Testing for Neglected Nonlinearity in Long Memory Models

This paper constructs tests for the presence of nonlinearity of unknown form in addition to a fractionally integrated, long memory component in a time series process. The tests are based on artificial neural network structures and do not restrict the parametric form of the nonlinearity. The tests only require a consistent estimate of the long memory parameter. Some theoretical results for the new tests are obtained and detailed simulation evidence is also presented on the power of the tests. The new methodology is then applied to a wide variety of economic and financial time series.Long memory, Non-linearity, Artificial neural networks, Realized volatility, Absolute returns, Real exchange rates, Unemployment

Nonlinear Models with Strongly Dependent Processes and Applications to Forward Premia and Real Exchange Rates

This paper considers estimation and inference in some general non linear time series models which are embedded in a strongly dependent, long memory process. Some new results are provided on the properties of a time domain MLE for these models. The paper also includes a detailed simulation study which compares the time domain MLE with a two step estimator, where the Local Whittle estimator has been initially employed to filter out the long memory component. The time domain MLE is found to be generally superior to two step estimation. Further, the simulation study documents the difficulty of precisely estimating the parameter associated with the speed of transition. Finally, the fractionally integrated, nonlinear autoregressive- ESTAR model is found to be extremely useful in representing some financial time series such as the forward premium and real exchange rates.Non-linearity, ESTAR models, Strong dependence, Forward premium, Real exchange rates

Do Asymmetric and Nonlinear Adjustments Explain the Forward Premium Anomaly?

The forward premium anomaly refers to the situation where the slope coefficient in a regression of spot returns on the lagged interest rate differential is negative and significantly different to unity. This paper explores some of the asymmetries and non linearities present in the anomaly and the apparent rejection of Uncovered Interest Parity (UIP). The methodology is motivated by some recent economic theory literature on transactions costs, the limits to speculation and hysteresis. The paper estimates Logistic Smooth Transition Dynamic Regression (LSTR) models with the transition variable being the lagged forward premium for a range of currencies. An inner regime with foreign interest rates exceeding US rates is found to be consistent with the anomaly. While a third and outer regime with US interest rates exceeding foreign rates indicates convergence towards UIP. Detailed Monte Carlo experiments support the finding that an LSTR data generating process can indeed induce the forward premium anomaly. While the methodology appears promising in terms of uncovering important non linear and asymmetric behavior in the relationship, it should be noted that parameter estimation uncertainty indicates quite wide confidence intervals on the estimated transition functions. Hence, the accurate prediction of states, or regimes where UIP has a high probability of holding, is quite hard.Forward premium anomaly, Uncovered Interest Parity, Non-linearity, LSTR models

Modeling Long Memory and Structural Breaks in Conditional Variances: an Adaptive FIGARCH Approach

This paper introduces a new long memory volatility process, denoted by Adaptive FIGARCH, or A-FIGARCH, which is designed to account for both long memory and structural change in the conditional variance process. Structural change is modeled by allowing the intercept to follow a slowly varying function, speci?ed by Gallant (1984)'s flexible functional form. A Monte Carlo study ?nds that the A-FIGARCH model outperforms the standard FIGARCH model when structural change is present, and performs at least as well in the absence of structural instability. An empirical application to stock market volatility is also included to illustrate the usefulness of the technique.FIGARCH, long memory, structural change, stock market volatility.

Post-Louvre intervention: did target zones stabilize the dollar?

An investigation of whether the G-3 nations (Germany, Japan, and the U.S.) successfully maintained target zones following the G-7's February 1987 Louvre meeting. Using daily, official intervention data and simultaneous-equation techniques, the authors determine that the G-3 reacted in a manner consistent with maintaining target zones, but find scant evidence that the intervention successfully influenced subsequent exchange-rate movements.Foreign exchange - Law and legislation ; Dollar, American

Central bank intervention and overnight uncovered interest rate parity

This paper considers the impact of U.S. and German central bank intervention on the risk premium in forward foreign exchange markets.Foreign exchange - Law and legislation

The risk premium in forward foreign exchange markets and G-3 central bank intervention: evidence of daily effects, 1985-1990

Evidence that forward rates for foreign exchange are not unbiased forecasts of future spot rates suggests a time-varying risk premium. However, there is little evidence that the forecast error is related to fundamentals, although most investigations have lacked high-frequency data. In this paper, we use daily exchange-rate and official Federal Reserve intervention data to test for an impact of intervention on the forecast error. This paper extends recent analyses of daily changes in exchange rates by Baillie and Bollersev (1989) and Hsieh (1989) to the daily forward-rate forecast errors for the dm/US$and yen/US$ rates. We estimate an MA(21) process and utilize GARCH with a conditional student-t distribution. We find that 1) U.S. purchases of dollars on day t-1 affect the day t forecast error (ft-Et[st+k]), 2) there are day-of-the-week effects in the conditional variance, and 3) for the yen/US$ rate, there is GARCH-in-mean. These findings provide some support for considering intervention as a channel through which fundamentals influence risk premiaannel through which fundamentals influence risk premia.Foreign exchange - Law and legislation ; Risk

Intervention as information: a survey

Research has generally failed to find reliable connections between official exchange-market interventions and exchange rates that are consistent with either a monetary or a portfolio-balance theory of exchange-rate determination. Recently economists have suggested that intervention might sometimes influence exchange rates through its effects on agents’ expectations. This survey discusses newer research that analyzes informational aspects of intervention.Foreign exchange - Law and legislation

Modeling Long Memory and Structural Breaks in Conditional Variances: An Adaptive FIGARCH Approach

This paper introduces a new long memory volatility process, denoted by Adaptive FIGARCH , or A-FIGARCH , which is designed to account for both long memory and structural change in the conditional variance process. Structural change is modeled by allowing the intercept to follow a slowly varying function, specified by Gallant (1984)'s flexible functional form. A Monte Carlo study finds that the A-FIGARCH model outperforms the standard FIGARCH model when structural change is present, and performs at least as well in the absence of structural instability. An empirical application to stock market volatility is also included to illustrate the usefulness of the technique.FIGARCH , Long memory, Structural change, Stock market volatility

Long Memory and FIGARCH Models for Daily and High Frequency Commodity Prices

Daily futures returns on six important commodities are found to be well described as FIGARCH fractionally integrated volatility processes, with small departures from the martingale in mean property. The paper also analyzes several years of high frequency intra day commodity futures returns and finds very similar long memory in volatility features at this higher frequency level. Semi parametric Local Whittle estimation of the long memory parameter supports the conclusions. Estimating the long memory parameter across many different data sampling frequencies provides consistent estimates of the long memory parameter, suggesting that the series are self-similar. The results have important implications for future empirical work using commodity price and returns data.Commodity returns, Futures markets, Long memory, FIGARCH