City Research Online

Abstract

This Thesis contributes to the study of the links between expectations, fundamentals, and asset returns using the rich empirical setup offered by commodity markets. The three Chapters, constituting this work, analyse empirically how expectations are formed and what are the implications of departures from perfect rational expectations on returns predictability. Monte- Carlo experiments are also used to rationalise and to give an economic interpretation to the empirical findings. In the First chapter, we show that survey-based expectations of returns are strongly correlated with past price variations, but not with fundamentals and can be largely explained by time-series momentum and value factors. Furthermore, we find that expectations have positive, but not significant correlation with future realised returns, which implies little predictive power. Using a Monte-Carlo experiment, we show that both results can also be generated by rational individuals provided the existence of extrapolative momentum traders and little predictability of fundamentals. Finally, our analysis also suggests that survey-based expectations can have a crucial role to understand better the dynamics of trading flows and the drivers of the option implied volatility risk premium. In the second Chapter, we investigate the dynamics of the ex-ante risk premia for different commodities and maturities through the lens of a model of rational learning in which expected future spot prices are revised in line with past prediction errors and changes in aggregate economic growth. The main results show that time-varying risk premia are predominantly driven by market activity and financial risks. More generally, we provide evidence of heterogeneity in the dynamics of factor loadings, both across commodities and time horizons. Finally, we show that the model-implied expectations are consistent with the cross-sectional average of Bloomberg professional analysts’ forecasts. In the third Chapter, we exploit the peculiarities of commodity markets to show that fundamental news about global growth is reflected into prices, but not instantaneously. News on economic activity can be filtered in real-time from commodity prices, but such news takes several months before being fully incorporated into prices, leading to returns predictability. Coherently with the theories of overreaction and underreaction to news, we show using simulated data that the results obtained can be explained by the existence of latecomers, who process information with a delay, and momentum traders.

Publication Type:	Thesis (Doctoral)
Subjects:	H Social Sciences > HG Finance
Departments:	Bayes Business School > Finance Doctoral Theses Bayes Business School > Bayes Business School Doctoral Theses

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