This short note gives an overview of recent research on topics concerning Financial, Housing, and Monetary markets. In particular, I introduce a special issue that includes a selection of papers presented at the second International Workshop on Financial Markets and Nonlinear Dynamics (FMND) held in Paris in June 2015 (www.fmnd.fr). The papers investigate various issues and discuss hypotheses that help us to understand asset price dynamics and their impact on real activity, as well as the new rules governing financial markets. Furthermore, their conclusions can help us to improve the forecasting of market trends in the future.

The October 1929 crash led to a complete freeze of New York open markets. Studying the Fed monetary policy conduct in a nonlinear framework, using credit spreads between open market rates and the Fed's instrument rates as a proxy for liquidity risk, we present econometric evidence that the Fed was well aware of such risks as early as 1930, reacted to the financial stress and altered its monetary policy in consequence. Our outcomes revisit conventional wisdom about the presumed passivity of the Fed throughout the 30s.

We investigate the consequences of overleveraging and the potential for destabilizing effects arising from financial- and real-sector interactions. In a theoretical framework, we model overleveraging and demonstrate how a highly leveraged banking system can lead to unstable dynamics and downward spirals. Inspired by models developed by Brunnermeier, Sannikov and Stein, we empirically measure the deviation-from-optimal-leverage for a sample of large EU banks. This measure of overleveraging is used to condition the joint dynamics of credit flows and macroeconomic activity in a large-scale regime change model: a Threshold Mixed-Cross-Section Global Vector Autoregressive (T-MCS-GVAR). The regime-switching component of the model is meant to make the relationship between credit and real activity dependent on the extent to which the banking system is overleveraged. We find significant nonlinearities as a function of overleverage. The farther the observed leverage in the banking system from optimal leverage, the more detrimental is the effect of a deleveraging shock on credit supply and economic activity.

In this paper, we assess the characteristics of the housing market and its main determinants. Using data for 20 industrial countries over the period 1970Q1–2012Q2 and a discrete-time Weibull duration model, we find that the likelihood of the end of a housing boom or a housing bust increases over time. Additionally, we show that the different phases of the housing market cycle are strongly dependent on the economic activity, but credit market conditions are particularly important in the case of housing booms. The empirical findings also indicate that although housing booms have similar lengths in European and non-European countries, housing busts are typically shorter in European countries. The use of a more flexible specification for the hazard function that is based on cubic splines suggests that it evolves in a nonlinear way. From a policy perspective, our study can be useful for predicting the timing and the length of housing boom–bust cycles. Moreover, it highlights the importance of monetary policy by influencing lending rates and affecting the likelihood of occurrence of housing booms.

By developing a class of dynamic stochastic general equilibrium models with nominal rigidities and assuming a two-country currency union with sovereign risk, we show that there is not necessarily a trade-off between the prevention of default risk and stabilizing inflation. Under optimal monetary and fiscal policy, comprising a de facto inflation stabilization policy, the tax rate as an optimal fiscal policy tool plays an important role in stabilizing inflation, although not completely because of the distorted steady state. Changes in the tax rate to minimize welfare costs via stabilizing inflation then improve the fiscal surplus, and because of this and the incompletely stabilized inflation, the default rate does not increase as much.

We develop a dynamic partial equilibrium model of the housing market, in which the dynamics of the house price is determined by the interaction between chartists and fundamentalists. The model endogenously generates episodes of boom and bust in the house price and can replicate the recent US house price dynamics, and points to endogenous and exogenous behavioral factors as the main determinants of such dynamics.

A variety of international macroeconomic models predict a relationship between the real exchange rate and consumption. The empirical evidence in favor of such a relationship is limited, the so-called Backus and Smith puzzle. In this paper, we extend the analysis to allow for nonlinear dynamics and volatility changes across exchange rate regimes. Our findings suggest that long-run relationships in line with standard international business cycle models do exist for many Organization for Economic Co-operation and Development (OECD) countries. Further, Monte Carlo experiments illustrate that the nonlinear models can generate the Backus and Smith and the exchange rate disconnect puzzles. In this paper, we also contribute to the nonlinear real exchange rate literature by establishing a theoretical relationship between volatility and persistence. In accordance with the theoretical results, our empirical findings suggest that the increase in volatility in the post-Bretton Woods era is associated with relatively fast mean reversion of the real rate toward its equilibrium value.

I study the role of shocks to beliefs combined with Bayesian learning in a standard equilibrium business cycle framework. In particular, I examine how a prior belief arising from the Great Depression may have influenced the macroeconomy during the last 75 years. In the model, households hold twisted beliefs concerning the likelihood and persistence of recession and boom states that are affected by the Great Depression. These initial beliefs are substantially different from the true data generating process and are only gradually unwound during subsequent years. Even though the driving stochastic process for technology is unchanged over the entire period, the nature of macroeconomic performance is altered considerably for many decades before eventually converging to the rational expectations equilibrium. This provides some evidence of the lingering effects of beliefs-twisting events on the behavior of macroeconomic variables.

It is commonly accepted that credit market frictions are an important source of macroeconomic fluctuations. But what is the link between the two? And what is the driving factor of asset prices volatility? To answer these questions, we have introduced a specific credit friction, limited commitment, in a general equilibrium model with production and investment in productive capital, where agents can trade bonds. The model always displays a stationary equilibrium where bonds are traded. More importantly, limited commitment may generate stochastic endogenous fluctuations driven by self-fulfilling volatile expectations (sunspots), yielding credit and investment cycles and bond price volatility consistent with data.

This paper studies stock price comovements in two key regions [the United States and Europe, which is represented by three major European developed countries (France, Germany, and the United Kingdom)]. Our paper uses recent high-frequency data (HFD) and investigates price comovements in the context of “normal times” and crisis periods. To this end, we applied a non-Gaussian Asymmetrical Dynamic Conditional Correlation (ADCC)-GARCH (Generalized Autoregressive Conditional Heteroscedasticity) model and the Marginal Expected Shortfall (MES) approach. This choice has three advantages: (i) With the development of high-frequency trading (HFT), it is more appropriate to use HFD to test price linkages for overlapping and nonoverlapping data. (ii) The ADCC-GARCH model captures further asymmetry in price comovements. (iii) The use of the MES enables to measure systemic risk contributions around the distribution tails. Accordingly, we offer two interesting findings. First, while the hypothesis of asymmetrical and time-varying stock return linkages is not rejected, the MES approach indicates that both European and US indices make a considerable contribution to each other's systemic risk, with significant input from Frankfurt to the French and US markets, especially following the collapse of Lehman Brothers. Second, we show that the propagation of systemic risk is higher during the crisis period and overlapping trading hours than during nonoverlapping hours. Thus, the MES test is recommended as an indicator to help monitor market exposure to systemic risk and to gauge expected losses for other markets.