Cryptocurrencies and stock market indices. Are they related?

In this paper, we investigate the stochastic properties of six major cryptocurrencies and their bilateral linkages with six stock market indices using fractional integration techniques. From the univariate analysis, we observe that for Bitcoin and Ethereum, the unit root null hypothesis cannot be rejected; for Litecoin, Ripple and Stellar, the order of integration is found to be significantly higher than 1; for Tether, however, we find evidence in favour of mean reversion. For the stock market indices, the results are more homogeneous and the unit root cannot be rejected in any of the series, with the exception of VIX where mean reversion is obtained. Concerning bivariate results within the cryptocurrencies and testing for cointegration, we provide evidence of no cointegration between the six cryptocurrencies. Along the same lines, testing for cointegration between the cryptocurrencies and the stock market indices, we find evidence of no cointegration, which implies that the cryptocurrencies are decoupled from the mainstream financial and economic assets. The findings in this paper indicate the significant role of cryptocurrencies in investor portfolios since they serve as a diversification option for investors, confirming that cryptocurrency is a new investment asset class.     

Foreign exchange intervention and equilibrium real exchange rates

Monetary authorities intervene in the currency markets in order to pursue a monetary rule and/or to smooth exchange rate volatility caused by speculative attacks. In the present paper we investigate for possible intervention effects on the volatility of nominal exchange rates and the estimated equilibrium behaviour of real exchange rates. The main argument of the paper is that omission of intervention effects – when they are significant – would bias the ability to detect any PPP-based behaviour of the real exchange rates in the long run. Positive evidence for this argument comes from the experience of six Central and Eastern European economies, whose exchange markets are characterised by frequent interventions.     

Cointegration, Efficiency and Forecasting in the Currency Market

Existing literature on using the cointegration approach to examine the efficiency of the foreign exchange market gives mixed results. Arguments typically focus on econometric testing techniques, with fractional cointegration being the most current one. This paper tries to look at the issue from an economic perspective. It shows that the cointegrating relationship, whether cointegrated or fractionally cointegrated, is found mainly among the currencies of the European Monetary System which are set to fluctuate within a given range. Hence, there is no inconsistency with the notion of market efficiency. Yet, exploiting such a cointegrating relationship is helpful in currency forecasting. There is some evidence that restricting the forecasting model to consist of only cointegrated currencies improves forecasting efficiency.     

The confusing time-series behaviour of real exchange rates: Are asymmetries important?

Evidence regarding the time-series properties of real exchange rates is mixed. There is evidence that such rates exhibit both non-stationary and stationary behaviour. The current dominant belief is that rates are non-linear stationary, however, this is not accepted without question. This paper re-examines the time-series properties of five US dollar real exchange rates and argues that the confusing time-series properties arise largely as each series examined exhibits periods of non-stationary and stationary behaviour such that the sample over which any empirical exercise is conducted is of importance. However, extending a typical non-linear model used within the literature to allow for asymmetries improves the models ability to fit the data. Therefore, our results suggest that modelling asymmetries between positive and negative real exchange rate deviations is of importance, whereas extant research has typically rules out asymmetry. Indeed a forecasting exercise conducted over a 1-year horizon is particularly supportive of this model. Such a finding is of importance not only for academics but also finance practitioners involved in trading and portfolio management and finance managers who act in the foreign exchange market for goods market trading. It remains for future research to theoretically motivate the asymmetries found here.     

Macroeconomic shocks, structural change and real exchange rates: Evidence from historical data

We present empirical evidence on the forces driving real exchange rates in the long-run. Using data from the US, UK and Italy across different exchange rate regimes, we find support for the hypothesis that productivity and fiscal shocks matter. However, in some cases fiscal shocks cause depreciations, likely triggered by the monetary accommodation of fiscal shocks. We also find that the traditional Harrod–Balassa–Samuelson effect of productivity on real exchange rates is reversed in some cases, which confirms the importance of the distributive sector in driving productivity gains.     

U.S. real exchange rate fluctuations and relative price fluctuations

Traditional theory attributes fluctuations in real exchange rates to changes in the relative price of nontraded goods. This paper studies the relation between the United States’ bilateral real exchange rate and the associated bilateral relative price of nontraded goods for five of its most important trade relationships. We find that this relation depends crucially on the choice of price series used to measure relative prices and on the choice of trade partner. The relation is stronger when we measure relative prices using producer prices rather than consumer prices. The relation is stronger the more important is the trade relationship between the United States and a trade partner. Even in cases where there is a strong relation between the real exchange rate and the relative price of nontraded goods, however, a large fraction of real exchange rate fluctuations is due to deviations from the law of one price for traded goods.     

New evidence on nominal exchange rate predictability

The Meese–Rogoff puzzle, one of the well-known puzzles in international economics, concerns the weak relationship between nominal exchange rates and market fundamentals. The purpose of this paper is to show that market fundamentals do in fact matter in forecasting nominal exchange rates. In particular, we emphasize the importance of the Harrod–Balassa–Samuelson effect in modeling deviations from purchasing power parity. Based on the post-Bretton Woods period, we provide solid out-of-sample evidence that rejects the random walk forecast model at medium-term and long-term forecast horizons. We also find mild evidence for out-of-sample predictability of nominal exchange rates over the short term.     

Re-examining Cointegration, Unit Roots and Efficiency in Foreign Exchange Rates

This paper examines the cointegrating relationships in seven foreign exchange rates for a sample period from 1974 to 1991 by utilizing Johansen's (1991) method. Three subperiods are also examined to confirm the intertemporal stability of the test results. In addition, subgroups of the seven exchange rates are analyzed to determine the consistency of the empirical results with respect to different dimensions in the system. We find that the test results are sensitive to the choice of test statistics, time trends, subperiods as well as subgroups. All results indicate either one or no cointegrating relationship exists. Further, we study time series properties of twenty one cross-currency rates and the corresponding exchange rates in terms of a common currency. None of cross-currency rates are stationary and hence the pairs of exchange rates are not cointegrated.     

Long memory in the U.S. interest rate

In this article, we examine the order of integration of the U.S. long-term interest rate by means of using fractionally integrated techniques. Using annual data for the time period 1940-2000, the results based on the univariate tests of Robinson [Journal of American Statistical Association 84 (1994) 1420] support the hypothesis of a unit root. However, using a much longer span of the data (1798-2000), the order of integration seems to be smaller than one if the disturbances are white noise, while the unit root cannot be rejected if they are weakly autocorrelated.     

The real exchange rate in the long run: Balassa-Samuelson effects reconsidered

Historical data for over hundred years and 14 countries is used to estimate the long-run effect of productivity on the real exchange rate. We find large variations in the productivity effect across four distinct monetary regimes in the sample period. Although the traditional Balassa-Samuelson model is not consistent with these results, we suggest an explanation of the results in terms of contemporary variants of the model that incorporate the terms of trade mechanism. Specifically we argue that changes in trade costs over time may affect the impact of productivity on the real exchange rate over time. We undertake simulations of the modern versions of the Balassa-Samuelson model to show that plausible parameter shifts consistent with the behavior of trade costs can explain the cross-regime variation of the productivity effect.     

Bivariate FIGARCH and fractional cointegration

We consider the modelling of volatility on closely related markets. Univariate fractional volatility (FIGARCH) models are now standard, as are multivariate GARCH models. In this paper, we adopt a combination of the two methodologies. There is as yet little consensus on the methodology for testing for fractional cointegration. The contribution of this paper is to demonstrate the feasibility of estimating and testing cointegrated bivariate FIGARCH models. We apply these methods to volatility on the NYMEX and IPE crude oil markets. We find a common order of fractional integration for the two volatility processes and confirm that they are fractionally cointegrated. An estimated error correction FIGARCH model indicates that the preponderant adjustment is of the IPE towards NYMEX.     

Relationship between Treasury bills and Eurodollars: Theoretical and Empirical Analyses

In this paper, we derive an equilibrium relationship between the yields on Eurodollar and Treasury bills based on equivalent martingale results derived by Harrison and Kreps (1979) and Harrison and Pliska (1981, 1983) as well as the corporate debt pricing model developed by Merton (1974). The derived equilibrium relationship incorporates the models used by Booth and Tse (1995) and Shrestha and Welch (2001) as special cases. The equilibrium relationship indicates that the conditional volatility of the yield on Eurodollars explains the variation in the TED spread. We empirically test the equilibrium relationship using a GARCH-M model and the concept of fractional cointegration. We use both the ex ante data implied by the respective futures contracts as well as the ex post spot data with daily, weekly and monthly frequencies. We find empirical support for the Equilibrium relationship.

World food prices and monetary policy

How should monetary policy respond to large fluctuations in world food prices? We study this question in an open economy model in which imported food has a larger weight in domestic consumption than abroad and international risk sharing can be imperfect. A key novelty is that the real exchange rate and the terms of trade can move in opposite directions in response to world food price shocks. This exacerbates the policy trade-off between stabilizing output prices vis a vis the real exchange rate, to an extent that depends on risk sharing and the price elasticity of exports. We characterize implications for dynamics, optimal monetary policy, and the relative performance of practical monetary rules. While CPI targeting and expected CPI targeting can dominate PPI targeting if international risk sharing is perfect, even seemingly mild departures from the latter make PPI targeting a winner.     

The Relationships Between Mortgage Rates and Capital-Market Rates Under Alternative Market Conditions

Mortgage interest rates have become more integrated with other capital-market interest rates over recent decades, apparently as a result of the deregulation of financial markets. The link is both imperfect and time-varying. Mortgage rates during some time periods appear to be sticky with respect to their adjustment to changes in capital-market rates. We examine the relationship between weekly conventional mortgage rates and the interest rates on treasury and corporate securities under differing market conditions. We draw three conclusions based on the analysis. First, deregulation changed the link between mortgage rates and riskless interest rates, which confirms the findings of Goebel and Ma (1993). Second, mortgage rates were cointegrated with risky interest rates even before deregulation. Third, the link between mortgage rates and the risky bond rate can be associated with the behavior of the risk premium in the bond rate. The observed relationship is consistent with the stickiness observed by Haney (1988) and causes a more pronounced stickiness when rates are falling than when they are rising.     

Nonlinear trends in real exchange rates: A panel unit root test approach

We analyze the possibility of nonlinear trend stationarity as the alternative to unit roots in 23 OECD real exchange rates, 1974–1998, by adding nonlinear time terms to the CIPS panel unit root test of Pesaran (2007). We follow a thorough bootstrapping approach and propose a technique to adjust statistical significance for the use of multiple tests over several time trend orders. The unit root null that all real exchange rates have unit roots is rejected at better than the 0.05 level. Bootstrapped results from a procedure of Chortareas and Kapetanios (2009) suggest that the hypothesis that all are stationary is reasonable. We argue that nonlinear trend stationarity is the most likely alternative hypothesis for at least some of the real exchange rates because: (1) the strongest CIPS rejection occurs when quadratic trends are specified; (2) nonlinear time terms are statistically significant at the 0.10 level; (3) the actual CIPS statistics are more consistent with CIPS sampling distributions from bootstrapped nonlinear trend stationary processes than from linear trend or mean stationary processes.