Volatility of exchange rate futures and high-low price spreads

This study explores the time-series behavior and the predictability of daily percentage changes in the Japanese Yen futures contracts. The relationship between currency futures volatility and high-low price spreads in the Japanese Yen futures contracts is examined. In addition, this study explores the issue of first- and second-order dependencies in the Japanese Yen futures contract prices changes, address the issue of asymmetric volatility, and examine the extent to which the information contained in the high-low price spreads can be used to predict future Japanese Yen currency futures contract price changes. The analysis is carried out using the EGARCH model. The volatility of the Japanese Yen currency futures price changes is adequately modeled by an EGARCH process and is predictable using information contained in the high-low price spread variables constructed in this study. This study also finds a positive and significant relationship between the spread variable and the conditional mean of price changes, suggesting that current information contained in the spread variable can be used to predict future Japanese Yen currency futures contract price changes. The hypothesis that volatility is an asymmetric function of past innovations is confirmed.     

How oil price and exchange rate affect stock price in China using Bayesian Quantile_on_Quantile with GARCH approach

We revisit the links of real exchange rate, oil price and stock market price for China using Bayesian Multivariate Quantile_on_Quantile with GARCH approach over the period of September 14, 2001 to June 17, 2022 (a total of 4051 days). Results indicate both the links between stock price and oil price and between stock price and exchange rate varying under different combinations of quantiles. GARCH model also indicate that yesterday news and persistence measures varying with current conditional variance under different quantiles. We further estimate half-life of a shock to our whole markets and find out the half-life of a shock range from 0.415 to 4.015 days. Result not found in previous study. Our study has important policy implications for the investors, practitioners, and the government.     

The true shadow price of foreign exchange

For the last half century, trade theorists, development economists, and development practitioners have been calculating what was claimed to be the shadow price of scarce foreign exchange. In fact, what they have been calculating is the social value of the receipt of a unit of a numeraire good from abroad, typically obtained from real models. In our paper, we explicitly deal with a model of a monetized economy, and we develop formulas for the social value of a unit of foreign currency, which, in general, differ from the traditional formulas.     

Capital control and exchange rate volatility

The study offers one conceptual and theoretical framework for evaluating the economic effects of a trading tax on foreign exchange transactions. Taxes and the price stickiness mechanism are taken into account in the model. When prices are flexible, full monetary neutrality can be obtained even in the short-term. Intuitively, taxes on foreign exchange transactions discourage speculation by rising currency trading costs, and, thus, increase the stability of the exchange rate. Finally, the results show that not only the exchange rate but consumption, investment and employment will become less volatile by imposing trading taxes on foreign exchange transactions.     

Economic theory and exchange rate forecasts

Businesses use forecasts of exchange rates to make decisions about production, employment, investment, financial management, and pricing decisions. The proper statistical criteria for making and evaluating these exchange rate forecasts are implied by the underlying decision problem. That decision problem is in turn affected by the economic environment facing the firm and its industry, the overall macroeconomic situation, and the main types of disturbances affecting exchange rates. In general, the proper loss function for the forecasting problem will be asymmetric.     

Statistical learning and exchange rate forecasting

This study uses innovative tools recently proposed in the statistical learning literature to assess the capability of standard exchange rate models to predict the exchange rate in the short and long runs. Our results show that statistical learning methods deliver remarkably good performance, outperforming the random walk in forecasting the exchange rate at different forecasting horizons, with the exception of the very short term (a period of one to two months). These results were robust across countries, time, and models. We then used these tools to compare the predictive capabilities of different exchange rate models and model specifications, and found that sticky price versions of the monetary model with an error correction specification delivered the best performance. We also explain the operation of the statistical learning models by developing measures of variable importance and analyzing the kind of relationship that links each variable with the outcome. This gives us a better understanding of the relationship between the exchange rate and economic fundamentals, which appears complex and characterized by strong non-linearities.     

Equilibrium price dynamics in an overlapping-generations exchange economy

An extension to the Yaari (1965)–Blanchard (1985) continuous time overlapping generations model for an endowment Arrow–Debreu economy with an age-structured population is presented. It is proved that Arrow–Debreu equilibrium prices are represented by a double linear integral equation, and depend on the age-distributions of population and endowments. For an economy with a balanced growth, and logarithmic utility, we prove that bubbles may exist if endowments are distributed earlier than some critical age.     

Information asymmetry,sentiment interactions,and asset price

We develop an asset pricing model with sentiment interactions between institutional and individual investors under the condition of information asymmetry. Our model considers private information and investor sentiment, two imperfections in securities markets, and integrates them into a theoretical model to investigate the role of the interaction between information asymmetry and investor sentiment in asset pricing. We show that the joint effect of private information and investor sentiment deviate the price of risky assets and efficiently explains anomalies in the stock market. Investor sentiment changes the effect of information on the equilibrium price relative to a world where all investors are completely rational. Private information changes the effect of investor sentiment on the equilibrium price in comparison with a scenario with symmetric market information. In addition, the individual investors’ learning and the disclosure of information both allow private information to be better integrated into the price and simultaneously changes the effect of investor sentiment on the equilibrium price.     

Understanding spot and forward exchange rate regressions

Using the Kalman filter, we obtain maximum likelihood estimates of a permanent–transitory components model for log spot and forward dollar prices of the pound, the franc, and the yen. This simple parametric model is useful in understanding why the forward rate may be an unbiased predictor of the future spot rate even though an increase in the forward premium predicts a dollar appreciation. Our estimates of the expected excess return on short-term dollar-denominated assets are persistent and reasonable in magnitude. They also exhibit sign fluctuations and negative covariance with the estimated expected depreciation. © 1997 John Wiley & Sons, Ltd.     

Bayesian Model Averaging and exchange rate forecasts

Exchange rate forecasting is hard and the seminal result of Meese and Rogoff [Meese, R., Rogoff, K., 1983. Empirical exchange rate models of the seventies: Do they fit out of sample? Journal of International Economics 14, 3–24] that the exchange rate is well approximated by a driftless random walk, at least for prediction purposes, still stands despite much effort at constructing other forecasting models. However, in several other macro and financial forecasting applications, researchers in recent years have considered methods for forecasting that effectively combine the information in a large number of time series. In this paper, I apply one such method for pooling forecasts from several different models, Bayesian Model Averaging, to the problem of pseudo out-of-sample exchange rate predictions. For most currency–horizon pairs, the Bayesian Model Averaging forecasts using a sufficiently high degree of shrinkage, give slightly smaller out-of-sample mean square prediction error than the random walk benchmark. The forecasts generated by this model averaging methodology are however very close to, but not identical to, those from the random walk forecast.     

Cointegration and models of exchange rate determination

The application of new techniques in testing for cointegration indicate the inappropriate- ness of the pure monetary model to explain movements in the nominal exchange rate. In general the fundamental variables are found to be integrated of different orders and there is a lack of cointegration between the exchange rate variables in the monetary model and relative prices. Estimation of other dynamic models are found to give rise to parameter estimates which do not support the monetary model. The results are broadly consistent across five countries. These results imply that it is not worthwhile to forecast from the monetary model and its main variants.     

Exchange rate and foreign price effects on UK inflation

The issue of incomplete pass-through from exchange rate changes to domestic inflation has received considerable attention. Most models try to account for this by using a variety of assumptions about the costs of changing prices. These suggest complete pass-through, but only after the possible elapse of a considerable delay. In contrast, in this article Graeme Chamberlin and Brian Henry provide evidence that exchange rate effects on inflation may be non-linear and, more specifically, subject to thresholds. Their tentative results suggest this may be important in describing price-setting behaviour in the UK.     

Asset price dynamics with heterogeneous beliefs and local network interactions

In this paper we investigate the effects of network topologies on asset price dynamics. We introduce network communications into a simple asset pricing model with heterogeneous beliefs. The agents may switch between several belief types according to their performance. The performance information is available to the agents only locally through their own experience and the experience of other agents directly connected to them. We model the communications with four commonly considered network topologies: a fully connected network, a regular lattice, a small world, and a random graph. The results show that the network topologies influence asset price dynamics in terms of the regions of stability, amplitudes of fluctuations and statistical properties.     

人民币汇率政策的分析探讨

近年来,在亚洲金融危机以后,人民币汇率政策成为国际舆论高度观注的焦点问题之一,各方观点的争论此起彼伏,从未停息。尤其是在近阶段,中国GDP、对外贸易和吸引外资都保持了强劲的发展势头,同时IMF的估算显示,2002年人民币相对于其他主要贸易伙伴的名义有效汇率下降了6％,此种背景下,各国专家、学者和政要对当前的人民币政策众说纷纭,中国的货币当局面临着相当复杂的国内国际政策环境。     

Implied volatility term structure and exchange rate predictability

This paper provides empirical evidence of the predictive power of the currency implied volatility term structure (IVTS) for the behavior of the exchange rate from both cross-sectional and time series perspectives. Intriguingly, the direction of the prediction is not the same for developed and emerging markets. For developed markets, a high slope means low future returns, while for emerging markets it means high future returns. We analyze predictability from a cross-sectional perspective by building portfolios based on the slope of the term structure, and thus present a new currency trading strategy. For developed (emerging) currencies, we buy (sell) the two currencies with the lowest slopes and sell (buy) the two with the highest slopes. The proposed strategy performs better than common currency strategies – carry trade, risk reversal, and volatility risk premium (VRP) – based on the Sharpe ratio, considering only currency returns, which supports the exchange rate predictability of the IVTS from a cross-sectional perspective.     

China''s exchange rate and the balance of trade

This paper examines the responsiveness of the balance of trade of the People's Republic of China to the real exchange rate. We find that, in both the short-run and the long-run, devaluation serves to improve the balance of trade. Using quarterly data for 1980:I to 1989:IV we show that the bulk of the response to devaluation occurs over a one year period, with noJ-curve effect. These results suggest that the two-tier price system and other measures to liberalize the Chinese economy have made the exchange rate an effective indirect tool for regulating trade.     

International foreign exchange agreements and nominal exchange rate volatility: a GARCH application

For eight major national currencies, this study estimates, and tests several hypotheses with, a t-distribution GARCH model of daily spot nominal exchange rate changes. The sample period covered is June 1, 1982 through September 30, 1992. By using likelihood ratio and parameter stability tests, it finds that for most of the currencies considered, both the conditional means and variances of unexpected exchange rate changes experienced statistically significant structural breaks across the five subperiods that are associated with four episodes of international foreign-exchange policy coordination. The study also finds that the orderings of the GARCH-estimated unconditional standard deviations roughly match the orderings of the sample standard deviations across the five subperiods. An explanation is provided for what underlying factors contributed to these structural shifts.     

Non-linear,hybrid exchange rate modeling and trading profitability in the foreign exchange market

A neuro-fuzzy decision-making technology is designed and implemented to obtain the optimal daily currency trading rule. It is found that a non-linear, artificial neural network exchange rate microstructure (hybrid) model combined with a fuzzy logic controller generates a set of trading strategies that earn a higher rate of return compared to the simple buy-and-hold strategy. After accounting for realistic transaction costs, the gains from utilizing a dynamic, neuro-fuzzy model are still present.