War-related risks and the İstanbul bourse on the eve of the First World War

Hanedar, Avni Önder; Torun, Erdost; Hanedar, Elmas Yaldız

doi:10.1016/j.bir.2015.05.001

Cited by 5 publications

(2 citation statements)

References 27 publications

(22 reference statements)

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“…7. WWI might make them behave differently rather than the underlying terms of the bonds, as there was no difference in default risk before WWI (see Hanedar et al 2015).…”

Section: Resultsmentioning

confidence: 99%

The end of the Ottoman Empire as reflected in the İstanbul bourse

Hanedar

Torun

2016

Historical Methods: A Journal of Quantitative and Interdiscipli

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The Ottoman Empire faced catastrophic events during its period of dissolution which started with the First World War. At the end of this war, the Ottoman lands were shared by the Allied forces. As a reaction to this occupation, the Turkish War of Independence started in 1919 and finished in 1923. The authors aim to examine how these events were reflected in the _ Istanbul bourse, using Ottoman government bond prices data between 1918 and 1925. Econometric methodology of Carla Inclan and George Tiao (1994) identifies several break points, which imply a lower risk for the repayment of the bonds during the end of the First World War and the Turkish War of Independence.

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“…7. WWI might make them behave differently rather than the underlying terms of the bonds, as there was no difference in default risk before WWI (see Hanedar et al 2015).…”

Section: Resultsmentioning

confidence: 99%

The end of the Ottoman Empire as reflected in the İstanbul bourse

Hanedar

Torun

2016

Historical Methods: A Journal of Quantitative and Interdiscipli

Self Cite

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“…Antonakakis et al (2017) analyze the influence of the Geopolitical Risk Index on the stock and oil markets relation and identify such events as the First and Second World Wars, the 1956 Suez Canal Crisis, the 1973 Arab-Israeli War, the Gulf War and the invasion of Iraq. Many studies explore the impact of wars on financial markets, such as Choudhry (1997), Kucher (2000, 2001), Rigobon and Sack (2005), Schneider and Troeger (2006), Choudhry (2010), Guidolin and La Ferrara (2010), Kollias et al (2010), Meulemann et al (2014), Brune et al (2015), Hanedar et al (2015), Hudson and Urquhart (2015). There is, however, a lack of research on the accuracy of volatility forecasts during a war period.…”

Section: Literature Reviewmentioning

confidence: 99%

Forecasting volatility during the outbreak of Russian invasion of Ukraine: application to commodities, stock indices, currencies, and cryptocurrencies

Fiszeder

Małecka

2022

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Research background: The Russian invasion on Ukraine of February 24, 2022 sharply raised the volatility in commodity and financial markets. This had the adverse effect on the accuracy of volatility forecasts. The scale of negative effects of war was, however, market-specific and some markets exhibited a strong tendency to return to usual levels in a short time. Purpose of the article: We study the volatility shocks caused by the war. Our focus is on the markets highly exposed to the effects of this conflict: the stock, currency, cryptocurrency, gold, wheat and crude oil markets. We evaluate the forecasting accuracy of volatility models during the first stage of the war and compare the scale of forecast deterioration among the examined markets. Our long-term purpose is to analyze the methods that have the potential to mitigate the effect of forecast deterioration under such circumstances. We concentrate on the methods designed to deal with outliers and periods of extreme volatility, but, so far, have not been investigated empirically under the conditions of war. Methods: We use the robust methods of estimation and a modified Range-GARCH model which is based on opening, low, high and closing prices. We compare them with the standard maximum likelihood method of the classic GARCH model. Moreover, we employ the MCS (Model Confidence Set) procedure to create the set of superior models. Findings & value added: Analyzing the market specificity, we identify both some common patterns and substantial differences among the markets, which is the first comparison of this type relating to the ongoing conflict. In particular, we discover the individual nature of the cryptocurrency markets, where the reaction to the outbreak of the war was very limited and the accuracy of forecasts remained at the similar level before and after the beginning of the war. Our long-term contribution are the findings about suitability of methods that have the potential to handle the extreme volatility but have not been examined empirically under the conditions of war. We reveal that the Range-GARCH model compares favorably with the standard volatility models, even when the latter are evaluated in a robust way. It gives valuable implication for the future research connected with military conflicts, showing that in such period gains from using more market information outweigh the benefits of using robust estimators.

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