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...

Using an agent-based model (ABM) with fundamentalists and chartists, prone to develop bubbles and crashes, we demonstrate the usefulness of direct market intervention by a policy maker, documenting strong performance in preventing bubbles and drawdowns and augmenting significantly the welfare of...

We propose a new set of stylized facts quantifying the structure of financial markets. The key idea is to study the combined structure of both investment strategies and prices in order to open a qualitatively new level of understanding of financial and economic markets. We study the detailed...

Using a recently introduced method to quantify the time varying lead-lag dependencies between pairs of economic time series (the thermal optimal path method), we test two fundamental tenets of the theory of fixed income: (i) the stock market variations and the yield changes should be...

The Johansen-Ledoit-Sornette (JLS) model of rational expectation bubbles with finite-time singular crash hazard rates has been developed to describe the dynamics of financial bubbles and crashes. It has been applied successfully to a large variety of financial bubbles in many different markets....

We augment the existing literature using the Log-Periodic Power Law Singular (LPPLS) structures in the log-price dynamics to diagnose financial bubbles by providing three main innovations. First, we introduce the quantile regression to the LPPLS detection problem. This allows us to disentangle...

We show how distributions can be reduced to low-dimensional scenario trees. Applied to intertemporal distributions, the scenarios and their probabilities become time-varying factors. From S&P 500 options, two or three time-varying scenarios suffice to forecast returns, implied variance or...

This paper introduces a no-arbitrage framework to assess how macroeconomic factors help explain the risk-premium agents require to bear the risk of fluctuations in stock market volatility. We develop a model in which stock volatility and volatility risk-premia are stochastic and derive...

The use of mixture distributions for modeling asset returns has a long history in finance. New methods of demonstrating support for the presence of mixtures in the multivariate case are provided. The use of a two-component multivariate normal mixture distribution, coupled with shrinkage via a...

Sentiment analysis is applied to the Federal Reserve's documents relating to the Federal Open Market Committee (FOMC). A new method of rating the sentiment of texts is developed through the creation of a 100 000 word sentiment dictionary, and is used to estimate the sentiment of the Beige Book...