X. Dai, S. Mouti, M. L. do Vale, S. Ray, J. Bohn, L. Goldberg. A resampling approach for causal inference on novel two-point time-series with application to identify risk factors for type-2 diabetes and cardiovascular disease. Statistics in Biosciences (SIBS), 2023.
C. R. Tramontt, S. Mouti, M. R. L. do Vale, X. Li, Christine Delon, S. Armes, R. Golubic, S. Ray. Do markers of adiposity and glycaemia mediate the association between low carbohydrate diet and cardiovascular risk factors: findings from the UK National Diet and Nutrition Survey (NDNS) 2008–2016. BMJ Nutrition, Prevention & Health, 2023.
L. Goldberg and S. Mouti, Sustainable investing and the cross-section of returns and maximum drawdown. The Journal of Finance and Data Science, Volume 8, 2022.
M. L. do Vale, L. Buckner, C. G. Mitrofan, C. R. Tramontt, S. K. Kargbo, A. Khalid, S. Ashraf, S. Mouti, X. Dai, and D. Unwin. A synthesis of pathways linking diet, metabolic risk and cardiovascular disease: a framework to guide further research and approaches to evidence-based practice. Cambridge University Press, 2021.
A. Kalife. G. L. Ruiz, S. Mouti, and X. Tan, Optimal behavior strategy in the Guaranteed Minimum Income Benefit product. Insurance Markets and Companies, 2018.
G. Livieri, S. Mouti, A. Pallavicini, and M. Rosenbaum, Rough volatility: Evidence from option prices. IISE Transactions, Volume 50, 2018.
A. Kalife and S. Mouti, On optimal options book execution strategies with market impact. Market Microstructure and Liquidity, Volume 6, Issue 3, December 2016
A. Kalife, S. Mouti and X. Tan, Minimizing the market impact of hedging insurance liabilities within risk appetite constraints. Insurance Markets and Companies: Analysis and Actuarial Computations, Volume 6, Issue 2, 2015
L. Wang, A. Kalife, X. Tan, B. Bouchard, S. Mouti. Understanding guaranteed minimum withdrawal benefit: a study on financial risks and rational lapse strategy. Insurance Markets and Companies, 6, Issue 1, 2015.
A. Kalife, L. Goudenege and S. Mouti, Managing gap risks in iCPPI for life insurance companies: a risk-return cost analysis. Insurance Markets and Companies: Analysis and Actuarial Computations, Volume 5, Issue 2, 2014
A. Kalife, S. Mouti and L. Wang, Financial risk management and the rational lapse strategy in life insurance policies. Insurance Markets and Companies: Analysis and Actuarial Computations, Volume 4, Issue 2, 2013
S. Mouti. Rough volatility: Evidence from range volatility estimators. Working paper, 2023
A. Kalife, L. Goodenège, T. Xiaolu, S. Mouti, M. Bellmane. Sustainable life insurance: Managing risk appetite for insurance savings and retirement products. CRC Press, 2023.
Objective: Investigating the causal effect of health conditions on survival probability using time-to-event analysis. This research primarily utilizes data from the UK BioBank.
Methodology: The study employs the potential outcome framework to model individual survival times under different scenarios (treatment vs. control). This approach accounts for the difference in potential outcomes as a measure of the treatment's causal effect.
Challenges and Approaches: Addressing common challenges in survival analysis, such as censoring, where the event of interest (e.g., death) isn't observed during the study period. The research also involves adjusting conventional methods to accommodate time-varying treatments and confounders.
Preliminary Results: Initial findings have explored the effects of factors like BMI and cholesterol. Ongoing work includes developing methods to account for mediators.
Applications: The insights gained are particularly relevant for insurance companies in pricing health insurance products, potentially leveraging smart monitors to track physical activity, medication adherence, and nutrition habits.
Objective: Exploring the application of causal inference in factor investing. This research aims to differentiate between association and causation in financial economics, addressing potential false discoveries in investment strategies.
Context and Challenge: Factor investing involves identifying risk factors that drive asset pricing models. However, there is often confusion between correlation and causation, leading to misguided investment strategies. This research scrutinizes such instances, particularly in ESG (Environmental, Social, and Governance) investing.
Methodology: Utilizing causal inference to assess the impact of actions on stock performance, particularly in ESG investing. This includes exploring counterfactual outcomes, where the performance of stocks is analyzed under hypothetical scenarios.
Approaches: Employing techniques like matching individuals in treated and control groups based on similar characteristics, and using synthetic control methods to create composite profiles for comparative analysis.
Applications: This research is particularly relevant in evaluating the true impact of ESG actions on stock performance, providing deeper insights for investors and policymakers.
Overview: Addressing the critical issue of electricity production through fossil fuels and its contribution to global emissions. This research focuses on the procurement of renewable energy as a strategy to combat the adverse effects of climate change.
Challenges: The project confronts several challenges, including the intermittent nature of renewable energy sources, the need for consistent green energy availability, and the intricacies of corporate renewable procurement strategies.
Procurement Strategies: Investigating various procurement strategies such as competitive solicitations, bilateral contracts, feed-in tariffs (FITs), and energy auctions. These are evaluated for cost-efficiency, procurement effectiveness, market accessibility, and integration with utility planning.
Approach: The research is centered on developing renewable energy portfolios that aim for specific hourly CFE performance scores. This involves a probabilistic approach with scenario analysis and probability constraints.
Applications: The methodology is designed to be adaptable for multiple corporates within the same region, allowing them to collectively meet their electricity requirements from shared renewable sources. Exploring the expansion of this framework into a competitive auction-based system, where bids are prioritized based on their value proposition.