Predicting Emerging Market Currency Crashes
By Manmohan S. Kumar, U. Moorthy, W. Perraudin. Social Science Research Network, 2003
240 citations recorded by the source corpus.
This paper assesses the extent to which crashes in emerging market currencies are predictable using simple logit models based on lagged macroeconomic and financial data. To evaluate our model, we calculate trading strategies in which an investor goes long or short in the currency depending on whether crash probabilities are low or high. When we estimate the model on part of the data and then use the parameter estimates to generate predictions for the remainder of the sample, we find that substantial profits may be made. Furthermore, the model correctly forecasts major crashes even on an out-of-sample basis.
Subfields: Economics and Econometrics, Finance
View Paper: https://www.semanticscholar.org/paper/705bb665ec1d1bdda8fc4269204de6116fd50c5f
How researchers see this paper
The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.
In Economics and Econometrics
- Peter Sarlin
- L. Chiaramonte
- Barbara Casu
- Elena Dumitrescu
- F. Betz
- Silviu Opricǎ
- Christophe Hurlin
- Tuomas A. Peltonen
In Finance
- Peter Sarlin
- L. Chiaramonte
- Barbara Casu
- F. Betz
- Silviu Opricǎ
- Christophe Hurlin
- Elena Dumitrescu
- Tuomas A. Peltonen
Citations in the corpus
- Capital and liquidity ratios and financial distress. Evidence from the European banking industry (2017, background): “See, among others, Kumar et al., 2003; Fuertes and Kalotychou, 2007; Davis and Karim, 2008; Poghosyan and Čihak, 2011; LoDuca and Peltonen, 2013; Sarlin and Peltonen, 2013; and Betz et al., 2014.”
- How to Evaluate an Early-Warning System: Toward a Unified Statistical Framework for Assessing Financial Crises Forecasting Methods (2010, methodology): “Indeed, taking into account the cut-off in the evaluation of an EWS can turn out to be crucial for an EWS with respect to a simple analysis based on QP S-type criteria.”
- Predicting Distress in European Banks (2014, methodology): “Typically, the literature has preferred the choice of a pooled logit model (e.g. Fuertes and Kalotychou, 2007; Kumar et al., 2003; Davis and Karim, 2008b; Lo Duca and Peltonen, 2013; Sarlin and Peltonen, 2013).”