Carol L. Osler

Currency Orders and Exchange Rate Dynamics: An Explanation for the Predictive Success of Technical Analysis

This paper documents clustering in currency stop-loss and take-profit orders, and uses that clustering to provide an explanation for two familiar predictions from technical analysis: (1) trends tend to reverse course at predictable support and resistance levels, and (2) trends tend to be unusually rapid after rates cross such levels. The data are the first available on individual currency stop-loss and take-profit orders. Take-profit orders cluster particularly strongly at round numbers, which could explain the first prediction. Stop-loss orders cluster strongly just beyond round numbers, which could explain the second prediction.

Methodical Madness: Technical Analysis and the Irrationality of Exchange-Rate Forecasts

Substantial empirical research documents that exchange-rate forecasts are not formed rationally. This paper identifies a common technical trading signal, the head-and-shoulders pattern, as a potential source of departures from rationality in exchange-rate forecasts. Forecasts based on this pattern are evaluated for daily dollar exchange rates over 1973 to 1994, using two criteria for rationality: profitability and efficiency. Resulting profits, replicable in real-time, are tested for statistical significance using a bootstrap technique. We find that the rule is profitable, but not efficient, since it is dominated by simpler trading rules.

Head and Shoulders: Not Just a Flaky Pattern

This paper evaluates rigorously the predictive power of the head-and-shoulders pattern as applied to daily exchange rates. Though such visual, nonlinear chart patterns are applied frequently by technical analysts, our paper is one of the first to evaluate the predictive power of such patterns. We apply a trading rule based on the head-and-shoulders pattern to daily exchange rates of major currencies versus the dollar during the floating rate period (from March 1973 to June 1994). We identify head-and-shoulders patterns using an objective, computer-implemented algorithm based on criteria in published technical analysis manuals. The resulting profits, replicable in real-time, are then compared with the distribution of profits for 10,000 simulated series generated with the bootstrap technique under the null hypothesis of a random walk.

Charting: Chaos theory in disguise?

The primary hypothesis of this article is that technical modeling methods may represent crude but useful ways of exploring nonlinear qualities in data. More specifically, it is proposed that graphical technical analysis may be restated in terms of attractors and strange attractors. Further, it is suggested that technical analysis methods may allow prediction on systems of higher dimension than nonlinear methods do at this time. An objective algorithm that identifies technical patterns is applied to highdimension nonlinear data, and provides support for the primary hypothesis. This article is distinguished from previous studies in that (a) a specific linkage/equivalence between technical analysis and nonlinear forecasting is proposed, and (b) statistically significant evidence in support of this specific linkage/equivalence is presented. If this link is valid, it has important implications for the future study of technical and nonlinear analysis, which should be studied jointly, and also suggests that other disciplines applying nonlinear analysis might benefit from applying technical methods.

Foreign Exchange Market Structure, Players and Evolution

Electronic trading has transformed foreign exchange markets over the past decade, and the pace of innovation only accelerates. This formerly opaque market is now fairly transparent and transaction costs are only a fraction of their former level. Entirely new agents have joined the fray, including retail and high-frequency traders, while foreign exchange trading volumes have tripled. Market concentration among dealers has risen reflecting the heavy investments in technology. Undeterred, some new non-bank market participants have begun to make markets, challenging the traditional foreign exchange dealers on their own turf. This paper outlines the players in this market and the structure of their interactions. It also presents new evidence on how that structure has changed over the past two decades. Throughout, it highlights issues relevant to exchange rate modelling.

Currency Orders and Exchange-Rate Dynamics: Explaining the Success of Technical Analysis

This paper provides a microstructural explanation for the success of two familiar predictions from technical analysis: 1) trends tend to be reversed at predictable support and resistance levels, and 2) trends gain momentum once predictable support and resistance levels are crossed. ; The explanation is based on a close examination of stop-loss and take-profit orders at a large foreign exchange dealing bank. Take-profit orders tend to reflect price trends, and stop-loss orders tend to intensify trends. The requested execution rates of these orders are strongly clustered at round numbers, which are often used as support and resistance levels. Significantly, there are marked differences between the clustering patterns of stop-loss and take-profit orders, and between the patterns of stop-loss buy and stop-loss sell orders. These differences explain the success of the two predictions.

Survival of Overconfidence in Currency Markets

This paper tests the influential hypothesis that irrational traders will be driven out of financial markets by trading losses. The paper’s main finding is that overconfident currency dealers are not driven out of the market. Dealers with extensive experience are neither more nor less overconfident than their junior colleagues. We set the stage for this investigation by providing evidence that currency dealers display two forms of overconfidence: They underestimate uncertainty, and they overestimate their professional success. This is notable because one might have expected the opposite: currency dealers face strong incentives for accuracy, they have access to comprehensive information, and they have extensive experience.

Short-Run Exchange-Rate Dynamics: Theory and Evidence

Recent research has revealed a wealth of information about the microeconomics of currency markets and thus the determination of exchange rates at short horizons. This information is valuable to us as scientists since, like evidence of macroeconomic regularities, it can provide critical guidance for designing exchange-rate models. This paper presents an optimizing model of short-run exchange-rate dynamics consistent with both the micro evidence and the macro evidence, the first such model of which we are aware. With respect to microeconomics, the model is consistent with the institutional structure of currency markets, it accurately reflects the constraints and objectives faced by the major participants, and it fits key stylized facts concerning returns and order flow. With respect to macroeconomics, the model is consistent with most of the major puzzles that have emerged under floating rates.

Asymmetric Information in the Interbank Foreign Exchange Market

This paper provides evidence of private information in the interdealer foreign exchange market. In so doing it provides support for the hypothesis that information is an important reason for the strong positive correlation between order flow and returns. It also provides evidence that information influences order-book structure. Our data comprise the complete record of interdealer trades at a good-sized Scandinavian bank during four weeks in 1998 and 1999, including bank identities. Our results indicate that larger banks have more information than smaller banks, that the relation between order flow and returns is stronger for larger banks than smaller banks, and that larger banks exploit their information advantage in limit-order placement.

Determinants of Currency Risk Premiums

The risk premium is a function of both the interest rate differential and the gap between the current exchange rate and its long-run equilibrium in a model of the foreign exchange market with both non-speculating traders and rational speculators. If the speculators have an alternative to specializing in exchange-rate speculation, then there should be no presumption that uncovered interest rate parity will hold even approximately with a long-run equilibrium number of speculators. Furthermore, when other traders respond to interest-rate differentials, the model can give rise to a negative relationship between the interest-rate differential and the subsequent change in the exchange rate, a phenomenon that is often evident in foreign exchange markets.