Heuristic learning in intraday trading under uncertainty

Until recently economists focused on structural models that were constrained by a lack of high-frequency data and theoretical deficiencies. Little academic research has been invested in actually trying to build successful real-time trading models for the high-frequency foreign exchange market, which is characterized by inherent complexity and heterogeneity. The present work opens new directions for inference on market efficiency in an attempt to account for the use of technical analysis by practitioners over many years now. This paper presents a heuristic model that efficiently emulates the dynamic learning of intraday traders. The proposed setup incorporates agent beliefs, preferences and expectations while it integrates the calibration of technical rules by means of adaptive training. The study focuses on EUR/USD which is the most liquid and widely traded currency pair. The data consist of a very large tick-by-tick sample of bid and ask prices covering many trading periods to enhance robustness in the results. The efficiency of a technical trading strategy based on the proposed model is investigated in terms of directional predictability. The heuristic learning system is compared against many non-linear models, a random walk and a buy & hold strategy. Based on statistical testing it is shown that, with the inclusion of transaction costs, the profitability of the new model is consistently superior. These findings provide evidence of technical predictability under incomplete information and can be justified by invoking the existence of heterogeneity caused by many factors affecting market microstructure. Overall, the results suggest that the proposed model can be used to improve upon traditional technical analysis approaches.     

Heterogeneous real-time trading strategies in the foreign exchange market

The foreign exchange (FX) market is worldwide, but the dealers differ in their geographical locations (time zones), working hours, time horizons, home currencies, access to information,transaction costs, and other institutional constraints. The variety of time horizones is large: from intra-day dealers, who close their positions every evening, to long-term investors and central banks. Depending on the constraints, the different market participats need different strategies to reach their goal, which is usually maximizing the profit, or rather a utility function including risk. Different intra-day trading strategies can be studied only if high-density data are available. Oslen & Associates (O & A) has collected and analysed large amounts of FX quotes by market makers around the clock (up to 5000 non-equally spaced prices per day for the German mark against US$). Based on these data, a set of real-time intra-day trading models has been developed. These models give explicit trading recommendations under realistic constraints. They are allowed to trade only during the opening hours of a market, depending on the time zone and local holidays. The models have been running real-time for more than three years, thus leading to an ex ante test. The test results, obtained with a risk-sensitive performance measure, are presented. All these trading models are profitable, but they differ in their risk behaviour and dealing frequency. If a certain profitable intra-day algorithm is tested with different working hours, its success can considerably change. A systematic study shows that the best choice of working hours is usually when the most important markets for the particular FX rate are active. All the results demonstrate that the assumption of a homogeneous 24-hour FX market with identical dealers, following an identical ‘rational expectation’, is far from reality. To explain the market dynamics, a heterogeneous model of the market with different types of dealers is more appropriate.     

The confusing time-series behaviour of real exchange rates: Are asymmetries important?

Evidence regarding the time-series properties of real exchange rates is mixed. There is evidence that such rates exhibit both non-stationary and stationary behaviour. The current dominant belief is that rates are non-linear stationary, however, this is not accepted without question. This paper re-examines the time-series properties of five US dollar real exchange rates and argues that the confusing time-series properties arise largely as each series examined exhibits periods of non-stationary and stationary behaviour such that the sample over which any empirical exercise is conducted is of importance. However, extending a typical non-linear model used within the literature to allow for asymmetries improves the models ability to fit the data. Therefore, our results suggest that modelling asymmetries between positive and negative real exchange rate deviations is of importance, whereas extant research has typically rules out asymmetry. Indeed a forecasting exercise conducted over a 1-year horizon is particularly supportive of this model. Such a finding is of importance not only for academics but also finance practitioners involved in trading and portfolio management and finance managers who act in the foreign exchange market for goods market trading. It remains for future research to theoretically motivate the asymmetries found here.     

The market microstructure approach to foreign exchange: Looking back and looking forward

Research on foreign exchange market microstructure stresses the importance of order flow, heterogeneity among agents, and private information as crucial determinants of short-run exchange rate dynamics. Microstructure researchers have produced empirically-driven models that fit the data surprisingly well. But FX markets are evolving rapidly in response to new electronic trading technologies. Transparency has risen, trading costs have tumbled, and transaction speed has accelerated as new players have entered the market and existing players have modified their behavior. These changes will have profound effects on exchange rate dynamics. Looking forward, we highlight fundamental yet unanswered questions on the nature of private information, the impact on market liquidity, and the changing process of price discovery. We also outline potential microstructure explanations for long-standing exchange rate puzzles.     

Further insights on the puzzle of technical analysis profitability

This paper extends current results concerning technical analysis efficiency on the foreign exchange market and attempts to determine whether filtering the raw exchange rate series with some trading rule significantly changes its characteristics. Because of the non-normality of exchange rate series, bootstrap methods are used on the main daily exchange rates since 1974 to show technical analysis performance. The technical analysis strategy tested generates returns whose distribution is significantly different from the basic series. The robustness of the results is tested in and out-of-sample and an explanation of the technical analysis performance based on its filtering properties is suggested.     

Order flow, bid-ask spread and trading density in foreign exchange markets

This paper examines the implications of market microstructure for foreign exchange markets. We argue that the usual order flow model needs to be recast in broader terms to incorporate the transaction costs of liquidity and the limitation of price discovery through order flows that involve low trading density currencies. Using a daily data set, we find that order flows are inadequate when it comes to explaining the changes in the low trading density currencies. Alternatively, within the high trading density, both order flows and bid-ask spreads significantly affect the foreign exchange rate returns. Our findings suggest that the order flow model is better at incorporating these microstructure effects except for some currencies with a very high level of trading density.     

跨境关联交易、外汇资金流动与外汇管理

跨境关联交易是涉及境内外关联方之间转移资源或义务的交易活动,它与外汇资金的流动密切相关,对一国的外汇管理具有不可忽视的影响。特别是在当前我国国际收支持续大幅双顺差、外汇储备不断增加的形势下,更需要高度关注跨境关联交易的各种风险。     

Bangladesh’s trade partners and the J-curve: an asymmetry analysis

Separating currency appreciations from depreciations and using non-linear models in recent literature have improved discovering significant link between the trade balance and the exchange rate. We add to this growing literature by considering the experience of Bangladesh with 11 trading partners. When a linear model was used, support for the J-curve effect was present only with one small partner. However, when a non-linear model was used, support increased to three countries including the largest partner, the United States, which accounts for more than 12% of Bangladesh’s trade. Furthermore, the non-linear models supported short-run asymmetry adjustment as well as short-run asymmetry effects of exchange rate changes in most cases. However, long-run asymmetric effects were limited to a few.     

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.     

Trading of foreign investors and stock returns in an emerging market - Evidence from Vietnam

This article investigates the impact of foreign investors' trading on stock returns in Vietnam, a key emerging market. We utilize a time series data set of foreign investors' trading volume and market returns of the Ho Chi Minh City stock exchange over an extended time frame before and after global financial crisis. The results indicate that foreign investors are positive feedback traders in Vietnam stock market. The findings also reveal the timing ability and trading strategy of foreign investors. The paper offers strong implications for market participants and portfolio investment.     

Comparing Trading Performance of the Constant and Dynamic Hedge Models: A Note

The constant and dynamic hedge models, with the presence of transaction costs are compared for the Share Price Index futures contract trading on the Sydney Futures Exchange. The optimal hedge ratio is estimated by using a dynamic, bivariate two-stage model for the return equation with a dynamic GARCH error structure for the conditional hedge ratios. When portfolio projections are compared based on their profit positions (net of transaction costs), the GARCH hedge model dominates the next best competitor in terms of trading profit.     

The role of attribute selection in Deep ANNs learning framework for high‐frequency financial trading

In financial trading, technical and quantitative analysis tools are used for the development of decision support systems. Although these traditional tools are useful, new techniques in the field of machine learning have been developed for time‐series forecasting. This paper analyses the role of attribute selection on the development of a simple deep‐learning ANN (D‐ANN) multi‐agent framework to accomplish a profitable trading strategy in the course of a series of trading simulations in the foreign exchange market. The paper evaluates the performance of the D‐ANN multi‐agent framework over different time spans of high‐frequency (HF) intraday asset time‐series data and determines how a set of the framework attributes produces effective forecasting for profitable trading. The paper shows the existence of predictable short‐term price trends in the market time series, and an understanding of the probability of price movements may be useful to HF traders. The results of this paper can be used to further develop financial decision‐support systems and autonomous trading strategies for the financial market.     

外汇储备、外汇交易量与CHIBOR利率的VAR模型(2000～2004)——兼论“三元悖论”下冲销干预与货币政策的独立性

本文以“三元悖论”为切入点,从总量与结构两方面考察当前结售汇制度对商业银行外汇头寸及外汇交易量的影响,进而考察在货币政策时滞的影响下央行冲销干预的效果以及货币政策的独立性。结论认为:我国外汇储备成因中政策性制度安排(结售汇)作用突出,现行结售汇业务导致外汇交易量受到外汇储备的冲击,冲销干预的有效性十分有限且不确定性很强。在CHIBOR利率的波动中,外汇储备和外汇交易量的作用不可忽视,同时外汇交易量的波动中,外汇储备与CHIBOR利率的冲击作用贡献明显,货币政策独立性受到侵蚀。     

Implied Spot Rates as Predictors of Currency Returns: A Note

Currency call option transactions data and the Black-Scholes option pricing model, as modified by Merton for continuous dividends and as adapted to currency options by Biger and Hull and by Garman and Kohlhagen, are used to imply spot foreign exchange rates. The proportional deviation between implied and simultaneously observed spot rates is found to be a direct and statistically significant determinant of subsequent returns on foreign currency holdings after controlling for interest rate differentials. Further, an ex ante trading rule reveals that the additional information contained in implied rates often is sufficient to generate significant economic profits.     

On market efficiency of Asian foreign exchange rates: evidence from a joint variance ratio test and technical trading rules

This study employs a joint variance ratio test and technical trading rules to examine the random walk behavior for nine Asian foreign exchange rates for the period 1988–1995. The joint variance ratio test results suggest that there is little evidence of serial correlations in the daily exchange rate series. The results also indicate that, in general, the moving average and channel trading rules do not generate significant, positive 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.     

FX technical trading rules can be profitable sometimes!

This paper investigates the profitability of technical trading rules in the foreign exchange market taking into account data snooping bias and transaction costs. A universe of 7650 trading rules is applied to six currencies quoted in U.S. dollars over the 1994:3–2014:12 period. The Barras, Scaillet, and Wermers (2010) false discovery rate method is employed to deal with data snooping and it detects almost all outperforming trading rules while keeping the proportion of false discoveries to a pre-specified level. The out-of-sample results reveal a large number of outperforming rules that are profitable over short periods based on the Sharpe ratio. However, they are not consistently profitable and so the overall results are more consistent with the adaptive markets hypothesis.     

The Exchange Rate in the Presence of Transaction Costs: Implications for Tests of Purchasing Power Parity

With transaction costs for trading goods, the nominal exchange rate moves within a band around the nominal purchasing power parity (PPP) value. We model the behavior of the band and of the exchange rate within the band. The model explains why there are below-unity slope coefficients in regression tests of PPP, and why these increase toward unity under hyperinflation or with low-frequency data. Our results are independent of the presence of nontraded goods in the economy.     

Portfolio optimization in discrete time with proportional transaction costs under stochastic volatility

This paper is devoted to evaluating the optimal self-financing strategy and the optimal trading frequency for a portfolio with a risky asset and a risk-free asset. The objective is to maximize the expected future utility of the terminal wealth in a stochastic volatility setting, when transaction costs are incurred at each discrete trading time. A HARA utility function is used, allowing a simple approximation of the optimization problem, which is implementable forward in time. For each of various transaction cost rates, we find the optimal trading frequency, i.e. the one that attains the maximum of the expected utility at time zero. We study the relation between transaction cost rate and optimal trading frequency. The numerical method used is based on a stochastic volatility particle filtering algorithm, combined with a Monte-Carlo method. The filtering algorithm updates the estimate of the volatility distribution forward in time, as new stock observations arrive; these updates are used at each of these discrete times to compute the new portfolio allocation.