Government bond yields in Germany and Spain—empirical evidence from better days

Basse, Tobias; Wegener, Christoph; Kunze, Frederik

doi:10.1080/14697688.2017.1419734

Cited by 17 publications

(11 citation statements)

References 36 publications

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“…Further, such forecasts are useful even when a base model does not perform well under significant fundamental changes. This may be because SIs can help to forecast a time-varying risk premium, which is reported to be responsible for the rejection of the IRP model (Ayuso & Restoy, 1996;Basse et al, 2018;Mayfield & Murphy, 1992;Sibbertsen et al, 2014). 7 Table 3 presents the test results for the AR1 model.…”

Section: Resultsmentioning

confidence: 99%

“…6 The use of the RW without drift follows prior studies, such as Bulut (2018), Ito et al (2021), and Matsuki and Chang (2016). 7 Basse et al (2018) discuss the relationship between the risk premium and a cointegration vector between German and Spanish government bonds during 2001-2006. Because the expected change in exchange rates should be zero under the EMU, the yield spread of the two countries should be equal to the timevarying risk premium.…”

Section: Data Availability Statementmentioning

confidence: 99%

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Do sentiment indices always improve the prediction accuracy of exchange rates?

Ito

Takeda

2021

Journal of Forecasting

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This study aims to improve the prediction accuracy of the exchange rate model by changing how indices that capture market sentiment are constructed. We construct the sentiment indices (SIs) for the Japanese and American markets using the Google search volume index (SVI) for financial terms listed in the Japanese dictionary. For these SVIs, we select keywords based on the correlation between weekly changes in the yen–dollar rate and the SVI. We use 30, 20, and 10 keywords that are replaced at three different frequencies: 3 months, 6 weeks, and weekly. The training period is from January 2013 to June 2015, and the forecast period is from July 2015 to December 2017. We perform a rolling regression, which keeps the length of the reference period constant at 2 and a half years, based on the interest rate parity and autoregressive models for the predictions. We compare the prediction accuracy using the mean squared prediction error, Clark and West's tests of equal predictive accuracy, and the direction of change test. When the SIs are updated every 3 months and 6 weeks, neither the interest rate parity model nor the autoregressive model shows improved prediction accuracy, even if the SI is added. However, when the SIs are updated weekly, prediction accuracy improves in both the interest rate parity and the autoregressive models as the number of words used to construct the SI increases. We conclude that frequently updated SIs can improve the short‐term prediction accuracy, while SIs updated less frequently may not.

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Section: Resultsmentioning

confidence: 99%

Section: Data Availability Statementmentioning

confidence: 99%

Do sentiment indices always improve the prediction accuracy of exchange rates?

Ito

Takeda

2021

Journal of Forecasting

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“…As discussed below in more detail, sovereign credit risk and redenomination risk did not seem to matter that much for the pricing of government bonds issued by member states of the currency union in the early days of the Euro (see, for example, Gibson et al. 2014 and Basse, Wegener and Kunze, 2018 ). This has definitely changed since severe fiscal problems have emerged in some member countries of the EMU in the aftermath of the house price collapse in the United States.…”

Section: Risk Premia and Different Types Of Riskmentioning

confidence: 99%

“…In any case, meanwhile many observers seem to believe that there certainly was an underpricing of sovereign credit risk in the EMU before 2008 (see, for example, Gibson et al. 2014 and Basse, Wegener and Kunze, 2018 ) and possibly also an overpricing of redenomination risk and sovereign credit risk after the debt crisis in Greece (see, on the one hand, Gibson et al. 2014 and, on the other hand, the more cautionary comments by Afonso et al.…”

Section: Interest Rate Convergence In the European Monetary Unionmentioning

confidence: 99%

Risk premia and the European government bond market: new empirical evidence and some thoughts from the perspective of the life insurance industry

et al. 2021

Self Cite

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We study yield spreads between government bonds in the European Monetary Union. This segment of the global fixed income market is of particular importance for insurance companies in Europe. Our empirical research strategy is inspired by Gunay (2020) who has analyzed the relationship between credit and liquidity risk in the United States using Granger causality tests. More specifically, we employ the procedure developed by Toda and Yamamoto (1995) to test for Granger causality among yield spreads in five different member countries of the European Monetary Union (namely Austria, Belgium, France, Italy and Ireland) relative to Germany. We examine interest rate data from bonds with three different maturities (5, 10 and 30 years). Given the importance of long-term bonds as asset class for European life insurers and pension funds, the empirical results from the often ignored market for government bonds with a maturity of 30 years should be of interest. With regard to long-term sovereign debt, there is no evidence for Granger causality among the time series examined here. Consequently, the risk premia required by investors to hold government bonds of one specific member country of the EMU do not help to forecast the risk premia that have to be paid by other countries. Given the structure of their liabilities, this empirical finding should be of high relevance for portfolio and risk managers in the European life insurance industry and in pension funds. With regard to the yield spreads to be observed in the market for 10-year government bonds, there seems to be no clear picture. Focusing on fixed income securities with a maturity of 5 years, there is one very interesting empirical finding. The test results reported here seem to imply that there is unidirectional Granger causality running from the yield spreads in all other four countries to Austria. Given that Austria is a comparably small country which is assumed to be in a fiscally stable position, this result could be interpreted as evidence for credit risk premia as being helpful to forecast liquidity risk premia in the market for medium-term government bonds issued by member states of the European Monetary Union.

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“…According to the traditional quantity theory of money, the money supply increases, and the price index rises, which in turn triggers inflation. In recent years, the macroeconomy has shown a deflationary trend [12][13][14][15]. A large amount of "excess" money supply and low price index coexist.…”

Section: Introductionmentioning

confidence: 99%

Optimal Combination of Currency Assets and Algorithm Simulation under Exchange Rate Risk

Wei

2020

Complexity

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The excess money supply did not lead to a rapid rise in the price index, which in turn triggered inflation. In this case, the redetermination of the demand for money is particularly important. At the same time, with the continuous expansion of the capital market and the rapid development of the virtual economy, the virtual economy is gradually deviating from the real economy. When selecting assets, microentities often incorporate virtual economic assets into investment considerations. Therefore, it is necessary to establish a money demand model that considers the impact of virtual economic assets. This paper uses the asset selection of microentities as the microfoundation to establish a money demand model to explain its economic significance. And based on the money demand model established, a dynamic equilibrium model of the money market was established, and the stability of the dynamic equilibrium point of the money market was verified through mathematical deduction. Based on the dynamic equilibrium model of the money market, the impact of money supply was analyzed. In order to verify the correctness of the aforementioned theory, this paper conducts an empirical analysis. Through cointegration analysis and the vector error correction model (VECM model), the correctness and applicability of the established money demand model are verified, and money demand, total social wealth, spreads between expected stock returns and interest rates, and real estate expectations are found. There is a long-term equilibrium relationship between the rate of return and the interest rate. The total amount of social wealth, the expected rate of return on stocks, and the interest rate spread will have an impact on the demand for money in the short term.

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Government bond yields in Germany and Spain—empirical evidence from better days

Cited by 17 publications

References 36 publications

Do sentiment indices always improve the prediction accuracy of exchange rates?

Do sentiment indices always improve the prediction accuracy of exchange rates?

Risk premia and the European government bond market: new empirical evidence and some thoughts from the perspective of the life insurance industry

Optimal Combination of Currency Assets and Algorithm Simulation under Exchange Rate Risk

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