Spot Exchange Research Articles

Non-Linear Interactions and Exchange Rate Prediction: Empirical Evidence Using Support Vector Regression

ABSTRACTThis paper analysed the prediction of the spot exchange rate of 10 currency pairs using support vector regression (SVR) based on a fundamentalist model composed of 13 explanatory variables. Different structures of non-linear dependence introduced by nine different Kernel functions were tested and the predictions were compared to the Random Walk benchmark. We checked the explanatory power gain of SVR models over the Random Walk by applying White’s Reality Check Test. The results showed that the majority of SVR models achieved better out-of-sample performance than the Random Walk, but in overall they failed to achieve statistical significance of predictive superiority. Furthermore, we observed that non-mainstream Kernel functions performed better than the ones commonly used in the machine-learning literature, a finding that can provide new insights regarding machine-learning methods applications and the predictability of exchange rates using non-linear interactions between the predictors.

Foreign Currency Mortgages Recast as Options on Commodity Futures

A foreign currency mortgage is debt for the purchase of residential property denominated in foreign currency. The borrower makes monthly payments in foreign currency. Devaluation of the domestic currency results in higher monthly payments. Practitioners have proposed solutions to avoid mortgage default. However, many of the practitioner solutions place excessive financial burdens on foreign lenders, while relieving domestic borrowers of responsibility. The goal of this paper is to present a solution that shares responsibility equitably between borrowers and lenders. First, we evaluate practitioner solutions by placing them in theoretical models. Then, the paper presents a solution, in which mortgages (loans) are viewed as derivatives (not loans). This is innovative, in that it takes mortgages out of banking and places them within investments. We recognize that investors have differential attitudes to risk. Accordingly, the proposed solution is presented in two contexts, i.e. from the perspective of a risk averse investor who shuns risk, or a risk taker, who is willing to take excessive risk to pursue returns. In the proposed solution, a call buyer may exercise the option, purchasing a futures contract to obtain the currency at a strike price that is less than the spot exchange rate. During the lengthy, uncertain delivery period, the exchange rate may vary more than the immediate period defined by the spot rate, in the form of jump diffusion models with stochastic volatility. The call buyer may purchase foreign currency at a strike price equal to the forward rates of a series of 1-period futures contracts with total life equal to the life of the mortgage. As strike prices continue to increase, with domestic currency depreciation, a repayment vehicle in the form of a portfolio of high-yielding securities is proposed, to produce the funds needed to meet forthcoming increases in monthly payments.

Income distribution, inflation and economic growth: A post-Keynesian approach

The dispute between social classes for fractions of income was a central theme for economic analysis at least since David Ricardo and Karl Marx. Its importance as an interpretative key declined with the marginalist revolution of the late nineteenth century and did not regain its central role in the conventional economic approach ever since. However, its relevance was maintained among heterodox economists such as Michal Kalecki and reinvigorated by post-Keynesian thinking. This paper seeks to offer three analytical contributions to the post- Keynesian literature: (1) it presents an integrated framework on the relationship between distributive conflict, inflation and economic growth in an open economy with government; (2) it proposes the use of a general framework, based on liquid preference, assets own interest rates, currency hierarchy and productivity differentials to understand the determinants of the spot exchange rate; and (3) it suggests a distinct monetary rule to take into account the role of interest rates on distributive conflict inflation and demand and growth regimes.

Bitcoin-based triangular arbitrage with the Euro/U.S. dollar as a foreign futures hedge: modeling with a bivariate GARCH model

This paper proposes a bitcoin-based triangular arbitrage, combining foreign exchanges in the bitcoin market and reverse foreign exchange spot transactions. An FX futures contract is used to reduce exposure to risk as a hedging instrument. The returns of the portfolio are jointly modeled using a bivariate DCC-GARCH model with multivariate standardized student's t disturbances due to the presence of leptokurtosis and fat tails observed. Based on the time-dependent covariance matrix, a dynamic optimal hedge ratio is formed, with a conditional correlation series as a by-product. Empirical results are obtained using Euros and U.S. dollars over the period from 21 April 2014 to 21 September 2018. Multiple rolling one-step-ahead forecasts are generated. The empirical results present bitcoin-based currency strategies dominate bitcoin trading in terms of risk management.

Complexity in financial asset returns: Evidence from the compass rose.

The compass rose pattern in financial data may indicate the presence of a nonlinear, possibly chaotic, data generating mechanism. The analysis of three key financial asset and denoised returns, gold, the Great British Pound/US dollar spot exchange rate, and the Standard & Poor's 500 stock index, reveals that over four equivalent subperiods, from 1996 to 2015, the compass rose pattern changes. This finding provides an opportunity to establish how noise affects financial time series. We conclude that the compass rose pattern is unlikely the product of an underlying nonlinear structure, since there is evidence of nonlinearity in all time periods, even those where the compass rose pattern is not evident. Therefore, the compass rose patterns, seen in the denoised data, suggest that the presence of noise masks the underlying dynamics of the asset returns.

Forward and Spot Exchange Rates in a Multi-Currency World*

Separate literatures study violations of uncovered interest parity (UIP) using regression-based and portfolio-based methods. We propose a decomposition of these violations into a cross-currency, a between-time-and-currency, and a cross-time component that allows us to analytically relate regression-based and portfolio-based facts and to estimate the joint restrictions they put on models of currency returns. Subject to standard assumptions on investors’ information sets, we find that the forward premium puzzle (FPP) and the “dollar trade” anomaly are intimately linked: both are driven almost exclusively by the cross-time component. By contrast, the “carry trade” anomaly is driven largely by cross-sectional violations of UIP. The simplest model that the data do not reject features a cross-sectional asymmetry that makes some currencies pay permanently higher expected returns than others, and larger time series variation in expected returns on the U.S. dollar than on other currencies. Importantly, conventional estimates of the FPP are not directly informative about expected returns because they do not correct for uncertainty about future mean interest rates. Once we correct for this uncertainty, we never reject the null that investors expect high-interest-rate currencies to depreciate, not appreciate.

Application and Comparison of the Full Information Maximum Likelihood of System Equations of 4 Spot Exchange Rates in Terms of CAD/USD, DKK/USD, CHF/USD and JPY/USD

In this article, we have tested the full information maximum likelihood, (FIML) of the natural logarithmic monthly returns of the CAD/USD, DKK/USD, CHF/USD and JPY/USD spot exchange rates. We have applied a system of four equations of the spot exchange rates to test and spot volatility clusters. The coefficient C(1) of the CAD/USD spot exchange rate is not significant at the 5% significant level. The coefficient is 0.000937, the z-statistic is -0.646 and the p-value is 0.5183. The standard error is 0.001450. The log likelihood is 507.9283. The average log likelihood is 2.49. The Akaike, Schwarz and Hannan-Quinn criterion are - 4.97, -4.95 and -4.96 respectively. The coefficient C(2) of the DKK/USD spot exchange rate is not significant at the 5% significant level. The coefficient is - 0.001560, the z-statistic is -0.946 and the p-value is 0.3441. The standard error is 0.001648. The log likelihood is 476.7551. The average log likelihood is 2.34. The Akaike, Schwarz and Hannan-Quinn criterion are -4.66, -4.65 and -4.66 respectively. The coefficient C(3) of the CHF/USD spot exchange rate is not significant at the 5% significant level. The coefficient is -0.003, the z-statistic is -1.73 and the probability is 0.0836. The standard error is 0.001708. The log likelihood is 470.50. The average log likelihood is 2.30. The Akaike, Schwarz and Hannan-Quinn criterion are -4.60, -4.59 and -4.60 respectively. The coefficient C(4) of the JPY/USD spot exchange rate is not significant at the 5% significant level. The coefficient is 0.00018, the z-statistic is 0.107 and the probability is 0.9146. The standard error is 0.001654. The log likelihood is 475.0964. The average log likelihood is 2.33. The Akaike, Schwarz and Hannan-Quinn criterion are -4.65, -4.63 and -4.64 respectively. The best fit model that helps the arbitrageurs to craft their investment strategy in terms of buying or holding large portfolios of spot exchange rates is the CAD/USD represented by equation 1. It has the largest value of the log likelihood and average log likelihood value. The values are 507.9283 and 2.49 respectively. In addition, the CAD/USD spot exchange rate has the lowest error term value of the Akaike, Schwarz and Hannan - Quinn information criterion. The numerical values are -4.97, -4.95 and - 4.96 respectively. Moreover, the CAD/USD spot exchange rate has the lowest standard error, which equals to 0.001450. The data that we have used started from 01/10/2000 to 01/09/2017 and represent the CAD/USD, DKK/USD, CHF/USD and JPY/USD spot exchange rates, which total to 204 observations. The data was obtained from the Federal Reserve statistical release department and it is denoted by the symbol, H.10.

Application of an ARCH System Equations of 4 Spot Exchange Rates in Terms of CAD/USD, DKK/USD, CHF/USD and JPY/USD to Check the Conditional Variance, Covariance and Correlation

In this article, we have tested the volatility of the natural logarithmic monthly returns of the CAD/USD, DKK/USD, CHF/USD and JPY/USD spot exchange rates. We have applied an ARCH – conditional heteroskedasticity method to model the variance, the covariance of the error terms and the correlation of the spot exchange rates. We have used three multivariate ARCH specifications in terms of the diagonal VECH, the conditional constant correlation, and the diagonal BEKK. By applying the system equations 1, which represent a diagonal VECH of a covariance specification multivariate ARCH model, we have found that the log likelihood value of the system equations model is 2935.896. The average log likelihood value is 2.66. The Akaike information criterion is -21.03. The Schwarz criterion is -20.58 and the Hannan – Quinn criterion is -20.85. By applying the system equations 2, which represent a constant conditional correlation of a covariance specification multivariate ARCH model, we have found that the log likelihood value of the system equations model is 2903.890. The average log likelihood value is 2.63. The Akaike information criterion is -20.88. The Schwarz criterion is -20.59 and the Hannan – Quinn criterion is -20.77. By applying the system equations 3, which represent a diagonal BEKK of a covariance specification multivariate ARCH model, we have found that the log likelihood value of the system equations model is 2891.647. The average log likelihood value is 2.62. The Akaike information criterion is -20.84. The Schwarz criterion is -20.63 and the Hannan – Quinn criterion is -20.75. The best fit model to help the arbitrageurs to craft their investment strategy in terms of buying, selling or holding large portfolios of spot exchange rates is the system ARCH equations 1. It has the largest value of the log likelihood and average log likelihood value and the lowest error term value of the Akaike and Hannan - Quinn information criterion. The Schwarz criterion has the highest value. By applying the Wald test of the symmetry restrictions of the natural logarithmic monthly returns of the spot exchange rate returns namely the CAD/USD, DKK/USD, CHF/USD and JPY/USD, we have found that the sample evidence suggests accepting the null hypothesis. In other words, the test has rejected the symmetry restrictions of the mean coefficients. The data that we have used started from 01/01/1990 to 01/01/2013 and represent the CAD/USD, DKK/USD, CHF/USD and JPY/USD spot exchange rates, which total to 277 observations. The natural logarithmic monthly returns total to 276 observations. The data was obtained from the Federal Reserve Statistical Release Department and it is denoted by the symbol, H.10.

Application of a GARCH, TGARCH, and EGARCH, Models to Test the Spot GBP/USD Exchange Rate Volatility.

In this article, we have tested the volatility of the returns of the spot exchange rate of GBP/USD for changing conditional variances. Generalized autoregressive conditional heteroskedastic models, GARCH, threshold generalized autoregressive conditional heteroskedastic models, (TGARCH), and exponential generalized autoregressive conditional heteroskedastic models, (EGARCH) models take into account the non- linearity that arises in financial time series. We have checked the volatility clusters for a long period of time that arises in the financial times series of returns or the fact that large and small values occur persistently in clusters. By applying a GARCH (1,1) model, we have found that the variance equation of the natural logarithmic returns of the GBP/USD spot rate are very significant. The coefficients of the ARCH and GARCH effects are statistically significant, which is a sign that the conditional variance and volatility clusters are persistent. By applying a TGARCH (1,1) model, we have found that there is no leverage effect. By applying an EGARCH (1,1) model, we have found that the asymmetry term is not statistically significant at the 5% significance level. Negative shocks do not imply a higher next period conditional variance than positive shocks of the same sign. There is no serial correlation in the residuals of the GARCH (1,1), TGARCH (1,1), and EGARCH (1,1), models. The residuals of the GARCH (1,1), TGARCH (1,1), and EGARCH (1,1) are homoskedastic and there is no additional ARCH effect. Finally, there are negative and positive shocks that are driving the GBP/USD exchange spot rate away from normality. The data that we have used are monthly returns starting from 01/01/1990 to 01/01/2013, which total to 276 observations. The data was obtained from the Federal Reserve Statistical Release Department and the symbol of the series is H.10.

Application of a Log Likelihood Object In GARCH with T-distributed errors and EGARCH With Generalised Error Distribution Model of the Spot AUD/USD Exchange Rate Volatility.

In this article, we have tested the volatility of the returns of the spot exchange rate of AUD/USD for changing conditional variances by using a log likelihood model. Generalized autoregressive conditional heteroskedastic models, (GARCH) with t-distributed errors, and exponential generalized autoregressive conditional heteroskedastic model, (EGARCH) with generalised error distribution take into account the non-linearity that arises in the financial time series. The aim is to compare and select the maximum value of the log likelihood estimation of the AUD/USD spot exchange rate. The log likelihood model take into account autoregressive, (AR), moving average, (MA), and monthly seasonal moving average, (SMA) factors that could better explain volatility clusters. We have selected the model with the best forecasting ability in terms of the lowest value of the Akaike information criterion, the Schwarz criterion, the Hannan – Quinn criterion. The best model will help the arbitrageurs to better craft their investment strategy in terms of holding, buying or selling portfolios of foreign currencies. The software that we have used is EViews 6. We have concluded that the best fit model is the GRACH model with a t-distribution, as it has the maximum log likelihood estimation of -500.354. The average log likelihood is -1.81. The Akaike information criterion, the Schwarz criterion and the Hannan – Quinn criterion have the lowest error estimates. Their values are 3.60, 3.56 and 3.59 respectively. In terms of gradients at the estimated parameters, we have found that there are outlier values and significant fluctuations at the various observations of the coefficients vectors, C(1), C(2), and C(3) of the gradients. Finally, the analytic derivatives were calculated based on the specified values. The real and minimum step sizes are identical for all coefficients vectors and very close to zero. We have used one-sided numeric derivative. The data that we have used are monthly returns starting from 01/01/1990 to 01/01/2013, which total to 276 observations. The total dataset includes 277 observations. The data was obtained from the Federal Reserve Statistical Release Department and the symbol of the series is H.10.

Intra-day dynamics of exchange rates: New evidence from quantile regression

This study provides a comprehensive description of the intra-day dynamics of major US-Dollar spot exchange rates. We use quantile autoregression to investigate the presence of (non-)linear temporal dependence in foreign exchange returns at various intra-daily time-horizons, ranging from ten minutes up to three hours. Specifically, we investigate an 11-year long sample of non-intermittent high frequency returns for the Euro (EUR), the British Pound (GBP) and the Japanese Yen (JPY) against the US-Dollar (USD). In contrast to previous studies, we find the temporal dependence of intra-daily foreign exchange returns to be non-linear and symmetrically U-shaped. Specifically, we observe pronounced negative autocorrelation for moderate USD appreciations and depreciations (central quantiles). For extreme positive and negative USD movements, we detect positive autocorrelation. This symmetric non-linear form of temporal dependence is remarkably stable across different exchange rates and states of the market. It appears to be a unique feature of foreign exchange returns and might be related to the fundamental ‘two-sidedness’ of foreign exchange markets.

“Amoateng Gut Check” approach to forecasting exchange rate using standard parity relationships

This pedagogical paper demonstrates how “the Gut check approach” uses a made-simple technique for international corporate finance and economics students to forecast exchange rates using parity relationships. The “Gut-check approach” uses two simple steps. First, check out if the spot exchange rate is either direct or indirect. Second, review the parity relationships (purchasing power parity or interest rate parity) for the two currencies in question to find out which currency appreciate or depreciates. To this end, the paper provides historical review of the standard technique by many textbook authors. The “Amoateng Gut-check technique” yields similar but more precise foreign exchange rate forecasting results than the standard approach. Moreover, it provides international corporate finance and economics students who may not recognize foreign and home countries an easy way of exchange rate forecast.

Predictability and Mispricing in Emerging vs. Developed Currency Markets

In this paper, we study predictability of returns on currencies of emerging and developed economies over the period February 1994 - July 2016. To assess the economic significance of currency predictability, we construct an upper bound on the explanatory power of predictive regressions, motivated by “no good-deal” restrictions that rule out unduly attractive investment opportunities. This bound is an extension of the bound proposed by Ross (2005) in that it allows for imperfect correlation between the kernel and trading strategies that exploit predictability. We find some evidence of predictability of futures returns outside of this bound, for realistic levels of risk aversion, for the emerging markets in our sample. We find, however, no excess-predictability of excessreturns computed from spot exchange rates and spot interest rates, in contrast with the results reported by Hsu et al. (2016) but in agreement with Kuang et al. (2014). The different predictability of spot and futures excess-returns is a noteworthy finding with potentially deep implications for the price discovery mechanism in currency markets. In addition, we find that emerging markets reacted differently from developed market, in terms of informational efficiency, to the onset of the ’post-Lehman’ financial crisis.

Foreign exchange markets with Last Look

We examine the Foreign exchange (FX) spot price spreads with and without Last Look on the transaction. We assume that brokers are risk-neutral and they quote spreads so that losses to latency arbitrageurs are recovered from other traders in the FX market. These losses are reduced if the broker can reject, ex-post, loss-making trades by enforcing the Last Look option which is a feature of some trading venues in FX markets. For a given rejection threshold the risk-neutral broker quotes a spread to the market so that her expected profits are zero. When there is only one venue, we find that the Last Look option reduces quoted spreads. If there are two venues we show that the market reaches an equilibrium where traders have no incentive to migrate. The equilibrium can be reached with both venues coexisting, or with only one venue surviving. Moreover, when one venue enforces Last Look and the other one does not, counterintuitively, it may be the case that the Last Look venue quotes larger spreads.

Market Efficiency of the Bitcoin Exchange Rate: Evidence From Co-Integration Tests

In this paper, we compare the bitcoin exchange rate of the U.S. dollar against the Euro with the relevant foreign spot exchange rate and find empirical evidence of co-integration and one-way Granger-causality from the spot exchange rate to the bitcoin exchange rate. Furthermore, we find market efficiency in the bitcoin exchange rate.

Exchange Rate and Oil Price Interactions in Selected CEE Countries

This paper reports a study on the causal dynamics between spot oil price, exchange rates, and stock prices in Poland, the Czech Republic, Hungary, Romania, and Serbia. The results are compared with a benchmark analysis in which U.S. monthly data are used, and time periods are selected according to the flexibility of exchange rate regimes in each country. A period between 2000 and 2015 is analyzed. The methodology is based on the Granger causality test, and the non-linear Diks–Panchenko test, while the causality in variance is checked with the Hafner–Herwartz test.

Back-Testing Methods Used to Estimate Future Spot Exchange Rates Utilizing Bloomberg Data

Since students ask for real life examples and employers look for better excel skills, I added an empirical project to International Finance class. Using Bloomberg data students, in teams of four, calculate annual and average annual currency appreciations, as well as, various parity conditions between dollar and major foreign currency. In the last phase of the project students back-test methods for predicting future spot exchange rates. As an incentive to experiment with different lengths of the estimation period, the team with the smallest standard deviation between estimated and actual exchange rates earn bonus points.

High-Frequency Trading, Liquidity Withdrawal, and the Breakdown of Conventions in Foreign Exchange Markets

:Conventions, or “that the existing state of affairs will continue indefinitely, except in so far as we have specific reasons to expect a change” (Keynes 1936), play a central role in over-the-counter markets. For instance, by allowing expectations about the future to become more harmonized and orderly, they act as stabilizers for the provision of liquidity. Conventions might, of course, change at any time. Nonetheless, by being attached to the daily trading routine and/or integrated within the institutional structure, the confidence in their relevance and validity can be long-lasting. In the foreign exchange market, in particular, where prices are quoted to end-users on demand, market-making banks rely on a convention to quote prices to each other to maintain liquidity. However, the rise of algorithmic and high-frequency trading poses a practical as well as a theoretical challenge to such conventions. By reacting ultra-fast to new information, including to new limit orders submitted by others, markets largely populated with algorithmic traders have become susceptible to a withdrawal of liquidity at an unprecedented speed and scale. Using a high-frequency dataset provided by Electronic Broking Services (EBS), we investigate the process of liquidity withdrawal from the foreign exchange spot market. By doing so, we consider the crowding out of conventions associated with liquidity provision, traditionally upheld through mutual understanding among financial institutions – in other words, reciprocity and trust among humans.

The application of block chain technology in spot exchange

The application of block chain technology in spot exchange

The Impact of Strategic Limit Order Submissions on Foreign Exchange Market Liquidity

In this paper, we empirically investigate the short-term impact of human/algorithmic limit order submissions on the liquidity provision and withdrawal process of other human/algorithmic traders. Using a high-frequency dataset containing over 1.5 million limit orders in the USD/JPY and EUR/JPY foreign exchange spot markets (amounting to a limit order volume of approximately $2 trillion), we document three key findings. First, order-splitting strategies widely adopted by algorithmic traders to disguise the true order size seem to go detected and are perceived as more information-rich or predatory than orders of the corresponding size typically submitted by human traders. Second, the inverse relationship between limit order size and price aggressiveness is less consistent than expected – both concerning traders’ strategic order submissions and their impact on the liquidity withdrawal by others. Third, we find that traders appear to be more sensitive to limit orders submitted from the same side (non-execution risk) than to the opposite side of the order book (free option risk), but that the ‘recovery’ of the limit order book primarily is driven by a reassessment of free option risk.