nach oben

Empirical Economics

Erschienen in:

01.12.2015

Informed traders’ arrival in foreign exchange markets: Does geography matter?

verfasst von: Ramazan Gençay, Nikola Gradojevic, Richard Olsen, Faruk Selçuk

Erschienen in: Empirical Economics | Ausgabe 4/2015

Einloggen

Aktivieren Sie unsere intelligente Suche, um passende Fachinhalte oder Patente zu finden.

search-config

KI-gestützte Suche

Aus

Abstract

This article critically investigates the possibility that private information offering systematic profit opportunities exists in the spot foreign exchange market. Using a unique dataset with trader-specific limit and market order histories for more than 10,000 traders, we detect transaction behavior consistent with the informed trading hypothesis, where traders consistently make money. We then work within the theoretical framework of a high-frequency version of a structural microstructure trade model, which directly measures the market maker’s beliefs. Both the estimates of the trade model parameters and our model-free analysis of the data suggest that the time-varying pattern of the probability of informed trading is rooted in the strategic arrival of informed traders on a particular day-of-week, hour-of-day, or geographic location (market).

Vorheriger Artikel Quantity theory is alive: the role of international portfolio shifts

Nächster Artikel On the distribution of links in the interbank network: evidence from the e-MID overnight money market

Sie haben noch keine Lizenz? Dann Informieren Sie sich jetzt über unsere Produkte:

Springer Professional "Wirtschaft"

Online-Abonnement

Mit Springer Professional "Wirtschaft" erhalten Sie Zugriff auf:

über 67.000 Bücher
über 340 Zeitschriften

aus folgenden Fachgebieten:

Bauwesen + Immobilien
Business IT + Informatik
Finance + Banking
Management + Führung
Marketing + Vertrieb
Versicherung + Risiko

Jetzt Wissensvorsprung sichern!

Jetzt informieren

Springer Professional "Wirtschaft+Technik"

Online-Abonnement

Mit Springer Professional "Wirtschaft+Technik" erhalten Sie Zugriff auf:

über 102.000 Bücher
über 537 Zeitschriften

aus folgenden Fachgebieten:

Automobil + Motoren
Bauwesen + Immobilien
Business IT + Informatik
Elektrotechnik + Elektronik
Energie + Nachhaltigkeit
Finance + Banking
Management + Führung
Marketing + Vertrieb
Maschinenbau + Werkstoffe
Versicherung + Risiko

Jetzt Wissensvorsprung sichern!

Jetzt informieren

Nur mit Berechtigung zugänglich

As in Dacorogna et al. (2001) and, recently, Kaul and Sapp (2009), we use the following geographic regions to cover the 24-h trading day: 03:00–07:00 EST (Europe only), 07:00–11:00 EST (both Europe and North America), 11:00–15:00 EST (North America only), 15:00–19:00 EST (post-North America), and 19:00–03:00 EST (Asia).

For example, in the framework by Lyons (2001), customers are the primary source of private information, but the implications of their strategic behavior are not considered.

This line of reasoning has also been documented for equity markets. For example, Foster and Viswanathan (1994) find that the optimal strategy of better informed traders is to delay trading on his or her private information in the early rounds of trading, while trading very intensely on the common information.

In a related study, Easley et al. (2008) find that the trade composition does not forecast intraday volatility. Lei and Wu (2005) also examine the time series properties of the PIN for a panel of stocks, arguing that the Easley et al. (1996b) model should be extended with the time-varying PIN.

See Triennial Central Bank Survey of Foreign Exchange and Derivatives Market Activity in April 2010: http://www.bis.org/publ/rpfxf10t.

www.fxall.com and www.currenex.com.

We are grateful for this and other useful comments from an anonymous referee.

www.oanda.com.

One basis point is defined as 1/100th of a percentage point.

In 2003/2004, the platform of OANDA did not have many decision support tools, so the traders were not well connected to the professional trading community. If traders can generate profits in a highly liquid and efficient market, such as the FX market, without access to “inside” information, then this raises interesting questions of why and how this can be feasible.

By “active,” we refer to traders that did not simply receive interest on their positions, but placed orders during this period. The market share of these traders is approximately 86.4 %.

The next most active currency pairs are USD-CHF (7.88 % share), GBP-USD (7.81 % share), USD-JPY (6.42 % share), and AUD-USD (5.98 % share).

Of the 10,000 registered traders, about 5,000 were active in the EUR–USD trading over the sample period.

Trader ID is withheld to preserve data confidentiality.

We also plot the hour-of-day indices for the raw data that use unadjusted $B_t$ and $S_t$ (dashed line). Similar arrival patterns are observed for the two types of traders. Thus, “hidden” hour-of-day patterns are present even after $B_t$ and $S_t$ are de-seasonalized. Since these effects are strong enough to persist even after adjusting for intraday time dependency, we will concentrate on the de-seasonalized data for the remainder of the paper.

The day-of-week indices, denoted by $SI_i$ ($i\in \{\alpha , \delta , \varepsilon , \mu , \mathrm{PIN}\}$), are found using the ratio-to-moving average method.

The estimates over 145 days are stable with regard to the reasonable choice of their starting values. The only case in which the estimates begin to substantially change is when $\mu _0>200$ and $\varepsilon _0>200$.

Easley et al. (1997b) test for the independence assumption and find that information events in their dataset are independent.

Under the null hypothesis of the randomness of information events across hours, the total number of runs $r$ (sequences of ones or zeros) is normally distributed with $\bar{r}=\frac{2e_i n_i}{e_i+n_i} +1$ and $\sigma _r^2=\frac{(\bar{r} -1)(\bar{r}-2)}{(e_i+n_i)-1}$.

For the null hypothesis of independence (or randomness) of information events over $I$=24 h, this test is based on the following statistic: $Q_L=I(I+2)\sum _{\tau =1}^{L}\frac{\hat{\rho }^2_\tau }{I-\tau }$, where $L$ is typically chosen to be substantially smaller than $I$ and $\hat{\rho }^2_\tau $ is the sample autocorrelation coefficient at lag $\tau $.

One may expect the arrival of informed traders to be related only to the information flow. However, in this setting, they appear to use their private information strategically. Another possibility is that informed traders enter the market not only to establish speculative positions (information effects), but also to adjust their currency inventory (inventory effects), as previously mentioned.

Cubic spline is an interpolation method that fits a curve by constructing piecewise third-order polynomials that pass through original data points (Burden and Faires 2004).

The Granger causality tests for the hourly arrivals yield findings similar to those for the daily arrival rates: $TT_t - |K_t|$ Granger-causes $|K_t|$, but not vice-versa.

This point is also made in Wuensche (2007), who proposes mixed Poisson distributions to capture the characteristics of the trade data. Other potential weaknesses of the Easley et al. (1996b) model can be found in Venter and De Jongh (2004).

This assumption may seem inappropriate, given that it rules out any strategic behavior. As shown in Sect. 2.3, informed traders have some tendency to trade strategically. Therefore, we concur that the assumption of risk neutrality needs defending, but we retain it for the sake of the model applicability.

To derive Eq. (11), the term $\ln [x^{M_i}(\mu +\varepsilon )^{B_i+S_i}]$ is simultaneously added to the first sum and subtracted from the second sum in Eq. (10). This is done to increase computational efficiency and to ensure convergence in the presence of a large numbers of buys and sells, as is the case in our dataset.

Albuquerque R, De Francisco E, Marques L (2008) Marketwide private information in stocks: forecasting currency returns. J Finance 63(5):2297–2343CrossRef

Bjønnes G, Rime D (2005) Dealer behavior and trading systems in foreign exchange markets. J Finan Econ 75(3):571–605CrossRef

Bjønnes G, Osler C, Rime D (2008) Asymmetric information in the interbank foreign exchange market, norges Bank Working Paper

Boehmer E, Grammig J, Theissen E (2007) Estimating the probability of informed trading—does trade misclassification matter? J Finan Mark 10(1):26–47CrossRef

Breedon F, Ranaldo A (2013) Intraday patterns in FX returns and order flow. J Money Credit Bank 45(5):953–965CrossRef

Burden R, Faires JD (2004) Numerical Analysis. Brooks Cole, Florence

Covrig V, Melvin M (2002) Asymmetric information and price discovery in the FX market: does Tokyo know more about the yen? J Empir Finance 9:271–285CrossRef

Dacorogna M, Gençay R, Muller U, Olsen R, Pictet O (2001) An introduction to high-frequency finance. Academic Press, San Diego

D’Souza C (2008) Price discovery across geographic locations in the foreign exchange market. Bank of Canada Review pp 17–25

Easley D, O’Hara M (1992) Time and the process of security prices adjustment. J Finance 47:577–605CrossRef

Easley D, Kiefer N, O’Hara M (1996a) Cream-skimming or profit-sharing? The curious role of purchased order flow. J Finance 51:811–833CrossRef

Easley D, Kiefer N, O’Hara M, Paperman J (1996b) Liquidity, information and infrequently traded stocks. J Finance 51:1405–1436CrossRef

Easley D, Kiefer N, O’Hara M (1997a) The information content of the trading process. J Empir Finance 4:159–185CrossRef

Easley D, Kiefer N, O’Hara M (1997b) One day in the life of a very common stock. Rev Finan Stud 10:805–835CrossRef

Easley D, Engle R, O’Hara M, Wu L (2008) Time-varying arrival rates of informed and uninformed trades. J Finan Econ 6(2):171–207

Evans M, Lyons R (2002) Order flow and exchange rate dynamics. J Political Econ 110:170–180CrossRef

Evans M, Lyons R (2005) Meese-rogoff redux: micro-based exchange rate forecasting. Am Econ Rev 95(2):405–414CrossRef

Evans M, Lyons R (2012) Exchange rate fundamentals and order flow. Q J Finance 2(4):1250,018CrossRef

Foster F, Viswanathan S (1994) Strategic trading with asymmetrically informed traders and long-lived information. J Finan Quant Anal 29(4):499–518CrossRef

Gallant A, Rossi P, Tauchen G (1992) Stock prices and volume. Rev Finan Stud 5(2):199–242CrossRef

Gençay R, Gradojevic N (2013) Private information and its origins in an electronic foreign exchange market. Econ Model 33:86–93CrossRef

Goldstein M, Van Ness BF, Van Ness RA (2006) The intraday probability of informed trading on the NYSE. Adv Quant Anal Financ Acc 3:139–158CrossRef

Gradojevic N (2007) The microstructure of the Canada/U.S. dollar exchange rate: a robustness test. Econ Lett 94(3):426–432CrossRef

Hau H (2001) Location matters: an examination of trading profits. J Finance 56(5):1959–1983CrossRef

Heimer R, Simon D (2012) Facebook finance: how social interaction propagates active investing, brandeis University Working Paper

Kaul A, Sapp S (2009) Trading activity, dealer concentration and foreign exchange market quality. J Bank Finance 33(11):2122–2131CrossRef

King M, Rime D (2010) The ${\$}4$ trillion question: What explains FX growth since the 2007 survey? BIS Quarterly Review pp 27–42

Lee C, Ready M (1991) Inferring trade direction from intraday data. J Finance 46:733–746CrossRef

Lei Q, Wu G (2005) Time-varying informed and uninformed trading activities. J Finan Mark 8(2):153–181MathSciNetCrossRef

Ljung G, Box G (1978) On a measure of lack of fit in time series models. Biometrika 65:297–303CrossRefMATH

Lyons R (1995) Test of microstructural hypotheses in the foreign exchange market. J Finan Econ 39:321–351CrossRef

Lyons R (2001) The microstructure approach to exchange rates. The MIT Press, Cambridge

Madhavan A, Smidt S (1993) An analysis of changes in specialist inventories and quotations. J Finance 48:1595–1628CrossRef

Marsh IW, O’Rourke C (2005) Customer order flow and exchange rate movements: Is there really information content?, working Paper

Menkhoff L, Schmeling M (2008) Local information in foreign exchange markets. J Int Money Finance 27(8):1383–1406CrossRef

Menkhoff L, Schmeling M (2010) Whose trades convey information? Evidence from a cross-section of traders. J Finan Mark 13(1):101–128CrossRef

Moore M, Payne R (2011) On the sources of private information in FX markets. J Bank Finance 35(5):1250–1262CrossRef

Nolte I, Nolte S (2012) How do individual investors trade? Eur J Finance 18(10):921–947MathSciNetCrossRef

Odders-White ER, Ready MJ (2008) The probability and magnitude of information events. J Finan Econ 87(1):227–248CrossRef

Osler C, Vandrovych V (2009) Hedge funds and the origins of private information in currency markets, working Paper No. 1484711

Payne R (2003) Informed trade in spot foreign exchange markets: an empirical investigation. J Int Econ 61:307–329CrossRef

Peiers B (1997) Informed traders, intervention, and price leadership: a deeper view of the microstructure of the foreign exchange market. J Finance 52(4):1589–1614CrossRef

Ranaldo A (2009) Segmentation and time-of-day patterns in foreign exchange markets. J Bank Finance 33(12):2199–2206CrossRef

Shapiro S, Wilk M (1965) An analysis of variance test for normality (complete samples). Biometrika 52(3–4):591–611MathSciNetCrossRefMATH

Venter J, De Jongh D (2004) Extending the ekop model to estimate the probability of informed trading, working Paper

Vitale P (2012) Optimal informed trading in the foreign exchange market. Eur J Finance 18(10):989–1013CrossRef

Wuensche O (2007) Using mixed Poisson distributions in sequential trade models, working Paper

Yao J (1998) Market making in the interbank foreign exchange market, working Paper No. S-98-3

Titel: Informed traders’ arrival in foreign exchange markets: Does geography matter?
verfasst von: Ramazan Gençay
Nikola Gradojevic
Richard Olsen
Faruk Selçuk
Publikationsdatum: 01.12.2015
Verlag: Springer Berlin Heidelberg
Erschienen in: Empirical Economics / Ausgabe 4/2015
Print ISSN: 0377-7332
Elektronische ISSN: 1435-8921
DOI: https://doi.org/10.1007/s00181-015-0917-z

Springer Professional

Abstract

Bitte loggen Sie sich ein, um Zugang zu Ihrer Lizenz zu erhalten.

Sie haben noch keine Lizenz? Dann Informieren Sie sich jetzt über unsere Produkte:

Springer Professional "Wirtschaft"

Springer Professional "Wirtschaft+Technik"

Weitere Artikel der Ausgabe 4/2015

Simpson’s paradox in GDP and per capita GDP growths

On the distribution of links in the interbank network: evidence from the e-MID overnight money market

A Gini approach to inequality of opportunity: evidence from the PSID

Semi-structural estimates of time-varying NAIRU based on the new Keynesian Phillips curve: evidence from Eastern European economies

The effects of fiscal shocks on the exchange rate in the EMU and differences with the USA

Sensitivity analysis for inference in 2SLS/GMM estimation with possibly flawed instruments