We present a self-consistent model for explosive financial bubbles, which combines a mean-reverting volatility process and a stochastic conditional return which reflects nonlinear positive feedbacks and continuous updates of the investors' beliefs and sentiments. The conditional expected returns...

We present a careful analysis of possible issues of the application of the self-excited Hawkes process to high-frequency financial data and carefully analyze a set of effects that lead to significant biases in the estimation of the "criticality index'' n that quantifies the degree of endogeneity...

We introduce a novel description of the dynamics of the order book of financial markets as that of an effective colloidal Brownian particle embedded in fluid particles. The analysis of a comprehensive market data enables us to identify all motions of the fluid particles. Correlations between the...

We report strong evidence that changes of momentum, i.e. "acceleration", defined as the first difference of successive returns, provide better performance and higher explanatory power than momentum. The corresponding Γ-factor explains the momentum-sorted portfolios entirely but not the reverse....

We introduce a model for portfolio selection with an extendable investment universe where the agent faces a trade-off between exploiting existing and exploring for new investment opportunities. An agent with mean-variance preferences starts with an existing investment universe consisting of a...

We propose a dynamic Rational Expectations (RE) bubble model of prices with the intention to exploit it for and evaluate it on optimal investment strategies. Our bubble model is defined as a geometric Brownian motion combined with separate crash (and rally) discrete jump distributions associated...