Background

Insurance firms across EU Member States are subject to prudential regulation to minimize the risk of insurer insolvency. This means they provide a safety net to a socially acceptable level, thereby protecting policyholders and maintaining market stability. This research project concerns the different approaches taken to portfolio regulation of life insurance firms, in particular the regulations imposed on asset allocation to mitigate investment risk.

There are essentially two types of regulations which are applied across the world. They are Quantitative Restrictions (QR), which impose explicit limits on holdings in risky asset classes, and the Prudent Person Rule (PPR), which requires firms to invest prudently and follow broad principles of portfolio diversification and asset-liability matching. The main objective of the project is to provide empirical evidence on whether QR leads to inferior investment outcomes, as the theory might suggest.

In unconstrained portfolio choice, rational portfolio managers are expected to choose portfolios which lie on the efficient frontier. This theoretical boundary traces out the minimum level of risk which needs to be incurred to achieve any level of expected return, reflecting optimal portfolios which exploit underlying correlations between assets. By limiting the range of assets or the amounts that can be invested in specific asset classes, investors are not able to fully take advantage of the diversification benefits that arise from the lack of correlation between each type and class of asset. So uniform restrictions on the type of assets can negatively impact on the performance of insurance firms' portfolios, creating a regulatory cost for firms.

Objective

On this basis, this research will aim to answer the following question:

To what extent do the restrictions on asset allocations under QR relative to PPR reduce the risk-adjusted returns that life insurance firms can achieve through their portfolio of assets?

Method

We investigate differences in investment returns across a sample of OECD countries which follow 'pure' PPR, 'pure' QR or a mix of the two regimes using firm level balance sheet data. This cross-country comparison builds on Davis (2001), which is largely a descriptive analysis of insurance fund returns based on aggregate data. We extend his work by adjusting for risk, given the need to control for variation in returns which is attributable purely to variation in risk targets. And by formulating a panel data econometric model which aims to isolate the impact of the QR regulation, holding constant all other factors which affect fund returns. Intuitively, this is important given that, for example, cross- country variation in asset market returns and volatilities will affect individual funds' returns and risks.