Date: October 14, 2022
Time: 12:15-13:45
Past Session

Bet on a bubble asset? An optimal portfolio allocation strategy

Speaker: Arthur Thomas, Associate Professor in Economics, Laboratoire d'Economie de Dauphine (LEDA)

Coauthors: Gilles de Truchis, Elena Dumitrescu, Sebastien Fries

Abstract

We discuss portfolio allocation when one asset exhibits phases of locally explosive behavior. We model the conditional distribution of such an asset through mixed causal-non-causal models which mimic well the speculative bubble behaviour. Relying on a Taylor-series-expansion of a CRRA utility function approach, the optimal portfolio(s) is(are) located on the mean-variance-skewness-kurtosis efficient surface. We analytically derive these four conditional moments and show in a Monte-Carlo simulations exercise that incorporating them into a two-assets portfolio optimization problem leads to substantial improvement in the asset allocation strategy. All performance evaluation metrics support the higher out-of-sample performance of our investment strategies over standard benchmarks such as the mean-variance and equally-weighted portfolio. An empirical illustration using the Brent oil price as the speculative asset confirms these findings.


The Origins of Commodity Price Fluctuations

Speaker: Evgenia Passari, Associate Professor in finance, DRM Finance, Dauphine

Coauthors: Sarah Mouabbi (Banque de France) and Adrien Rousset Planat (London Business School)

Abstract

We build novel indexes of commodity price developments by simulating news-reading. Our proposed computer-based, narrative approach is flexible, unified and spans the global commodity market, including energy, industrial and precious metals, and agricultural commodities. Empirical evidence and human readings of news articles indicate that our indexes capture commodity-price supply and demand components. Index-peaks track the post-crisis collapse of commodity markets, other market-specific developments, as well as the recent COVID-19 crisis. The richness of news content allows us to decompose the supply and demand indexes into a number of key determinants that shaped commodity markets since the beginning of the 21st century, including business cycle effects, geopolitical risk, natural disasters, and climate change considerations. Preliminary results reveal that the nature of commodity price movements matters for macroeconomic outcomes, firms' decisions, and asset prices.