Strategic thinking

23

JANUARY 2025

12:00

Strategic thinking is thinking for the future. But that means understanding what the future and time are. Therefore, strategic thinking is a skill any manager should have to develop strategies for the future of the company. Strategic thinking is valuable for each individual in order to have success in his/her career and personal life.

The place of circular economy in territorial development processes

11

DECEMBER

14:30

Development can no longer be understood without taking into account the dimensions of sustainability, such as climate change, the loss of biodiversity or soil erosion and the depletion of natural resources. But how can the slogan "Think global and act local" be made concrete? How can we really act at the local level? In this context, the circular economy appears to be a credible solution, because it spares as much as possible the objectives of sustainable development and the preservation of the planet. In a way, it makes it possible both to setup production activities and therefore to maintain or develop jobs at the local level, and also to limit the use and transport of resources, thanks to a system of control of uses and recycling of materials, which remains virtuous in environmental terms, because they are grounded and territorially based.

The connections world the future development of asian economies

20

SEPTEMBER

13:45

Modern Asia thrives on tight business-political networks, driving mutual gains but also entrenching market power, stifling competition, and fueling inequality. These issues threaten growth and stability. To secure the future, the authors urge reforms to dismantle these connections and foster a sustainable system.

An empirical inquiry into the redistributive nature of energy price shocks

30

MAY

14:30

A fundamental question in macroeconomy is to study how of oil price variations affect the functional distribution of income and through which channel. In this talk, we will identify these channels and we will provide and discuss reliable estimates for each of them.

How LLM models work and how to get the most out of them

16

MAY

16:30

The seminar will focus on the topics of Leadership and Innovation, that play a critical role to enable people reaching the skill-set required to lead a company.

Gamifying Education: Learning about Supply Chain Management Through Simulation

21

MAY

12:30

The presentation highlights a game designed for operations and supply chain management courses, where students simulate distributing medical supplies during a bioterrorism attack. Through this game, students engage with complex mathematical concepts. Preliminary survey results indicate positive student feedback. The presentation concludes by suggesting further research and encouraging other instructors to use similar games in their teaching.

The capital-on-capital cost in solvency II risk margin

18

DECEMBER

11:30

The presentation examines the capital-on-capital cost in insurance liability valuation and its effect on risk margin (RM) calculations. Capital-on-capital covers risks from future regulatory capital changes, distinct from cash-flow uncertainties. We compare two valuation approaches: one using backward iteration of the SCR risk measure and another based on additive-SCR (ASCR). Applying this to long-term equity-linked life insurance, we highlight the significant role of capital-on-capital in long-term liabilities, providing insights into RM and capital managemen

Numerical methods for lambda quantiles: robust evaluation and portfolio optimization

18

DECEMBER

12:15

Lambda quantiles, originally introduced as lambda value at risk, generalise the classical value at risk by allowing for a variable confidence level. In this article, we examine their numerical properties. We begin by developing a globally convergent Newton-based algorithm for evaluating lambda quantiles, named Λ-Newton-Bis. We prove convergence under mild assumptions, including cases with discontinuities, and local convergence under stronger local regularity conditions. Additionally, we consider an optimal portfolio allocation problem using lambda quantiles, proposing two alternative solution approaches based on the Λ-Newton-Bis algorithm. Several examples compare the performance of the two approaches and confirm the numerical efficiency of Λ-Newton-Bis.

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