Scandinavian Actuarial Journal
Scope & Guideline
Uncovering transformative insights in economics and statistics.
Introduction
Aims and Scopes
- Risk Modeling and Assessment:
The journal emphasizes the development and application of models for assessing various types of risks, including life, health, and financial risks. This includes advanced stochastic models, collective risk models, and methodologies for estimating ruin probabilities. - Investment Strategies and Financial Engineering:
Research on optimal investment strategies, especially in the context of pension funds and insurance products, is a core focus. This includes studies on asset-liability management and the interplay between insurance and investment. - Insurance Pricing and Valuation:
The journal covers methodologies for pricing insurance products, including variable annuities and reinsurance contracts. It explores innovative approaches to valuation that incorporate complex financial and risk factors. - Statistical and Computational Methods:
There is a strong emphasis on the use of statistical techniques, machine learning, and computational methods in actuarial science. This includes applications of Bayesian methods, copula models, and ensemble forecasting techniques. - Socioeconomic Impacts and Policy Design:
The journal also addresses the socioeconomic implications of actuarial practices, exploring topics such as demographic disparities in insurance pricing and the design of pension systems to enhance financial security.
Trending and Emerging
- Cyber Risk and Data Security:
Recent publications have increasingly focused on cyber risk modeling and the implications for insurance portfolios. This trend underscores the importance of addressing new risks associated with digital transformation and data breaches. - Advanced Machine Learning Techniques:
There is a significant uptick in the application of machine learning and artificial intelligence in actuarial science, particularly in pricing, forecasting, and risk assessment. This reflects a broader trend towards data-driven decision-making in the industry. - Intergenerational Risk Sharing and Pension Design:
Research on intergenerational risk sharing within pension systems has gained traction, indicating a growing interest in sustainable pension design that considers the long-term implications for multiple generations. - Complex Dependencies in Risk Models:
The journal is witnessing an increase in the exploration of complex dependencies among risks, particularly through the use of copula models and multivariate approaches, which enhance the understanding of joint risks in insurance. - Sustainability and Environmental Risks:
Emerging themes related to sustainability, including the assessment of environmental risks and their impact on insurance products, are becoming more prevalent, reflecting a shift towards incorporating social responsibility into actuarial practices.
Declining or Waning
- Traditional Risk Models:
There is a noticeable decline in the publication of papers focused solely on traditional risk models, such as basic actuarial models that do not incorporate advanced dependencies or modern statistical techniques. - General Mortality Forecasting:
While mortality forecasting remains a critical area, there is a shift away from simpler mortality models towards more complex, hybrid approaches. This indicates a waning interest in basic methodologies that do not integrate newer statistical advancements. - Static Insurance Pricing Models:
Static models for insurance pricing that do not consider dynamic factors or advanced data analytics are becoming less common. The focus is shifting towards more dynamic and adaptive models that incorporate real-time data and predictive analytics.
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