, Paulo Ferreira
Resources Policy, 2022
Interactive websites of e-malls instigate intentions to generate e-WoM
Tahir Mumtaz Awan, Tayyaba Latif, Faheem Aslam, Tayyba Fatima
International Journal of Electronic Marketing and Retailing, 2022
Changes in Community Mobility and Covid-19 Cases: A Multiscale Analysis for Portuguese Districts
Revista Portuguesa De Estudos Regionais, 2022
COVID-19 pandemic and the dependence structure of global stock markets
Faheem Aslam, Khurrum S. Mughal, Saqib Aziz, Muhammad Farooq Ahmad, Dhoha Trabelsi
Applied Economics, 2022
A new vision about the influence of major stock markets in CEEC indices: a bidirectional dynamic analysis using transfer entropy
Paulo Ferreira, Andreia Dionísio, Dora Almeida, Derick Quintino, Faheem Aslam
Post Communist Economies, 2022
The Effect of Enterprise Risk Management on Ameliorating Competitive Advantage: A Cross-Sectional Study of Software Houses in Pakistan
Sameeta Javaid, Faheem Aslam
Pertanika Journal of Social Sciences and Humanities, 2021
Money Multiplier Bias Due to Informal Sector: An Extension of the Existing Money Multiplier
Khurrum S. Mughal, Friedrich G. Schneider, Faheem Aslam, Alishba Tahir
South Asian Journal of Macroeconomics and Public Finance, 2021
Is Brazilian music getting more predictable? A statistical physics approach for different music genres
Paulo Ferreira, Derick Quintino, Bruna Wundervald, Andreia Dionísio, Faheem Aslam, Ana Cantarinha
Physica A Statistical Mechanics and Its Applications, 2021
Application of Weighted Linear Combination approach in a Geographical Information System environment for nuclear power plant site selection: the case of Ghana
Ephraim Bonah Agyekum, Fahd Amjad, Faheem Aslam, Amjad Ali
Annals of Nuclear Energy, 2021
Modeling dynamic multifractal efficiency of us electricity market
Haider Ali, Faheem Aslam, Paulo Ferreira
Energies, 2021
Investigating the causal relationship between transport infrastructure, economic growth and transport emissions in Pakistan
Yasir Tariq Mohmand, Fahad Mehmood, Khurrum Shahzad Mughal, Faheem Aslam
Research in Transportation Economics, 2021
Stock Market Volatility and Terrorism: New Evidence from the Markov Switching Model
Faheem Aslam, Hyoung-Goo Kang, Khurrum Shahzad Mughal, Tahir Mumtaz Awan, Yasir Tariq Mohmand
Peace Economics Peace Science and Public Policy, 2021
Forecasting Islamic securities index using artificial neural networks: performance evaluation of technical indicators
Faheem Aslam, Khurrum S. Mughal, Ashiq Ali, Yasir Tariq Mohmand
Journal of Economic and Administrative Sciences, 2021
Prediction of COVID-19 confirmed cases in indo-pak sub-continent
Faheem Aslam, Tahir Mumtaz Awan, Ruqia Khan, Maira Aslam, Yasir Tariq Mohmand
Journal of Infection in Developing Countries, 2021
Intraday volatility spillovers among european financial markets during COVID-19
Faheem Aslam, Paulo Ferreira, Khurrum Shahzad Mughal, Beenish Bashir
International Journal of Financial Studies, 2021
Investigating the implications of covid-19 on pm2.5 in Pakistan
Hassaan Sipra, Faheem Aslam, Jabir Hussain Syed, Tahir Mumtaz Awan
Aerosol and Air Quality Research, 2021
Extreme value theory and covid-19 pandemic: Evidence from india
Economic Research Guardian, 2021
Policy Analytics-Insights from Pakistan and India Water Policies
Faheem Aslam, Aneel Salman, Inayatullah Jan, Sarah Siddiq Aneel
Sarhad Journal of Agriculture, 2021
Forecasting Stock Market Using Machine Learning Approach Encoder-Decoder ConvLSTM
Khurum Iqbal, Ali Hassan, Syed Shah Mir Ul Hassan, Shuaib Iqbal, Faheem Aslam, Khurrum S Mughal
Proceedings 2021 International Conference on Frontiers of Information Technology Fit 2021, 2021
The footprints of COVID-19 on Central Eastern European stock markets: an intraday analysis
Faheem Aslam, Francisca Nogueiro, Mariana Brasil, Paulo Ferreira, Khurram Shahzad Mughal, Beenish Bashir, Saima Latif
Post Communist Economies, 2021
A complex networks based analysis of jump risk in equity returns: An evidence using intraday movements from Pakistan stock market
Faheem Aslam, Yasir Tariq Mohmand, Saqib Aziz, Jamal Ouenniche
Journal of Behavioral and Experimental Finance, 2020
Sentiments and emotions evoked by news headlines of coronavirus disease (COVID-19) outbreak
Faheem Aslam, Tahir Mumtaz Awan, Jabir Hussain Syed, Aisha Kashif, Mahwish Parveen
Humanities and Social Sciences Communications, 2020
On the efficiency of foreign exchange markets in times of the COVID-19 pandemic
Faheem Aslam, Saqib Aziz, Duc Khuong Nguyen, Khurrum S. Mughal, Maaz Khan
Technological Forecasting and Social Change, 2020
Network analysis of global stock markets at the beginning of the coronavirus disease (Covid-19) outbreak
Faheem Aslam, Yasir Tariq Mohmand, Paulo Ferreira, Bilal Ahmed Memon, Maaz Khan, Mrestyal Khan
Borsa Istanbul Review, 2020
Investigating long-range dependence of emerging asian stock markets using multifractal detrended fluctuation analysis
Faheem Aslam, Saima Latif, Paulo Ferreira
Symmetry, 2020
Prediction of daily COVID-19 cases in European countries using automatic ARIMA model
Tahir Mumtaz Awan, Faheem Aslam
Journal of Public Health Research, 2020
Evidence of intraday multifractality in european stock markets during the recent coronavirus (Covid-19) outbreak
Faheem Aslam, Wahbeeah Mohti, Paulo Ferreira
International Journal of Financial Studies, 2020
Predicting wheat production in pakistan by using an artificial neural network approach
Faheem Aslam, Aneel Salman, Inayatullah Jan
Sarhad Journal of Agriculture, 2019
The impact of terrorism on financial markets: Evidence from Asia
FAHEEM ASLAM, AMIR RAFIQUE, ANEEL SALMAN, HYOUNG-GOO KANG, WAHBEEAH MOHTI
Singapore Economic Review, 2018
How Different Terrorist Attacks Affect Stock Markets
Faheem Aslam, Hyoung-Goo Kang
Defence and Peace Economics, 2015

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