Using a wide sample of countries during the period 1970-2004, we instrument leader exits and financial crises to assess the causal effect each has on the other. We find that leader exits due to scheduled elections and term limits raise the probability of a banking crisis in the same year by 9% and that of a twin crisis by 7.6%. These effects are highly significant statistically, robust, and confined primarily to presidential regimes. In contrast, for financial crises instrumented with determinants from early warning models, only sovereign defaults appear to induce the exit of national leaders.

Rising yields in particular increase the potential for equity volatility. Assuming stable expectations for the path of company earnings, upward shifts in the yield curve exert downward pressure on the prices of equities through the valuation channel. For equity prices to remain stable in a rising interest rate environment, therefore, investors must believe that the expected path of earnings continues to improve.

In this paper, we introduce a new risk management tool focused on network connectivity between financial institutions. This tool will enable banks to better understand the counterparty risks faced by their counterparties and themselves. Additionally, our methodology cuts to the heart of the problem of systemic risk measurement and assessment. Our toolkit, which we call the Systemic Risk Monitor (SRM), will be indispensable for regulators seeking to fulfill their mandates to avoid banking crises.

To improve short-horizon exchange rate forecasts, we employ foreign exchange market risk factors as fundamentals, and Bayesian treed Gaussian process (BTGP) models to handle non-linear, time-varying relationships between these fundamentals and exchange rates. Forecasts from the BTGP model conditional on the carry and dollar factors dominate random walk forecasts on accuracy and economic criteria in the Meese-Rogoff setting. Superior market timing ability for large moves, more than directional accuracy, drives the BTGP's success. We explain how, through a model averaging Monte Carlo scheme, the BTGP is able to simultaneously exploit smoothness and rough breaks in between-variable dynamics. Either feature in isolation is unable to consistently outperform benchmarks throughout the full span of time in our forecasting exercises. Trading strategies based on ex ante BTGP forecasts deliver the highest out-of-sample risk-adjusted returns for the median currency, as well as for both predictable, traded risk factors.

Studies that test the effect of economic outcomes on political transitions using weather variations as instruments have generally overlooked findings from climate science that economic output is a hill-shaped, rather than linear, function of temperature and precipitation levels. We design an improved set of instruments for growth based on this fact, and find that growth-maximizing temperatures coincide with levels that maximize energy sector output in the climate response literature. Previous studies significantly overestimate the increase in the probability of democratic transitions resulting from negative growth shocks, although we find leadership transition frequencies rise significantly following transitions to democracy.

Although speculative activity is central to black markets for currency, the out-of-sample performance of structural models in those settings is unknown. We substantially update the literature on empirical determinants of black market rates and evaluate the out-of-sample performance of linear models and non-parametric Bayesian treed Gaussian process (BTGP) models against the random walk benchmark. Fundamentals-based models outperform the benchmark in out-of-sample prediction accuracy and trading rule profitability measures given future values of fundamentals. In simulated real-time trading exercises, however, the BTGP achieves superior realized profitability, accuracy and market timing, while linear models do no better than a random walk. Copyright (c) 2013 John Wiley & Sons, Ltd.

We develop a novel structural credit risk model that extends the original Merton model by allowing for stochastic interest rates and stochastic volatility. The model is estimated using Bayesian methods implemented via a Markov chain Monte Carlo algorithm, in light of the demonstrable advantages of likelihood approaches and the importance of taking into account parameter uncertainty documented in the literature. We solve the nontrivial computational problem of contingent claim valuation in our set-up by using a Taylor series approximation to the expectation of the claim payoffs under the risk-neutral measure. Finally, we illustrate our model and compare it against the Merton model with real data on a nonfinancial firm (Ford Motor Company) and three financial firms (Citigroup, Goldman Sachs, and Lehman Brothers) during the recent financial crisis.

We use popular non-parametric (CART, TreeNet) and parametric (logit) techniques to identify robust economic, demographic and political conditions that lead to shifts in control in the executive branch of government in 162 countries during the period 1960–2004. We find that institutional aspects of the political system, executive characteristics, demographic variables, economic growth, and economic trade variables are all very important for predicting leadership turnover in the following year. Financial crises are not robustly useful for this purpose, but a vulnerability to currency crises in times of low economic growth implies very high conditional probabilities of job losses for democratic leaders in non-election years. In-sample, TreeNet predicts 78% of leadership transition events correctly, compared to CART’s 70%, and TreeNet also generally achieves higher overall prediction accuracies than either CART or the logit model out-of-sample.

This chapter contains sections titled: Capital structure arbitrage for firms and financial institutions Credit and equity cycles Sovereign capital structure relative value Summary

This chapter contains sections titled: The model Equilibrium Monetary and fiscal policy Summary