Do momentum-based strategies work in emerging currency markets?

Existing studies on the profitability of trading rules in the currency market focus mainly on the currencies of developed countries. The profitability of technical trading rules on the currencies of emerging economies is surprisingly understudied. This paper evaluates the profitability of technical trading rules in emerging currency markets. Similar to Okunev and White [Okunev, J. and White, D., (2003) “Do Momentum-based Strategies Still Work in Foreign Currency Markets?” Journal of Financial and Quantitative Analysis 38, 425–447.], 354 long/short moving average rules for six currencies are investigated. It is found that investing in emerging currencies can generate a considerable annual return of over 20%, even after a 5% annual transaction cost is imposed. The trading-rule profits are relatively stable across the 20 year sample period. Furthermore, the impact of financial crises on the trading-rule returns is also examined. It is found that the profitability of the trading rules is improved after the crises.     

中国银行间市场开创卢布交易业务完善市场功能

1994年人民币汇率形成机制改革以来,中国银行间外汇市场挂牌了美元、欧元、日元、英镑和港币等五种国际储备货币。本轮国际金融危机以来,主要货币汇率波动加大,微观主体出于节约汇兑成本的需要,对人民币与新兴市场货币兑换交易的需求不断上升。为满足经济主体的需求,中国人民银行积极探索在银行间外汇市场挂牌人民币对新兴市场货币交易。2010年11月22日,中国银行间外汇市场挂牌人民币对卢布交易。挂牌以来,中国银行间外汇市场人民币对新兴市场货币交易健康发展,报价日益活跃,成交快速增长。截至2011年9月末,银行间外汇市场人民币对卢布成交53.10亿元人民币,2011年下半年以来的交易量也已超过了人民币对英镑的交易量。在我国银行间市场挂牌人民币对卢布交易一周年之际,本刊特推出四家人民币对卢布做市商相关经验与感想的专题文章,供市场参考。     

Predictability,trading rule profitability and learning in currency markets

This paper studies currency predictability over time. We assess predictability by testing for the presence of exploitable patterns in currency returns. To do so, we first generate consistent and parsimonious reduced-form estimates of currency expected returns and variances and then use these estimates to form dynamic trading strategies that maximize the multi-period Sharpe ratio. Our results show that currency predictability is time-varying and, for a number of currencies, has increased substantially in recent times, casting doubt on the widespread view that currency pricing may be on a path of convergence towards efficiency. We find, however, that currency markets learn in an efficient manner and a close relation between our strategies and indices that track popular technical trading rules, namely moving average cross-over rules and the carry trade, suggesting that the technical rules represent heuristics by which professional market participants exploit currency mispricing.     

Bitcoin as a Complement to Emerging Market Currencies

Bitcoin is a digital currency that has gained significant traction as an economic instrument. Despite its rise, it has received little attention from the scholarly community. This study is one of the first studies to examine Bitcoin’s use as a complement to emerging markets currencies; more specifically, I analyze the value and volatility of Bitcoin relative to emerging market currencies and explore ways in which Bitcoin can complement emerging market currencies. The results suggest that Bitcoin has characteristics that make it well-suited to work as a complement to emerging market currencies and that there are ways to minimize Bitcoin’s risks.     

2011年上半年银行间市场运行报告

2011年上半年,银行间市场运行平稳,交易稳步增长。主要特点是：货币市场资金面大幅收紧,主要货币市场利率大幅上升;银行间国债指数震荡上扬,国债收益率曲线整体上移;人民币对美元汇率中间价保持较快升值速度,非美货币即期交易显著活跃;利率互换交易量大幅增长,利率互换交易确认服务推出;汇率衍生品市场交易稳定增长,期权产品上线完善外汇衍生产品体系。     

Are Open Markets Good for Foreign Investors and Emerging Nations?

Although policymakers of emerging nations routinely brand foreign capital as "hot money" and hold it responsible for the ills of their economies, this article suggests that the experience of opening up their markets to overseas investors has been largely beneficial for the host countries. Based on their own recent study, the authors report that when emerging economies open their markets, the level of stock prices tends to rise without an associated increase in volatility, and more capital becomes available for domestic investment at a lower cost. The stock markets also appear to become more efficient, thus resulting in a better allocation of resources. Furthermore, the inflow of foreign capital does not lead to higher inflation or stronger currencies, nor does the volatility of inflation or exchange rates increase. If some countries experience large capital outflows with damaging consequences, the culprit is not foreign investors, but rather policymakers' futile attempt to defy market forces and the failure of their economies to put the capital to productive uses.
The authors' analysis also suggests that, when the recent turmoil in emerging markets is set in the context of a longer-run historical perspective, nothing appears to have changed that would materially alter the prospects for investing in emerging markets. The recent market volatility and currency crises in emerging nations are by no means extraordinary—indeed, the currencies of many developing countries fall routinely. What distinguishes the Mexican and Thai currency crises from such run-of-the-mill devaluations is that both governments resisted the inevitable until market forces brought about a crash. The recent emerging market currency crises should accordingly be viewed as more or less predictable "road bumps" that can be expected when the policymakers of emerging economies gradually—and grudgingly—relinquish their power to the markets.     

Nonparametric testing of the high-frequency efficiency of the 1997 Asian foreign exchange markets

Sherry’s nonparametric pattern tests for neural information processing are used to ascertain if the Asian foreign exchange (FX) rates followed random walks [Sherry, C.J., 1992. The Mathematics of Technical Analysis: Applying Statistics to Trading Stocks, Options and Futuresm Probus, Chicago]. The stationarity and serial independence of the price changes are tested on minute-by-minute data for nine Asian currencies from 1 January 1997 to 30 December 1997. The efficiency of these FX markets before and after the Asian currency ‘regime discontinuity’ are compared. The Thai baht (THB), Malaysian ringgit (MYR), Indonesian rupiah (IDR) and Singapore dollar (SGD) exhibited non-stationary behavior during the entire year, and gave evidence of a trading regime break, while the Phillipines’ peso (PHP), Taiwan dollar (TWD), Japanese yen (JYP) and German deutschmark (DEM) remained stationary, with the US dollar (USD) as numeraire. However, each half-year regime showed stationarity, indicating stable and nonchaotic trading regimes for all currencies, despite their high volatilities, except for the MYR, which exhibited non-stationarity in the second half of 1997. The Thai baht traded nonstationarily in the first half of 1997, but stationarily in the second half. while the TWD reversed that trading pattern. Based on Sherry’s four tests for serial independence, none of the currencies exhibited complete independence. Thus no Asian currency market—including the JYP—exhibited complete efficiency in 1997, in particular when compared with the highly efficient DEM. Remarkably, the PHP remained as efficient as the JYP throughout 1997.     

Deep networks for predicting direction of change in foreign exchange rates

Trillions of dollars are traded daily on the foreign exchange (forex) market, making it the largest financial market in the world. Accurate forecasting of forex rates is a necessary element in any effective hedging or speculation strategy in the forex market. Time series models and shallow neural networks provide acceptable point estimates for future rates but are poor at predicting the direction of change and, hence, are not very useful for supporting profitable trading strategies. Machine learning classifiers trained on input features crafted based on domain knowledge produce marginally better results. The recent success of deep networks is partially attributable to their ability to learn abstract features from raw data. This motivates us to investigate the ability of deep convolution neural networks to predict the direction of change in forex rates. Exchange rates for the currency pairs EUR/USD, GBP/USD and JPY/USD are used in experiments. Results demonstrate that trained deep networks achieve satisfactory out‐of‐sample prediction accuracy.     

Flight-to-quality and correlation between currency and stock returns

We document that capital flows in and out of emerging or developed markets are sensitive to global equity market conditions. Capital tends to move out of emerging into developed countries in global down markets, leading to depreciation (appreciation) of emerging (developed) currencies. This generates a positive (negative) correlation between currency and equity in emerging (developed) markets which is amplified by the magnitude of the capital movement. We also verify that hedging currency risks may undo the natural hedge and increase the total return volatility under negative correlation.     

Currency momentum strategies

We provide a broad empirical investigation of momentum strategies in the foreign exchange market. We find a significant cross-sectional spread in excess returns of up to 10% per annum (p.a.) between past winner and loser currencies. This spread in excess returns is not explained by traditional risk factors, it is partially explained by transaction costs and shows behavior consistent with investor under- and overreaction. Moreover, cross-sectional currency momentum has very different properties from the widely studied carry trade and is not highly correlated with returns of benchmark technical trading rules. However, there seem to be very effective limits to arbitrage that prevent momentum returns from being easily exploitable in currency markets.     

Time and frequency dynamics of connectedness and hedging performance in global stock markets: Bitcoin versus conventional hedges

Some studies have revealed the hedging ability of Bitcoin against stock markets, but the knowledge of how it compares with other hedges is in its infancy. This paper presents the first study on time-frequency domain connectedness and hedging among five hedges (Bitcoin, crude oil, commodities, gold and the U.S. dollar (USD) index) and four stock indices (developed markets ex U.S., emerging markets ex China, U.S. and China). We find that the connectedness between hedges and stock markets varies by time across time horizons. Specifically, the connectedness between Bitcoin and stock indices is the smallest among all hedges, especially for the short horizon. Gold and USD are isolated from other markets at longer horizons. The hedging ratio, optimal portfolio weights and hedging effectiveness also vary across investment horizons. For short-term investment, gold has better hedging effectiveness, especially for emerging stock markets and the U.S. stock market. For median- and long-term investment, USD has better performance, especially for developed markets ex U.S. and emerging stock markets. Additionally, although Bitcoin has good hedging properties, it has high volatility compared with other hedging assets. In other words, if Bitcoin is included in a portfolio, investors should pay attention to its wide variation. These empirical findings highlight the important role that gold and USD play in hedging against global stock markets.     

2014年11月银行间市场运行报告

11月,银行间市场的主要运行特点是：人民币市场资金面维持宽松格局,长期利率继续走低、短期利率升而不高;债券市场交投活跃,国债收益率曲线继续下移;人民币对美元交易汇率月度走弱,对非美货币汇率普遍继续走强,直接交易明显活跃;人民币利率互换收盘曲线整体下移,交易量同比显著增长;外汇衍生品交易连续超越即期,期权交易涨势突出。     

Volatility linkage among currency futures markets during US trading and non-trading periods

This paper examines the volatility transmission across different currency markets during trading and non-trading periods. Using vector autoregressive analysis (VAR), we find similar patterns between information flows during trading and non-trading hours of the US currency futures exchange. The results indicate that trading-hour information and non-trading-hour information have similar effects on currency prices and that the markets do not differentiate information based upon the timing of its release. Our study observes that currencies exhibit different levels of global linkage and appear to play different informational roles in the currency market. Additionally, this study observes a trend toward increased integration among the currency futures markets.     

Can technical trading beat the foreign exchange market in times of crisis?

I examine the profitability of three simple foreign exchange technical trading rules (moving average, momentum, and relative strength index) before, during, and after the 2007–2008 global financial crisis. These rules significantly improve profitability during the crisis (as opposed to before and after it). The moving average rule significantly increases profitability for exchange rate changes during the crisis. The momentum and relative strength index rules generate significant positive excess currency returns (defined as the difference between the forward premium and spot rate changes), but this profitability is not visible in spot rate changes. These findings are robust for portfolios of developed and emerging market currencies as well as for bilateral exchange rates.     

Technological bias at the exchange rate market

Prediction of exchange rates has been a topic for debate in economic literature since the late 1980s. The recent development of machine learning techniques has spurred a plethora of studies that further improves the prediction models for currency markets. This high-tech progress may create challenges for market efficiency along with information asymmetry and irrationality of decision-making. This technological bias emerges from the fact that recent innovative approaches have been used to solve trading tasks and to find the best trading strategies. This paper demonstrates that traders can leverage technological bias for financial market forecasting. Those traders who adapt faster to the changes in market innovations will get excess returns. To support this hypothesis we compare the performance of deep learning methods, shallow neural networks with baseline prediction methods and a random walk model using daily closing rate between three currency pairs: Euro and US Dollar (EUR/USD), British Pound and US Dollar (GBP/USD), and US Dollar and Japanese Yen (USD/JPY). The results demonstrate that deep learning achieves higher accuracy than alternate methods. The shallow neural network outperforms the random walk model, but cannot surpass ARIMA accuracy significantly. The paper discusses possible outcomes of the technological shift for financial market development and accounting conforming also to adaptive market hypothesis.     

Oil market uncertainty and excess returns on currency carry trade

This paper examines the role of oil market uncertainty on currency carry trade payoffs. We find that oil market uncertainty can impact currency carry trade excess returns. When oil market uncertainty rises, expected currency excess returns will increase. Our findings are robust to alternative measures of oil market uncertainty and, after controlling for traditional uncertainties, different types of oil shocks. The results also hold well in both developed and emerging markets, as well as for oil-related currencies, non-oil currencies, commodity currencies, and non-commodity currencies. Additionally, oil market uncertainty can be priced in the cross section of currency carry trade excess returns. This effect can be explained by investors becoming more risk averse under high oil market uncertainty and requiring greater compensation for bearing such risk. Moreover, our measure of oil market uncertainty, the downside risk from the oil market, is quite different from that of traditional aggregate measures.     

Forecasting Emerging Market Exchange Rates from Foreign Equity Options

The use of derivatives to infer future exchange rates has long been a subject of interest in the international finance literature. With the recent currency crises in Mexico, Southeast Asia, and Brazil, work on exchange rate expectations in emerging markets is of particular interest. For some emerging markets, foreign equity options are the only liquid exchange‐traded derivatives with currency information embedded in their prices. Given that emerging markets sometimes undergo currency realignment with discrete jumps in their exchange rate, estimation of risk‐neutral probability density functions from foreign equity option data provides valuable evidence concerning market expectations. To illustrate the use of foreign equity options in estimating market beliefs, we consider Telmex options around the 1994 peso devaluation and find evidence that markets anticipated the change in the Mexican government's foreign exchange policy.     

Impact of portfolio flows and heterogeneous expectations on FX jumps: Evidence from an emerging market

Motivated by the recent currency crisis in Turkey, we investigate the role of portfolio flows and heterogeneous expectations on the high frequency stochastic jump behavior of the US dollar value against the Turkish lira, one of the most traded emerging market currencies in the world. We group the detected jumps into different types with respect to their direction (up and down) and timing (local and off-shore trading hours). For each type of jumps, we examine their relation with portfolio flows (in the form of equity and bond flows, and carry trade activity), and dispersion in beliefs for the future exchange rate level and key macroeconomic variables. We find that inflows to both equity and bond markets, and increasing carry trade activity significantly reduce the size of jumps and (partially) their intensity. On the other hand, heterogeneous expectations for the future exchange rate level, consumer price index and gross domestic product are found to increase the number of jumps and the average jump size.     

Joint dynamics of foreign exchange and stock markets in emerging Europe

This paper proposes an ideal specification for studying joint dynamics of emerging stock and foreign exchange markets, and applies it on European emerging markets where this interaction is of particular significance due to large external deficits. Results show that global developed and emerging stock market returns account for a large proportion of the (permanent) comovement between the stock index and currency value. The residual interaction after controlling for global indexes is small. The sign of the currency-stock market relationship is driven by dependence on foreign capital (predominantly positive for countries which are net receivers of foreign portfolio capital) and depth of the local stock market. Bank of Russia's intensive involvement in the currency market delays Ruble's response to global information. Emerging European currencies predict reversals in global equity indexes several months ahead.     

Overreaction and underreaction in the foreign exchange market

Research has documented overreaction and underreaction for stocks and stock market indices, but it has not yet analyzed these phenomena with regard to currency exchange rates. This paper examines exchange rate changes following extreme 1-day fluctuations for currencies in industrialized and emerging markets. In this study, the exchange rate is defined as the number of foreign currency units per US dollar. An overreaction phenomenon for currencies in emerging markets and an underreaction phenomenon for currencies in industrial markets are found. Each extreme 1-day currency fluctuation event is classified according to the type of underlying reason as described in the Wall Street Journal. Events for which no announcements (undefined events) were found are associated with a stronger tendency toward overreaction than those events for which an explanation was given (defined events). This suggests that investors overreact more when the source of the extreme fluctuation is largely unknown. The defined events are classified into two groups: economic events and political events. There is some evidence that political events are associated with a stronger tendency toward overreaction than economic events. These findings can be attributed to uncertainty. Political events (e.g., civil uprising) should be more difficult to assess than economic events (e.g., the release of an inflation report), and undefined events should be associated with the largest degree of uncertainty. Cross-sectional analysis is used to relate post-event exchange rate changes to the magnitude of the initial exchange rate change, leakage, day of the week effects, type of currency (from emerging or industrial market), and the type of announcement (economic, political, or undefined) that appeared in the Wall Street Journal. The cross-sectional analysis confirms that currencies in emerging markets experience stronger degrees of overreaction than those of industrial markets, even after controlling for potentially confounding factors. Moreover, it confirms that undefined events experience stronger degrees of overreaction than defined events, even when controlling for other factors.