Order Flow and the Monetary Model of Exchange Rates: Evidence from a Novel Data Set

We propose an exchange rate model that is a hybrid of the conventional specification with monetary fundamentals and the Evans–Lyons microstructure approach. We estimate a model augmented with order flow variables, using a unique data set: almost 100 monthly observations on interdealer order flow on dollar/euro and dollar/yen. The augmented macroeconomic, or “hybrid,” model exhibits greater in‐sample stability and out of sample forecasting improvement vis‐à‐vis the basic macroeconomic and random walk specifications.     

A Comparison of Seasonal Adjustment Methods When Forecasting Intraday Volatility

In this article we compare volatility forecasts over a thirty‐minute horizon for the spot exchange rates of the Deutsche mark and the Japanese yen against the U.S. dollar. Explicitly modeling the intraday seasonal pattern improves the out‐of‐sample forecasting performance. We find that a seasonal estimated from the log of squared returns improves with the use of simple squared returns, and that the flexible Fourier form (FFF) is an efficient way of determining the seasonal. The two‐step approach that first estimates the seasonal using the FFF and then the parameters of the generalized autoregressive conditional heteroskedasticity (GARCH) model for the deseasonalized returns performs only marginally worse than the computationally expensive periodic GARCH model that includes the FFF.     

LINEAR RELATIONSHIP BETWEEN THE AUD/USD EXCHANGE RATE AND THE RESPECTIVE STOCK MARKET INDICES: A COMPUTATIONAL FINANCE PERSPECTIVE

In the recent era, computational intelligence techniques have found an increased popularity in addressing varied financial issues, including foreign exchange rate prediction. This article, through an intelligent system research framework, relates the Australian dollar (AUD)/US dollar (USD) exchange rate to the Australian and the US stock market indices. Information for exchange rate, All Ordinaries Index (AOI) and Dow Jones Industrial Average (DJI) for the trading days over the period January 1991–May 2011 is considered in this research. Utilizing a set of statistical and computational intelligence techniques, the research establishes that the AUD/USD exchange rate is best estimated by a linear forecast model compared with the nonlinear and ensemble‐based intelligent system models. This research further highlights that, among the competing linear models, the model with both the stock market indices and historical exchange rate values as the predictors is the best forecaster. Parameters of the linear model are deduced through a Monte Carlo stochastic approach. Relative importance of the predictors is also studied, and the influence of historical exchange rates, the immediate impact of AOI and the lagged effect of DJI are noted. Copyright © 2012 John Wiley & Sons, Ltd.     

Exchange Rates and Monetary Policy Uncertainty

We document that a trading strategy that is short the U.S. dollar and long other currencies exhibits significantly larger excess returns on days with scheduled Federal Open Market Committee (FOMC) announcements. We show that these excess returns (i) are higher for currencies with higher interest rate differentials vis‐à‐vis the United States, (ii) increase with uncertainty about monetary policy, and (iii) increase further when the Federal Reserve adopts a policy of monetary easing. We interpret these excess returns as compensation for monetary policy uncertainty within a parsimonious model of constrained financiers who intermediate global demand for currencies.     

Trading activity,dealer concentration and foreign exchange market quality

We study the relation between foreign exchange market quality and both trading activity and dealer concentration by considering two currency pairs with significant differences along both dimensions – the Euro–US dollar and Canadian dollar–US dollar. A variance ratio test reveals over-reaction in currency prices, but that this is smallest when trading activity is high and dealer concentration at its peak. A GARCH model shows that over-reaction declines as trading activity and dealer concentration increase, with the results being stronger for the Euro. Our results confirm that trading activity is an important determinant of market quality, but also point to a significant role for dealer concentration.     

Taiwan's Foreign Exchange Market—Volatile but Still Efficient?

This paper investigates the importance of return heterogeneity and volatility for the foreign exchange rate on the New Taiwan (NT) dollar in terms of the U. S. dollar. We describe the price behavior of the foreign exchange market through the Power GARCH (1,1) and EGARCH (1,1) models. The time knots of market events are found to have deep impacts on the behavior of both market agents and the intraday characteristics of the price process. Evidence also reveals that Taiwan's foreign exchange market is semi-strong efficient.     

Determinants of periodic volatility of intraday exchange rates in the Taipei FX Market

Using the periodic GARCH (P-GARCH) model, this paper investigates the cause of the volatility seasonality of intraday Taiwan dollar/U.S. dollar (NTD/USD) exchange rate. We study the intraday volatility of NTD/USD exchange rate by considering impacts from public news arrivals, inventory risk and central bank interventions. The estimation results indicate that news arrivals at the market open may induce traders to adjust their inventory position and result in higher NTD/USD volatility on days with reported central bank interventions.     

Non-Linear Predictive Models for Intra-Day Foreign Exchange Trading

Artificial neural networks were used to search for non-linear relations in high- frequency foreign exchange time series. Three years (1985-7) tick-by-tick bid prices for the Swiss franc to the US dollar exchange rate were used in this study as training data to specify predictive models for intra-day trading, which was then tested on the same exchange rate time series in the following year (1988). A simple trading rule was adopted to evaluate the models, which showed statistically significant trading profit under moderate transaction costs. In contrast, a standard linear model did not produce profit with the same training and test data and under the same trading rule and transaction cost assumption. This provides evidence for the non-linear nature of the foreign exchange time series under study.     

Overstatement of Implied Variance in the Dollar/Yen Currency Option Market

This paper investigates the predictive power of implied variancesextracted from the dollar/yen option prices. Implied variances areestimated from transaction prices of currency options traded on PHLXusing the option pricing model of Garman and Kohlhagen (1983). Incontrast to recent findings on stock and stock index options, theout-of-sample tests indicate that the implied variance is an upwardbiased estimator of future variance; and that the variance forecastsfrom GARCH and historical models do not contain significantincremental information in predicting future variance. Tradingstrategies are also developed to exploit the observed overstatementof variance in the dollar/yen option market. Traders that can executethe delta-neutral trading strategies at the observed markettransaction prices could lock in a significant profits during theperiod examined. However, for investors that facing highertransaction costs, the magnitude of the profits is generally notlarge enough to allow for abnormal risk-adjusted profits.     

Dynamic Volatility Trading Strategies in the Currency Option Market

The conditional volatility of foreign exchange rates can be predicted using GARCH models or implied volatility extracted from currency options. This paper investigates whether these predictions are economically meaningful in trading strategies that are designed only to trade volatility risk. First, this article provides new evidence on the issue of information content of implied volatility and GARCH volatility in forecasting future variance. In an artificial world without transaction costs both delta-neutral and straddle trading stratgies lead to significant positive profits, regardless of which volatility prediction method is used. Specifically, the agent using the Implied Stochastic Volatility Regression method (ISVR) earns larger profits than the agent using the GARCH method. Second, it suggests that the currency options market is informationally efficient. After accounting for transaction costs, which are assumed to equal one percent of option prices, observed profits are not significantly differentfrom zero in most trading strategies. Finally, these strategies offered returns have higher Sharpe ratio and lower correlation with several major asset classes. Consequently, hedge funds and institutional investors who are seeking alternative “marketneutral” investment methods can use volatility trading to improvethe risk-return profile of their portfolio through diversification. This revised version was published online in November 2006 with corrections to the Cover Date.     

Can the traditional Asian US dollar peg exchange rate regime be extended to include the Japanese yen?

Using daily data for a select set of four Asian exchange rates, namely the Hong Kong dollar, the Singapore dollar, the Taiwan dollar and the Thailand baht, from October 1985 to October 2002, we apply principal components analysis and the O-GARCH model to describe the evolution and persistence in the correlations over time. We also estimate 2-, 3- and 4-variable multivariate GARCH models, without imposing the assumption of constant correlations, to investigate volatility interaction amongst the currencies. To allow for fat tails in the distributions of exchange rate changes, we use the multivariate student-t distribution in maximising our log-likelihood functions. Our results indicate the possibility of designing an Asian exchange rate system involving a number of the region's currencies.     

Dynamics of credit spread moments of European corporate bond indexes

Traditional quantitative credit risk models assume that changes in credit spreads are normally distributed but empirical evidence shows that they are likely to be skewed, fat-tailed, and change behaviour over time. Not taking into account such characteristics can compromise calculation of loss probabilities, pricing of credit derivatives, and profitability of trading strategies. Therefore, the aim of this study is to investigate the dynamics of higher moments of changes in credit spreads of European corporate bond indexes using extensions of GARCH type models that allow for time-varying volatility, skewness and kurtosis of changes in credit spreads as well as a regime-switching GARCH model which allows for regime shifts in the volatility of changes in credit spreads. Performance evaluation methods are used to assess which model captures the dynamics of observed distribution of the changes in credit spreads, produces superior volatility forecasts and Value-at-Risk estimates, and yields profitable trading strategies. The results presented can have significant implications for risk management, trading activities, and pricing of credit derivatives.     

A Note on the Term Structure of Implied Volatilities for the Yen/U.S. Dollar Currency Option

This paper tests the relationship between short dated and long dated implied volatilities obtained from Tokyo market currency option prices by employing three different volatility models: a mean reverting model, a GARCH model, and an EGARCH model. We document evidence that long dated average expected volatility is higher than that predicted by the term structure relationship during the dramatic appreciation of yen/dollar exchange in the early 1990's. This revised version was published online in August 2006 with corrections to the Cover Date.     

FX Trading and Exchange Rate Dynamics

I examine the sources of exchange rate dynamics by focusing on the information structure of FX trading. This structure permits the existence of an equilibrium distribution of transaction prices at a point in time. I develop and estimate a model of the price distribution using data from the Deutsche mark/dollar market that prroduces two striking results:(1) Much of the short-term volatility in exchange rates comes from sampling the heterogeneous trading decisions of dealers in a distribution that, under normal market conditions, changes comparatively slowly; (2) public news is rarely the predominant source of exchange rate movements over any horizon.     

Modelling and trading the EUR/USD exchange rate at the ECB fixing

The motivation for this paper is to investigate the use of alternative novel neural network (NN) architectures when applied to the task of forecasting and trading the euro/dollar (EUR/USD) exchange rate, using the European Central Bank (ECB) fixing series with only auto-regressive terms as inputs. This is done by benchmarking four different NN designs representing a higher-order neural network (HONN), a Psi Sigma Network and a recurrent neural network with the classic multilayer perception (MLP) and some traditional techniques, either statistical such as an auto-regressive moving average model, or technical such as a moving average convergence/divergence model, plus a naïve strategy. More specifically, the trading performance of all models is investigated in a forecast and trading simulation on the EUR/USD ECB fixing time series over the period 1999–2007 using the last one and half years for out-of-sample testing, an original feature of this paper. We use the EUR/USD daily fixing by the ECB as many financial institutions are ready to trade at this level and it is therefore possible to leave orders with a bank for business to be transacted on that basis. As it turns out, the MLP does remarkably well and outperforms all other models in a simple trading simulation exercise. However, when more sophisticated trading strategies using confirmation filters and leverage are applied, the HONN network produces better results and outperforms all other NN and traditional statistical models in terms of annualized return.     

Using simulated currency rainbow options to evaluate covariance matrix forecasts

In the literature one can find a number of different methods to evaluate covariance matrix forecasts, and in choosing among these one has to consider what the actual purpose of the forecasts is. In this paper we look at portfolios of currency rainbow options and how simulated trading of such options portfolios can be used as a preference free evaluation measure for the forecasted covariance matrix. The main advantage of using portfolios instead of single options, in addition to making it possible to study multivariate problems of arbitrary size, is the possibility it gives to rely on shorter data series. We apply the methodology to a system of four US dollar exchange rates and compare the relative performance of different forecasting models, among them the fairly new Orthogonal GARCH model.     

The Trading Volume of Currency Options and the Spot Exchange Rate

This paper estimates the interrelation between the spot exchange rate of the Israeli currency, the new Israeli shekel, to the U.S. dollar, and the trading volumes of put and call options on the U.S. dollar in the Tel Aviv Stock Exchange. An increase in the trading volume of calls is positively correlated with an increase in the spot exchange rate of the dollar on the same day and the following day, but with a lower coefficient. Similarly, an increase in the trading volume of puts is related to a decrease in the spot price of the dollar on the same day of trade, with a smaller effect on the following day.     

Real effective exchange rate volatility and growth: A framework to measure advantages of flexibility vs. costs of volatility

By devising a real effective exchange rate (REER) index where bilateral exchange rates are weighted for relative trade shares, we find that the REER volatility (differently from the bilateral exchange rate volatility with the dollar) has significant impact on growth of per capita income after controlling for other variables traditionally considered in conditional convergence estimates. We also find that this (cost of volatility) effect can be reconciled with the concurring negative and significant effect on growth of the adoption of a fixed exchange rate regime (advantage of flexibility effect), where the latter may be also interpreted as the cost of choosing pegged regimes without harmonization of rules and macroeconomic policies with main trading partners. The adoption of an REER volatility measure, instead of a bilateral exchange rate with the dollar, has the advantage of making it possible a joint test for these two effects. This is because, while fixed exchange rate regimes are strongly negatively correlated, and almost collinear, with bilateral exchange rate volatility with the dollar, the correlation is much weaker when considering our REER volatility measure.     

On the sources of private information in FX markets

We investigate the source of information advantage in inter-dealer FX trading using data on trades and counter-party identities. In liquid dollar exchange rates, information is concentrated among dealers that trade most frequently and specialize their activity in a particular rate. In cross-rates, traders that engage in triangular arbitrage are best informed. Better-informed traders are also located on larger trading floors. In cross-rates, the ability to forecast flows explains all of the advantage of the triangular arbitrageurs. In liquid dollar rates, specialist traders can forecast both order-flow and the component of exchange rate changes that is uncorrelated with flow.     

Exchange rate bubbles: Fundamental value estimation and rational expectations test

We propose a model of periodically collapsing bubbles which extends the Van Norden (1996) model, and nests it, by considering a non-linear specification for the bubble size in the survival regime, and the endogenous determination of the level of the fundamental value of the stochastic process. They allow us to test for rationality in the formation of expectations, and remove the arbitrariness of exogenously setting the level of the fundamental value. This general model is applied to the exchange rate of the Brazilian real to the US dollar from March 1999 to February 2011. The futures market exchange rate is used as a proxy of its expected future value, and three different structural models are considered for the determination of the fundamental value. The first two imply that the exchange rate satisfies either purchasing power parity (PPP), or a modified version of it. The third structural model is a version of the monetary model of exchange rate determination, fitted to the period under consideration. We obtain the maximum likelihood estimate of the parameters of the models, explore the properties of the errors, test its restricted versions, and compare the three specifications for the fundamental. We find that the models we propose fit well the data, and are useful in the heuristic interpretation of the exchange rate movements of the period. Finally we select the structural models that display the best performance, according to several criteria.