Is gold a Sometime Safe Haven or an Always Hedge for Equity Investors? A Markov-Switching CAPM Approach for US and UK Stock Indices

This paper re-examines gold's role as a tool for investors to manage their portfolio risk. We begin by assessing gold's average relationship to an investor's diversified equity portfolio by applying the basic Capital Asset Pricing Model (CAPM) to UK and US equity indices. Next, we apply a Markov-switching CAPM to assess whether two distinct states exist between gold's relationship with the Market Portfolio. This approach allows the data to determine if two separate states exist and, if so, whether one state matches the definition of a Safe Haven from the literature. Using this new approach, we find that gold is consistently a Hedge, but that no distinct Safe Haven state exists between gold and UK or US stock markets

Costly Sequential Experimentation and Project Valuation with an Application to Health Technology Assessment

We study the optimal investment/abandonment decision for a project, where costly sequential experimentation provides information about its true profitability. We derive the optimal decision rule by appropriately extending the Bayesian framework of sequential hypothesis testing. The optimal decision time takes the form of the first exit time of a particular inaction region. We find that increased noise in the observations lowers the value of the project, and that the effect on the expected time at which a decision is taken is ambiguous. Delays in observations affect both project value and the inaction region. The model is illustrated with a health technology assessment application using data on standard versus robot-assisted laporascopic prostatectomy

Pareto Optimality and Existence of Quasi-Equilibrium in Exchange Economies with an Indefinite Future

We study the attainability of Pareto optimal allocations and existence of quasi-equilibrium in exchange economies where agents have utility functions that value consumption in an indefinite future. These utility functions allow for fairly general discounting of consumption over finite time horizons, but add a utility weight to the bulk of the consumption sequence, which we identify with the indefinite future. As our commodity space we use the space of all convergent sequences with the limit of the sequence representing consumption in the indefinite future. We derive a necessary and sufficient condition for the attainability of the Pareto optimal allocations. This condition implies that efficiency can only be attained if consumers’ valuations of time are very similar. Our proof relies on the existence of an interior solution to certain infinite dimensional optimization problems. If the condition is not met, no interior quasi-equilibria exist. We extend the model to include consumers with Rawlsian-like maximin utility

Green Investment under Policy Uncertainty and Bayesian Learning

Many countries have introduced support schemes to accelerate investments in renewable energy (RE). Experience shows that, over time, retraction or revision of support schemes become more likely. Investors in RE are greatly affected by the risk of such subsidy changes. This paper examines how investment behavior is affected by updating a subjective belief on the timing of a subsidy revision, incorporating Bayesian learning into a real options modeling approach. We analyze a scenario where a retroactive downward adjustment of fixed feed-in tariffs (FIT) is expected through a regime switching model. We find that investors are less likely to invest when the arrival rate of a policy change increases. Further, investors prefer a lower FIT with a long expected lifespan. We also consider an extension where, after retraction, electricity is sold in a free market. We find that if policy uncertainty is high, an increase in the FIT will be less effective at accelerating investment. However, if policy risk is low, FIT schemes can significantly accelerate investment, even in highly volatile markets