Contagion modeling between the financial and insurance markets with time changed processes

Area of Science:

• Quantitative Finance
• Insurance Risk Management
• Stochastic Modeling

Background:

• Financial and non-life insurance markets exhibit complex interdependencies.
• Understanding contagion effects is crucial for robust asset-liability management (ALM).
• Existing models may not fully capture delayed co-movements.

Purpose of the Study:

• To analyze the impact of contagion between financial and non-life insurance markets on ALM.
• To model the indirect dependence between these markets.
• To investigate the drivers of delayed co-movements.

Main Methods:

• Modeling asset returns using time-changed Brownian motion.
• Modeling non-life insurance claims using time-changed jump processes.
• Utilizing stochastic clocks based on mutually self-exciting processes to capture indirect dependence.

Main Results:

• The developed model demonstrates delayed co-movements between financial and non-life insurance markets.
• This indirect dependence is influenced by stochastic clocks derived from self-exciting processes.
• The model captures contagion effects relevant to ALM.

Conclusions:

• Contagion between financial and non-life insurance markets significantly impacts ALM policies.
• The proposed stochastic model effectively captures delayed co-movements.
• Events like natural disasters, epidemics, and recessions can trigger these co-movements, necessitating advanced risk management strategies.