This article comments on the paper “Less-expensive long-term annuities linked to mortality, cash and equity” by Kevin Fergusson and Eckard Platen, appearing in this issue of the Annals of Actuarial Science. It adds two perspectives to their thought-provoking contribution. The first is a similarity to some recent work in quantitative finance on “deep hedging” that leverages machine learning models to find the cheapest replication strategy for a derivative payoff in a largely model-free setting. The second perspective engages with some of the interesting implications of their approach and draws parallels to literature in asset pricing and macro-finance. These perspectives point to the potential need for more fundamental shifts than the authors of the paper are advertising.

In this paper, I use the case of financial economics to show how an innovative idea can shape a research agenda. I focus on why the efficient-market hypothesis, crystallized in Eugene Fama’s research, acquired core theoretical status in the discipline of financial economics, whereas the Capital Asset Pricing Model, championed by, among others, Fischer Black, did not. I draw attention both to differences in the networks propagating these models, in particular differences in cohesion and coherence, and to differences in the methodologies underlying the models. I argue that Fama’s use of “data-dredging” techniques and frequentist statistics increased the coherence of the intellectual circle around him, turning the analysis of efficiency into a collective project oriented towards the discovery of objective properties. By contrast, Black’s adoption of more subjectivist methods exacerbated the individualistic tendencies of his approach and his network, increasing the incoherence of his research group.

This paper is divided into three parts. Taken together, the three parts intend to provide the reader with an overview of the first 101 years of financial economics, with particular attention on those developments that are of special interest to actuaries. In Section 1, S.F. Whelan attempts to capture the flavour of the subject and, in particular, to give an overview or road map of this discipline, highlighting actuarial input. In Section 2, D.C. Bowie gives a concise and self-contained overview of the Modigliani and Miller insights (or MM Theorems, as they are often known). In Section 3, A.J. Hibbert considers the novel option pricing method proposed by Black, Merton, and Scholes. These two insights are highlights of this newscience, and, in both cases, contradict our intuition.

T.S. Elliot, the mathematically trained poet, described the darkness that intercedes between the idea and the action as the ‘shadow’. There is a shadow to be considered between these insights and their application. The demonstration of the results requires, of course, some idealised circumstances, and therefore the extent and degree of their applicability to the non- idealised problems encountered by actuaries requires some delicate considerations. An attempt is made to outline these further considerations.

This paper addresses the fundamental issues in the construction and use of actuarial economic models, with specific reference to those described in the UK literature. Two approaches are considered: an empirical approach and a theoretical approach using financial economics. Although empirical testing is essential, the difficulties associated with it should not be underestimated. A theoretical framework can be used to limit the impact of these difficulties. However, economic modelling is further complicated by the lack of a reliable and comprehensive theoretical framework. This suggests that economic models are always likely to be inaccurate and consequently actuarial judgement is likely to be indispensable.

This paper shows how the powerful and flexible tool of stochastic modelling can be applied to a range of business decisions extending far beyond the asset allocation solutions that are common to many asset/liability modelling studies. The example used to demonstrate these techniques is a general insurance case study, but similar principles can be extended to many different business situations. At each stage of the analysis we consider the implications of modern financial theory on the management decision process together with a practical perspective on observed behaviour in the real world. Opportunities are taken to suggest directions in which further research may be of benefit to the actuarial profession.

There has recently been some debate about the usefulness of financial economics to the actuarial profession. The consensus appears to be that the techniques are potentially valuable, but the published material is not quite ‘oven ready’. Some development work is required before the material can be applied.

The author has carried out much of the necessary development work on behalf of various clients over the last few years. On some occasions the results have conflicted with more conventional actuarial methods. The main aim of the paper is to bring the new techniques into the public domain so that they can be properly discussed by the profession, and adopted more widely if appropriate.

The paper contains a number of worked examples using techniques developed by financial economists. The author has listed the computer code which generated the examples and deposited copies on the Internet, so that others can explore the issues with a minimal development overhead.

This paper considers some of the properties of the jump-equilibrium model suggested by Smith (1996). A more detailed description of the model's derivation is provided. The model is represented in a discrete time format and a number of statistics are derived and discussed.

In a world of transition for all our disciplines, actuaries can get and keep ahead of the changes by, first, getting our thinking right. Right behaviour and actions will follow. We will think about the needs of our employers and clients and present our findings more in the business context; we will look through their needs to the needs and interests of their employees and customers. We will grasp financial economics and learn banking thinking. The profession will raise issues of public interest and inform the debate.

The paper compares and contrasts the theories and methodologies of financial economics with generalisations drawn from practical experience of institutional investment management. A Dynamic Equilibrium Model is put forward as a much more realistic theoretical framework than the Sharpe Diagonal Model, a downside theory of risk is developed from sports analogies, and a detailed model of human behaviour, incorporating benchmark levels of ‘unintelligent’, ‘intelligent’, ‘optimal’ and ‘rational’ behaviour, is suggested as a replacement for the very restrictive simplifying assumptions of existing theories. On the basis of a classification system derived from parallels with the history of astronomy, it is concluded that, as a scientific framework, the current theories of financial economics are seriously incomplete, the two crucial areas of incompleteness being the absence of a downside theory of risk and the absence of a realistic model of human behaviour under conditions of risk and uncertainty.

In this paper, we identify the economic system in which occupational pension schemes operate. This system includes all parties to the pension arrangement, particularly the members of the scheme and the shareholders of the sponsoring company. This requires us to model the pension scheme not as a self-contained fund, but simultaneously alongside the company, and to recognise its interaction with other parties with financial interests in the scheme. Under this method, the stakes of the various parties aggregate to 100% of the assets of the company including the assets of the pension scheme. The power of this approach is that decisions taken in relation to the management of the pension scheme can be assessed by the effect they have on the way in which the overall economic value of the company is divided between stakeholders.