Random Premiums Risk Process with Dividends and Investment

We extend the discrete time risk model studied in [1] by introducing an investment component and show that the combined dividend-investment model provides higher expected returns for both the insurer and the shareholders. Furthermore, we show that given two strategies that have the same probability of ultimate ruin on the infinite time horizon, the strategy with larger initial capital and smaller loading factor is less risky than the strategy with smaller initial capital and larger loading factor in that it has a smaller lower bound for ruin probability on the finite time horizon.

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Publication Details

Journal
Journal of Mathematical Finance
Published
2025-01-01
DOI
https://doi.org/10.4236/jmf.2025.152018
Primary Topic
Insurance and Financial Risk Management
Type
article
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article

Random Premiums Risk Process with Dividends and Investment

Andrzej Korzeniowski, Enoch J. Dangbe
Journal of Mathematical Finance
Insurance and Financial Risk Management
article

Random Premiums Risk Process with Dividends and Investment

Andrzej Korzeniowski, Enoch J. Dangbe
article en

Abstract

We extend the discrete time risk model studied in [1] by introducing an investment component and show that the combined dividend-investment model provides higher expected returns for both the insurer and the shareholders. Furthermore, we show that given two strategies that have the same probability of ultimate ruin on the infinite time horizon, the strategy with larger initial capital and smaller loading factor is less risky than the strategy with smaller initial capital and larger loading factor in that it has a smaller lower bound for ruin probability on the finite time horizon.

Journal of Mathematical FinanceVol. 15(02)
The University of Texas at Arlington (US)
Openalex Percentile: Top 83%
Insurance and Financial Risk Management
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Random Premiums Risk Process with Dividends and Investment — Andrzej Korzeniowski, Enoch J. Dangbe · Journal of Mathematical Finance (2025) | TGRS Research Map | TGRS