Can we beat the Random Walk? The case of survey-based exchange rate forecasts in Chile

Pincheira-Brown, Pablo; Neumann, Federico

doi:10.1016/j.frl.2019.101380

Cited by 3 publications

(3 citation statements)

References 28 publications

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“…(2019) , for instance, show the importance of commodity prices. The random walk model of exchange rates has occupied significant interest of researchers, such that, over half a century, concerted research has been devoted to finding exchange rate predictors that can beat the random walk model; for recent research, see Pincheira-Brown and Neumann (2019) . Our results demonstrate that the bulk of the variation in exchange rates is due to exchange rate shocks.…”

Section: Introductionmentioning

confidence: 99%

Understanding exchange rate shocks during COVID-19

Narayan

2022

Finance Research Letters

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Section: Introductionmentioning

confidence: 99%

Understanding exchange rate shocks during COVID-19

Narayan

2022

Finance Research Letters

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“…To evaluate the difference between our models in the context of nested models, we used the ENCNEW test proposed by Clark and McCracken [ 41 ]. Additionally, following Pincheira and Neumann [ 42 ], we implemented a mean directional accuracy test to assess the accuracy of commodity currencies in anticipating the direction change in commodity market synchronization. Since the results of the Wild Clark West test proposed by Pincheira, Hardy, and Muñoz [ 43 ] and the ENCt test proposed by Clark and McCracken [ 41 ] reached conclusions similar to those of the ENCNEW test, we decided not to report the results of these tests.…”

Section: Methodsmentioning

confidence: 99%

“…In this analysis, we examined the accuracy of commodity currencies in anticipating the direction change of commodity market synchronization. In the literature on forecasting, this type of analysis is also frequently used; for example, see [ 42 , 45 ].…”

Section: Methodsmentioning

confidence: 99%

Forecasting Commodity Market Synchronization with Commodity Currencies: A Network-Based Approach

Magner

Hardy

Lavín

et al. 2023

Entropy

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This paper shows that some commodity currencies (from Chile, Iceland, Norway, South Africa, Australia, Canada, and New Zealand) predict the synchronization of metals and energy commodities. This relationship links the present-value theory for exchange rates and its connection with commodity export economies’ fundamentals, where prospective commodity price fluctuations affect exchange rates. Predicting commodity market return synchronization is critical for dealing with systemic risk, market efficiency, and financial stability since synchronization reduces the benefits of diversification and increases the probability of contagion in financial markets during economic and financial crises. Using network methods coupled with in-sample and out-of-sample econometrics models, we find evidence that a fall in the return of commodity-currencies (dollar appreciation) predicts an increase in commodity market synchronization and, consequently, in commodity market systemic risk. This discovery is consistent with a transitive capacity phenomenon, suggesting that commodity currencies have a predictive ability over commodities that extend beyond the commodity bundle that a country produces. The latter behavior would be exacerbated by the high financialization of commodities and strong co-movement of commodity markets. Our paper is part of a vigorously growing literature that has recently measured and predicted systemic risk caused by synchronization, combining a complex systems perspective and financial network analysis.

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“Agree to Disagree”: Forecasting Stock Market Implied Volatility Using Financial Report Tone Disagreement Analysis

et al. 2023

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This paper studies the predictability of implied volatility indices of stocks using financial reports tone disagreement from U.S. firms. For this purpose, we build a novel measure of tone disagreement based on financial report tone synchronization of U.S. corporations scattered across five Fama-French industries. The research uses tree network methods to calculate the minimum spanning tree length utilizing data from text mining sentiments features extracted from all U.S. firms that considers 837,342 financial reports. The results show that periods of increased disagreement predict higher implied volatility indices. We contribute to the literature that proposes that a high level of expectations dispersion leads to higher stock volatility and fills a gap in understanding how firms’ disagreement level of financial report tone forecast the aggregate stock market behavior. The findings also have implications for financial stability and delegated portfolio management, as accurate volatility prediction is critical for practitioners.

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Can we beat the Random Walk? The case of survey-based exchange rate forecasts in Chile

Cited by 3 publications

References 28 publications

Understanding exchange rate shocks during COVID-19

Understanding exchange rate shocks during COVID-19

Forecasting Commodity Market Synchronization with Commodity Currencies: A Network-Based Approach

“Agree to Disagree”: Forecasting Stock Market Implied Volatility Using Financial Report Tone Disagreement Analysis

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