Rare disaster risks and volatility of the term-structure of US Treasury Securities: The role of El Niño and La Niña events (original) (raw)

Economic events and the volatility of government bill rates

PLOS ONE

Many studies show that in many countries (especially the G7), volatility in government bill rates far exceeds that in consumption growth rates. This volatility puzzle cannot be predicted by traditional disaster models, in which rare economic disasters are defined as a peak-to-trough percent fall in consumption (or real per capita GDP) by a high threshold (≥10%). For this purpose, we extend the traditional definition of rare economic disasters and propose a novel asset pricing model that models both good and bad events. We define a bad (or good) event as a peak-to-trough absolute decline (or a trough-to-peak absolute rise) in consumption growth rates by a low threshold (<10%). Compared to traditional disaster models, our model contains three improvements. First, model good and bad events, not just bad ones (e.g., rare economic disasters). Second, the event’s impact lasts for multiple periods rather than one period. Third, model non-rare economic events. We calibrate the parameters...

Credit Risk Volatility: Evidences From the Green Bond Market

2022

The paper is an investigation on the impact of financial markets on the volatility of green bonds credit risk component, measured by the option-adjusted spread/swap curve (OAS) of the Global Bloomberg Barclays MSCI Green Bond Index, for both the non and pandemic periods. For these purpose, after observing the dynamic joint correlations between all the variables through a DCC-GARCH, we adopt GARCH(1,1) and EGARCH(1,1) models, putting the OAS as dependent variable. Our main results show that the conditional variance parameters are significant and persistent in both times, testifying the overall impact of the other markets on the OAS. In more detail, we highlight that the gamma in the two EGARCH models is positive: so the “green” credit risk volatility is more sensitive to positive shocks than negative ones. With reference to the conditional mean, we note that if during the non pandemic time only the stock market is significant, during the pandemic also conventional bonds and gold are ...

Loan portfolio performance and El Niño, an intervention analysis

Agricultural Finance Review, 2011

PurposeThis paper illustrates that natural disasters can significantly threaten financial institutions serving the poor. The authors test the case of a microfinance institution (MFI) in Northern Peru, where severe El Niño events create catastrophic flooding.Design/methodology/approachPortfolio‐level, monthly data from January 1994 to October 2008 were examined using an intervention analysis. The paper tested whether the 1997‐1998 El Niño increased problem loans and estimated the magnitude of the effect.FindingsThe results indicate El Niño significantly increased problem loans, specifically the level of restructured loans. While restructured loans averaged 0.5 percent of the total loan portfolio before the El Niño, the estimated cumulative effect of El Niño indicates that an additional 3.6 percent of the portfolio value was restructured due to this event.Research limitations/implicationsFuture research could build on these results by modeling insurance‐type mechanisms for the MFI. Ad...

El Niño, La Niña, and the Forecastability of the Realized Variance of Heating Oil Price Movements

Sustainability

We use the heterogenous autoregressive (HAR) model to compute out-of-sample forecasts of the monthly realized variance (RV) of movements of the spot and futures price of heating oil. We extend the HAR–RV model to include the role of El Niño and La Niña episodes, as captured by the Equatorial Southern Oscillation Index (EQSOI). Using data from June 1986 to April 2021, we show evidence for several model configurations that both El Niño and La Niña phases contain information useful for forecasting subsequent to the realized variance of price movements beyond the predictive value already captured by the HAR–RV model. The predictive value of La Niña phases, however, seems to be somewhat stronger than the predictive value of El Niño phases. Our results have important implications for investors, as well as from the perspective of sustainable decisions involving the environment.