Project 1: Modelling regulatory uncertainty in financial decisions with applications to taxation and insurance
Work Package 1:
This Work Package introduces a simple model to illustrate how regulatory uncertainty affects investment decisions. We distinguish between two sources of uncertainty: random market fluctuations and ambiguity about the true return of assets, which can arise from regulatory shocks. Our approach allows investors to treat risk and model ambiguity differently, reflecting varying attitudes toward uncertainty.
If both types of uncertainty are perceived in the same way, the problem reduces to a standard Bayesian setting. Otherwise, more advanced methods are needed. By reformulating the problem using recent theoretical advances, we can separate the effects of regulatory ambiguity from ordinary risk aversion. This makes it possible to compute semi-explicit solutions and to analyze numerically how regulatory shocks influence investment strategies.
Optimal asset allocation under model ambiguity
In this Work Package, we study investment problems that incorporate regulatory uncertainty in the form of risk constraints on wealth. Traditional constraints, such as Value-at-Risk or Expected Shortfall, impose limits on terminal wealth or on the wealth process at specific points in time. However, regulatory uncertainty arises when the precise form of these constraints is not predictable, for example due to unknown model parameters or changing thresholds.
A practical illustration is provided by Solvency II, where uncertainty may concern the choice of risk measure itself or the threshold levels that define default events. To address this challenge, we develop models that account for such ambiguity in regulatory requirements and analyze how it affects investment strategies.
Work Package 2:
Regulatory uncertainty concerning risk constraints
This Work Package examines optimal asset allocation under tax uncertainty, focusing on risky investments such as R&D or highly innovative businesses. These investments are affected by complex tax regulations, where incentives depend on conditions and future profits, and traditional models largely consider only simple tax rates.
We extend this literature by analyzing how regulatory risk constraints, behavioral frictions, and tax uncertainty interact in investment decisions. Our framework incorporates loss aversion, advance tax rulings, and information asymmetry between investors and tax authorities, allowing us to study their combined effects on investment behavior and the determination of fees for tax certainty.
This model provides a comprehensive perspective on the interplay between regulatory constraints, behavioral factors, and tax uncertainty, offering insights for both theory and practice.
Work Package 3:
Optimal investment under tax uncertainty
Work Package 4:
Changes in statutory pension legislation, reflecting political uncertainty, can influence an insurance company’s operations, but the impact is less direct than uncertainty regarding solvency regulation. Solvency regulation, such as Solvency II, directly dictates the capital requirements insurers must maintain to limit insolvency risk, immediately affecting investment strategies and risk assessments. Since the implementation of Solvency II, regulatory tools are still evolving, and inconsistencies across jurisdictions create significant regulatory uncertainty that has been underexplored in the literature.
We analyze collective investment problems under regulatory uncertainty, considering situations where investors delegate asset management to fund managers, either due to professional expertise or investment inertia. Using a collective utility framework, the fund manager optimizes investment strategies while balancing the risk preferences of all participants. Regulatory uncertainty arises in the specification of risk constraints, such as Value-at-Risk or Expected Shortfall measures, which underpin regulatory capital requirements. By incorporating these uncertainties, our framework allows us to study how regulatory ambiguity affects collective investment decisions from both policyholders’ and insurers’ perspectives.
Optimal (collective) investment under uncertain VaR or ES constraint
In this project, we investigate how regulatory uncertainty influences asset allocation decisions. Such uncertainty arises from changes in regulatory frameworks, as seen in initiatives like Basel III, Solvency II, or international tax reforms such as the OECD’s BEPS plan. It can create unpredictability in both the dynamics of underlying assets and the regulatory constraints that govern investment. These uncertainties shape the strategies of financial institutions and firms and can have significant effects on asset prices. We conceptualize regulatory uncertainty as model ambiguity, distinct from model risk, and address it by modeling uncertain parameters in asset dynamics and within risk constraints. This approach advances theoretical work on optimal asset allocation under regulatory uncertainty and provides predictions on how regulatory frameworks might be shaped. We further apply this perspective to decision problems in taxation, insurance, and pension-related collective investment. The research objectives lead to the following Work Packages:
(consultative role)
Principal Investigators: