We present a new theory of homogeneous volatility (and variance) estimators for arbitrary stochastic processes. The main tool of our theory is the parsimonious encoding of all the information contained in the OHLC prices for a given time interval by the joint distributions of the high-minusopen,...

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...

Performance of investment managers are evaluated in comparison with benchmarks, such as financial indices. Due to the operational constraint that most professional databases do not track the change of constitution of benchmark portfolios, standard tests of performance suffer from the look-ahead...

Following Levy and Roll [2010], we posit that the market portfolio is the efficient tangent Markowitz portfolio, i.e., it is mean-variance efficient. We then reverse engineer the expected returns and variance terms with constraints imposed by empirical data on a hierarchy of asset baskets. This...

Why do investors keep buying underperforming mutual funds? To address this issue, we develop a one-period principal-agent model with a representative investor and a fund manager in an asymmetric information framework. This model shows that the investors perception of the fund plays the key role...

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 inspect the price volatility before, during, and after financial asset bubbles in order to uncover possible commonalities and check empirically whether volatility might be used as an indicator or an early warning signal of an unsustainable price increase and the associated crash. Some...

Using virtual stock markets with artificial interacting software investors, aka agent-based models (ABMs), we present a method to reverse engineer real-world financial time series. We model financial markets as made of a large number of interacting boundedly rational agents. By optimizing the...

We propose a novel class of models in which the crash hazard rate is determined by a function of a non-local estimation of mispricing. Rooted in behavioral finance, the non-local estimation embodies in particular the characteristic of "anchoring" on past price levels and the "probability...