A comparative study of exchange rates and order flow based on wavelet transform coherence and cross wavelet transform

Understanding the relationship and behavior of microstructures and exchange rates is an essential discussion for global foreign exchange investors. There are numerous research works regarding the linkage between order flow and exchange rates, yet the exact relationship between the order flow and the market price that indicates whether participants have an impact on the market trend remains undefined. This paper investigates the empirical association and behavior of order flow and the exchange rate movements within the time-frequency space, on three popular currency pairs, using the cross wavelet transform and wavelet transform coherency. The results indicate that order flow has a strong negative correlation and is the leader variable of the exchange rate. A predictor using order flow as an input variable was implemented to forecast the exchange rate direction using the sample data and out-of-sample data. This methodology, which performs with high accuracy and very low drawdown, could be a suitable tool for portfolio managers and forex participants during their trading activities.     

Dynamic responses and tail-dependence among commodities,the US real interest rate and the dollar

Theoretical models suggest monetary policy is transmitted to commodity prices. We quantify this channel using several empirical methods under daily data. In early 2009, the US real interest rate became negative, with sample mean varying from 1.75 % (in the mid-1997 to January 28, 2009, subsample) to \(-1.50\,\%\) (in January 29, 2009, to mid-September 2013 subsample). Gold displays higher risk-adjusted returns earlier, while copper and oil have higher risk-adjusted returns more recently. Shocks to the exchange rate and the real interest rate in VARs explain almost 30 % for oil and 32 % for copper more recently when impulse responses are more significant. The time-varying correlation of oil with the real interest rate in the more recent period is \(-0.462\), and its correlation with the exchange rate is \(-0.460\), compared to \(-0.089\) and \(-0.120\), respectively, in the earlier period. Vine copula methods identify a dependence pattern of C-vine copula with t-copula in almost every pair among commodity prices, the real value of the US dollar and the US real interest rate.     

Is the corn futures market noisier? The impact of high frequency quoting

ABSTRACT

The paper pioneers research on high frequency (HF) quoting noise in electronically traded agricultural futures markets. HF quoting – quickly cancelling posted limit orders and replacing them with new ones – emerges as a strategy for liquidity-providing traders. HF quoting can generate noise in price quotes which adds uncertainty to order execution and impairs the informational value of bid and ask prices. It can also lead to the perception that markets cannot be trusted for commercial transactions. Using intraday Best Bid Offer data for 2008–2013 and wavelet-based measures of volatility, we investigate the excess variance and co-movement discrepancies in the bid and ask prices. We find excess HF quoting variance exists. It is the highest at 250-ms scale – 90% higher than the variance implied by a random walk – but declines quickly to 7% at the 32 s scale. But its economic magnitude is negligibly small. Bid and ask price co-movements show a low degree of discrepancy with average correlations at 0.67 at 250 ms and reaching 0.95 at 8 s. All measures indicate that HF quoting noise has declined through the period. Overall, HF quoting has not caused excess variance during the transition to electronic trading in the liquid corn futures market.     

Liquidity and crude oil prices: China's influence over 1996–2011

Movement in China's money supply is shown to drive the movement in world money supply over the last fifteen years. Structural shocks to G3 (U.S., Eurozone and Japan) real M2 and to China's real M2 are both large over 1996:1–2011:12. The cumulative impact of real G3 M2 shocks on real oil prices is small and statistically insignificant. In contrast, the cumulative impact of China's real M2 on the real price of crude oil is large and statistically significant. Following a sharp fall in real oil price in the last half of 2008, the cumulative impact of China's real M2 on the real price of crude oil is particularly substantial in the recovery of oil price during 2009 from a low of $41.68 for January 2009. The analysis sheds light on the causes of movement in oil prices over the last fifteen years and in assessing the relative importance of China in the upsurge of the real price of crude oil.     

Analyzing time–frequency relationship between interest rate,stock price and exchange rate through continuous wavelet

In this study we investigate and identify the patterns of co-movement of interest rate, stock price and exchange rate in India in the period between July 1997 and December 2010 using the cross-wavelet power, the cross-wavelet coherency, and the phase difference methodologies. Our empirical findings suggest that stock prices, exchange rates and interest rates are linked. The cross wavelet results show that stock price movements are lagging both to the exchange rate and interest rate fluctuations. The interest rate lead over the stock price movements is even clearer, especially after 2006, and it suggests that the stock market follows the interest rate signals. Comparing results of WTC and XWT, we find very clear results of phase difference of lead–lag relationship between stock prices, exchange rates and interest rates.     

Impact of state-dependent oil price on US stock returns using local projections

In this paper, we investigate the impact of oil prices on both aggregate and industry US real stock returns over the period 1973–2017. The empirical analysis contributes to the related literature introducing a state-dependent oil price (high and low) and the local projections approach. Our main finding is that, depending on the nature of the shock and industry, the negative effects of oil price shocks become exacerbated -and the positive effects get moderated- if oil prices are already high.     

Oil price risk in the Spanish stock market: An industry perspective

This study examines the sensitivity of the Spanish stock market at the industry level to movements in oil prices over the period 1993–2010, paying special attention to the presence of endogenously determined structural changes in the relationship between oil price changes and industry equity returns. The empirical results show that the degree of oil price exposure of Spanish industries is rather limited, although significant differences are found across industries. The oil price sensitivity is very weak in the 1990s, a period of fairly stable and low oil prices. Instead, the link between crude oil and stock prices seems to have increased during the 2000s, becoming primarily positive. This evidence highlights the key role played by aggregate demand-side oil price shocks associated with the global real economic activity in the link between oil price fluctuations and the Spanish stock market.     

An empirical research of crude oil price changes and stock market in China: evidence from the structural breaks and quantile regression

This article investigates the relationship between real crude oil price changes and the Chinese real stock market at the industry level. Our study uses monthly data over the period 1994:03 to 2013:12. Based on input–output (IO) tables, this article will explore more details for the driving factors of sensitivity to oil price changes. We divide these driving factors into cost- and demand-side dependence. Empirical results reveal that sensitivity varies across different industries and periods based on structural breaks and asymmetric effects of oil price changes. Furthermore, some industries seemingly not directly affected by oil are sensitive to the real oil price changes. Finally, using a penalized quantile regression for panel data, we find that these two factors significantly affect lower, but not upper, quantile of sensitivity.     

The risk of falling house prices in Italy

This paper shows that Italian house market is less exposed to price shocks than the American one. Variations in the house price index in real terms have been studied along with the affordability ratio and the relation between house prices and rent levels for the period 1995–2004 in Italian provinces. Comparison with US data reveals greater overpricing in the US during the expansion phase (2000–2004). Although a speculative bubble in all US metropolitan areas considered does not emerge, US financial and economic structural factors make the US real estate sector more exposed to price shocks. To test the compatibility of Italian house prices with fundamentals an econometric model is designed to analyze the provincial house prices from 1995 to 2003.     

Testing for rational bubbles in the US housing market

The presence of a bubble in the US housing market prior to the 2007 subprime mortgage financial crisis is investigated. This is done by looking into the relationship between house prices and rental prices, known as the price–rent ratio, which is an important measure of a potential deviation between house prices and its fundamental value. Additionally, the interest rate is taken into account since it is an important factor in determining demand for housing mortgages and thereby influencing house prices, and explosive behavior of house prices is considered. These relationships are investigated through a theoretical and econometrical framework. The empirical evidence suggests that there was a bubble in the housing market prior to the financial crisis, even when controlling for the decreasing interest rate and the fundamental information given by the rental price in the period. Explosiveness was the main source of the price increase, such that a bubble was present in the housing market after correcting for other fundamental factors. The econometric procedures used in the analysis may therefore be relevant for monitoring the housing market.     

Time–frequency relationship between US output with commodity and asset prices

Commodity and asset prices have a well-documented effect on economic growth as manifested through various channels. At the same time, the business cycle influences the commodity and asset prices. Whereas empirical evidence on the effect of commodity and asset prices on the long-run economic growth is ambiguous, most of the previous researches highlight a positive correlation in the short run. The aim of this article is to disentangle the short- and long-run co-movements between US historical business cycles and commodity and asset prices over the period 1859–2013. For this purpose, we use a time–frequency approach and we test the historical influence of oil, gold, housing and stock prices over the output growth. In contrast to other studies, we control for the effect of other prices and monetary conditions, using the wavelet partial coherency. In line with the previous works, we discover that co-movements between economic growth and commodity and assets prices manifest especially in the short run. We also find that stock returns and housing prices have a more powerful effect on the US economic growth rate than the oil and gold prices. The long-run co-movements are documented especially around the World War II. Finally, when controlling for the influence of the interest rate, inflation and other commodity and asset prices, co-movements become weaker in the short run. In general, the oil and housing prices lead the GDP growth, the US output leads the gold prices, while there is no clear causality direction between business cycle and stock prices.     

Explaining House Prices in Australia: 1970–2003*

This paper aims to explain changes in real house prices in Australia from 1970 to 2003. We develop and estimate a long-run equilibrium model that shows the real long-run economic determinants of house prices and a short-run asymmetric error correction model to represent house price changes in the short run. We find that, in the long run, real house prices are determined significantly and positively by real disposable income and the consumer price index. They are also determined significantly and negatively by the unemployment rate, real mortgage rates, equity prices and the housing stock. Employing our short-run asymmetric error correction model, we find that there are significant lags in adjustment to equilibrium. When real house prices are rising at more than 2 per cent per annum, the housing market adjusts to equilibrium in approximately four quarters. When real house prices are static or falling, the adjustment process takes six quarters.     

A wavelet decomposition approach to crude oil price and exchange rate dependence

This paper studies the relationship between oil prices and US dollar exchange rates using wavelet multi-resolution analysis. We characterized the oil price–exchange rate relationship for different timescales in an attempt to disentangle the possible existence of contagion and interdependence during the global financial crisis and analyze possible lead and lag effects. For crude oil prices and a range of currencies, we show that oil prices and exchange rates were not dependent in the pre-crisis period; however, we did find evidence of contagion and negative dependence after the onset of the crisis. Additionally, we found that oil prices led exchange rates and vice versa in the crisis period but not in the pre-crisis period. These findings have important implications for risk management, monetary policies to control oil inflationary pressures and fiscal policy in oil-exporting countries.     

Revisiting global economic activity and crude oil prices: A wavelet analysis

Based on the wavelet analysis approach, this paper firstly examines the dynamic relationship between global economic activity (proxied by the Kilian economic index) and crude oil prices in both time- and frequency-domains. Our empirical results demonstrate significant correlation between crude oil prices and global economic activity at high frequencies (in the short run) during the entire sample period; however, the co-movement between the two at low frequencies (in the long run) is weaker and exists only during certain proportions of the sample period. We also document evidence that global economic activity and oil price are positively correlated, with dynamic lead-lag relationships across time. Our findings are robust to alternative choices of oil price indexes and controlling for other confounding factors such as geopolitical risk, armed conflicts, economic policy uncertainty and equity market uncertainty. The current study provides valuable implications for oil market investors based on the information of global economic situation and its dynamic relationships with oil prices.     

Oil price effects over individual Portuguese stock returns

During the last decades, the world energy dependence increased significantly. Understanding how companies depend on oil prices is essential, especially for countries highly dependent or importers. The work intends to investigate the relationship between oil price changes and Portuguese listed companies’ returns. Using the generalized autoregressive conditional heteroskedasticity model, we conclude that nearly 20 % of the companies are significantly affected by oil prices, finding also evidence that these effects are asymmetric, depending on the company’s current situation in the market (result attributed to the lack of liquidity and the small number of firms included within the sample). There exists some differences among economic sectors in the way they are impacted by oil price changes, although not so much significant. The results show that the bigger the company, the higher the probability of being significantly affected by oil price changes. Results suggest that lagged oil price positive shocks increase Portuguese companies’ returns, by opposition to the current oil price change. Findings highlight the key role played by aggregate demand-side oil price shocks over the financial economic activity, showing sector and individual companies’ differences, thus inducing the possibility of results being highly dependent over the economic context faced by the country under analysis, that firms are more sensitive to oil prices when the equity market is busiest and that oil price increases affect companies returns in a negative way, but price decreases cause more positive than negative effects over company returns.     

The Robertson connection between the natural rates of interest and unemployment

The paper explores the connection between the natural rates of unemployment and interest first put forward in the literature by Dennis Robertson in the 1930s. This looks at monetary dynamics in the business cycle and assesses the Robertsonian contribution to developments in macroeconomics before and after Keynes's General Theory. Robertson showed how unanticipated price level changes affect supply and demand in the labour market, as well as the saving–investment process in the credit market. Robertson's approach to economic policy was that of getting the relations right between cyclical changes in prices, output and employment and their long-run equilibrium values over time.     

Reconsidering the macroeconomics of the oil price in Germany: testing for causality in the frequency domain

This paper reconsiders the macroeconomics of the oil price for Germany. It investigates whether causality between the oil price and a selection of both macroeconomic and financial market variables differs between frequency bands. Both a bivariate frequency-wise causality measure and its higher-dimensional extension are applied. The main findings are that short-run causality exists between the oil price and variables such as short-term interest rates and the German share price index, while long-run causality is found between the oil price and long-term interest rates. Moreover, the oil price predicts the consumer price index at a high number of different frequencies, while no significant causality is found to run from the oil price to industrial production and the unemployment rate.      

The empirical study on price discovery of cornstarch futures market in China

This article aims at exploring the performance of the price discovery function of cornstarch futures market in China. In order to test the stationarity of the cash and futures prices of cornstarch, the augmented Dickey–Fuller test is applied. Both prices are integrated of order one. Then, the Johansen cointegration test is conducted to test the cointegrating relationship between those two prices. Finally, the Granger causality test is performed to observe the direction of causality. The evidence shows that there is a long-run relationship between cash and futures prices and the futures price Granger causes cash price. As a whole, price discovery of cornstarch market in China is present although it is a newly emerged market.     

The international business cycle as intertemporal coordination failure

Where investments are irreversible and the future is uncertain, people in two countries can make investment decisions that turn out to be mutually inconsistent. I argue that this intertemporal coordination failure explains international business cycles in a two-currency-area setting with a floating foreign exchange rate. The sequence of events starts with an expansionary domestic monetary shock, which decreases the domestic real interest rate. Facing low transactions costs, people spend the new money relatively early in the foreign exchange market and in the foreign market for loanable funds. Domestic monetary expansion thereby changes the relative prices of domestic and foreign goods and also of goods of earlier and later stages of production. The relative price changes lead to intertemporal and international coordination failures once the monetary expansion ends and relative prices change. Domestic monetary policy thereby causes the comovement across different currency areas we observe of business cycles.     

Relationship between oil price and exchange rate by FDA and copula

This article investigates the relationship between daily crude oil prices and exchange rates. Functional data analysis is used to show the clustering pattern of exchange rates and oil prices over the time period through high dimensional visualizations. We select exchange rates for important currencies related to crude oil prices by using the objective Bayesian variable selection method. The selected sample data exhibits non-normal distribution with fat tails and skewness. Under the non-normality of the return series, we use copula functions that do not require to assume the bivariate normality to consider marginal distribution. In particular, our study applies the popular and powerful statistical methods such as Gaussian copula partial correlations and Gaussian copula marginal regression. We find evidence of significant dependence for all considered pairs, except for the Mexican peso-Brent. Our empirical results also show that the rise in the West Texas Intermediate (WTI) oil price returns is associated with a depreciation of the US dollar.