M
Marcela Valenzuela
Researcher at Pontifical Catholic University of Chile
Publications - 24
Citations - 460
Marcela Valenzuela is an academic researcher from Pontifical Catholic University of Chile. The author has contributed to research in topics: Volatility (finance) & Systemic risk. The author has an hindex of 9, co-authored 21 publications receiving 373 citations. Previous affiliations of Marcela Valenzuela include University of Chile & London School of Economics and Political Science.
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Model risk of risk models
TL;DR: In this paper, the authors evaluate the model risk of models used for forecasting systemic and market risk, which is the potential for different models to provide inconsistent outcomes, is shown to increase with market uncertainty, and particular conclusions on the underlying reasons for the high model risk and the implications for practitioners and policy makers are discussed.
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Learning from History: Volatility and Financial Crises
TL;DR: This paper studied the effects of volatility on the probability of financial crises by constructing a cross-country database spanning 211 years and found that volatility is not a significant predictor of crises whereas unexpected high and low volatilities are.
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Deglacial and postglacial vegetation changes on the eastern slopes of the central Patagonian Andes (47°S)
TL;DR: In this article, the authors report pollen, spore, and charcoal records from Lago Augusta (47°05′S, 72°23′W, 440m a.s.l.), a small closed-basin lake located near the modern forest-steppe ecotone east of the Andes in Central Patagonia, Chile.
Posted Content
Learning from history: volatility and financial crises
TL;DR: This paper studied the effects of volatility on the probability of financial crises by constructing a cross-country database spanning 211 years and found that volatility is not a significant predictor of crises whereas unexpected high and low volatilities are.
Journal ArticleDOI
Can We Prove a Bank Guilty of Creating Systemic Risk? A Minority Report
TL;DR: In this paper, the authors evaluate the performance of two leading systemic risk models and show that estimation error alone prevents the reliable identification of the most systemically risky banks, and conclude that it will be a considerable challenge to develop a riskometer that is sound and reliable enough to provide an adequate foundation for macro-prudential policy.