A real-time quantile-regression approach to forecasting gold returns under asymmetric loss

Pierdzioch, Christian; Risse, Marian; Rohloff, Sebastian

doi:10.1016/j.resourpol.2015.07.002

Cited by 21 publications

(1 citation statement)

References 52 publications

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“…Using data for major gold-producing countries, we have shown that a novel nonparametric causality-in-quantiles test provides new insights into the in-sample causal links between gold-price fluctuations and exchange-rate movements in both their first and second moments. In future research, it is interesting to extend our analysis to a out-of-sample forecasting context, since in-sample predictability does not guarantee the same over the out-ofsample (Bonaccolto et al, 2015; on out-of-sample forecasting of gold-price fluctuations using variants of quantile-regression techniques, see also Pierdzioch et al 2015Pierdzioch et al , 2016.…”

Section: Discussionmentioning

confidence: 99%

On exchange-rate movements and gold-price fluctuations: evidence for gold-producing countries from a nonparametric causality-in-quantiles test

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Gupta

Pierdzioch

2016

Int Econ Econ Policy

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The links between exchange-rate movements and gold-price fluctuations have been extensively studied in earlier research using various econometric techniques. Our contribution to this research is that we apply a novel nonparametric causality-in-quantiles test to study the causal links between exchange-rate movements and gold-price fluctuations. We use daily data for the sample period 1994-2015 for major gold-producing countries to illustrate the novel test. We find that, for the majority of countries, gold-price fluctuations help to predict in sample the returns and the volatility of exchange rates. While exchange-rate movements predict in sample gold volatility, they do not predict gold returns.

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Section: Discussionmentioning

confidence: 99%

On exchange-rate movements and gold-price fluctuations: evidence for gold-producing countries from a nonparametric causality-in-quantiles test

Balcılar

Gupta

Pierdzioch

2016

Int Econ Econ Policy

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Fluctuations of the real exchange rate, real interest rates, and the dynamics of the price of gold in a small open economy

2016

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Standard-Nutzungsbedingungen:Die Dokumente auf EconStor dürfen zu eigenen wissenschaftlichen Zwecken und zum Privatgebrauch gespeichert und kopiert werden.Sie dürfen die Dokumente nicht für öffentliche oder kommerzielle Zwecke vervielfältigen, öffentlich ausstellen, öffentlich zugänglich machen, vertreiben oder anderweitig nutzen.Sofern die Verfasser die Dokumente unter Open-Content-Lizenzen (insbesondere CC-Lizenzen) zur Verfügung gestellt haben sollten, gelten abweichend von diesen Nutzungsbedingungen die in der dort genannten Lizenz gewährten Nutzungsrechte. Abstract Economic theory predicts that, in a small open economy, the dynamics of the real price of gold should be linked to real interest rates and the rate of change of the real exchange rate. Using data for Australia, we use a real-time forecasting approach to analyze whether real interest rates and the rate of change of the real exchange rate help to forecast out-ofsample the rate of change of the real price of gold. We study the economic value-added of out-of-sample forecasts using a behavioral-finance approach that takes into account that a forecaster may have an asymmetric loss function. Terms of use: Documents in EconStor mayJEL classification: C53; E44; G02

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Safe Havens, Machine Learning, and the Sources of Geopolitical Risk: A Forecasting Analysis Using Over a Century of Data

Gupta,

Karmakar,

Pierdzioch

2023

Comput Econ

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We use monthly data covering a century-long sample period (1915–2021) to study whether geopolitical risk helps to forecast subsequent gold volatility. We account not only for geopolitical threats and acts, but also for 39 country-specific sources of geopolitical risk. The response of subsequent volatility is heterogeneous across countries and nonlinear. We find that accounting for geopolitical risk at the country level improves forecast accuracy, especially when we use random forests to estimate our forecasting models. As an extension, we report empirical evidence on the predictive value of the country-level sources of geopolitical risk for two other candidate safe-haven assets, oil and silver, over the sample periods 1900–2021 and 1915–2021, respectively. Our results have important implications for the portfolio and risk-management decisions of investors who seek a safe haven in times of heightened geopolitical tensions.

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A real-time quantile-regression approach to forecasting gold returns under asymmetric loss

Cited by 21 publications

References 52 publications

On exchange-rate movements and gold-price fluctuations: evidence for gold-producing countries from a nonparametric causality-in-quantiles test

On exchange-rate movements and gold-price fluctuations: evidence for gold-producing countries from a nonparametric causality-in-quantiles test

Fluctuations of the real exchange rate, real interest rates, and the dynamics of the price of gold in a small open economy

Safe Havens, Machine Learning, and the Sources of Geopolitical Risk: A Forecasting Analysis Using Over a Century of Data

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