3 papers in the archive (2024), average empirical rigor 5.7/10, average math complexity 3.5/10. Quadrant mix: Philosophers ×1, Street Traders ×2.
Works mostly in Risk Management & Tail Risk, Fixed Income & Interest Rates.
Frequent co-authors: Fernando Acebes (3), David Poza (2), Javier Pajares (2), Adolfo Lopez-Paredes (2), David Curto (1).
Scores are our LLM-assisted heuristics (methodology), not peer review or citation counts. Author pages are generated from paper metadata; name variants may split one person across pages. arXiv author page →
Ordered by a blend of empirical rigor (60%) and math complexity (40%).
Obtaining a viable schedule baseline that meets all project constraints is one of the main issues for project managers. The literature on this topic focuses mainly on methods to obtain schedules that meet resource restrictions and, more recently, financial limitations. The methods provide different
In construction projects, contingency reserves have traditionally been estimated based on a percentage of the total project cost, which is arbitrary and, thus, unreliable in practical cases. Monte Carlo simulation provides a more reliable estimation. However, works on this topic have focused exclusi
Project managers need to manage risks throughout the project lifecycle and, thus, need to know how changes in activity durations influence project duration and risk. We propose a new indicator (the Activity Risk Index, ARI) that measures the contribution of each activity to the total project risk wh