• Puzzles in the Tokyo Fixing in the Forex Market: Order Imbalances and Bank Pricing
  Masahiro YamadaTakatoshi Ito

  Abstract

  “Fixing” in the foreign exchange market, in Tokyo at 10am and in London at 4pm, is a market practice that determines the bid-ask-mid-point exchange rate at a scheduled time of the day in Japan. The fixing exchange rate is then applied to the settlement of foreign exchange transactions between banks and retail customers including broker dealers, institutional investors, insurance companies, exporters and importers, with varying bid-ask spreads. The findings for the Tokyo fixing are summarized as follows. (1) Price spikes are more frequent than the London fixing. (2) The customer orders are biased toward buying the foreign currencies, and this is predictable. (3) Trading volumes and liquidity concentrate on the USD/JPY. (4) Before 2008, the fixing price set by banks was biased upward, and higher than the highest transaction price during the fixing time window; the banks were earning monopolistic profits, but this gap disappeared after 2008. (5) The fixing price is still above the average transaction prices in the fixing window, suggesting that banks make profits, but that can be understood considering the risk of maintaining the fix for the rest of the business day. And (6) calendar effects also matter for the determination of the fixing rate and the price fluctuation around fixing.

  Introduction

  “Fixing” in the foreign exchange market is a market practice that determines the bid-ask mid-point exchange rate around a pre-announced time of the day. The fixing exchange rate is then applied to the settlement of foreign exchange transactions between banks and retail customers including broker dealers, institutional investors, insurance companies, exporters and importers, with varying bid-ask spreads.

  2016.09

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• On the Nonstationarity of the Exchange Rate Process
  Hideki TakayasuMisako TakayasuTakaaki OhnishiTakatoshi ItoTsutomu WatanabeYuko Hashimoto

  Abstract

  We empirically investigate the nonstationarity property of the dollar-yen exchange rate by using an eight year span of high frequency data set. We perform a statistical test of strict stationarity based on the two-sample KolmogorovSmirnov test for the absolute price changes, and the Pearson’s chi-square test for the number of successive price changes in the same direction, and find statistically significant evidence of nonstationarity. We further study the recurrence intervals between the days in which nonstationarity occurs, and find that the distribution of recurrence intervals is well-approximated by an exponential distribution. Also, we find that the mean conditional recurrence interval 〈T|T₀〉 is independent of the previous recurrence interval T₀. These findings indicate that the recurrence intervals is characterized by a Poisson process. We interpret this as reflecting the Poisson property regarding the arrival of news.

  Introduction

  Financial time series data have been extensively investigated using a wide
  variety of methods in econophysics. These studies tend to assume, explicitly
  or implicitly, that a time series is stationary, since stationarity is a requirement
  for most of the mathematical theories underlying time series analysis.
  However, despite its nearly universal assumption, there is little previous studies
  that seek to test stationarity in a reliable manner. (Toth1a et al. (2010)).

  2010.11

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• Random Walk or A Run ―Market Microstructure Analysis of the Foreign Exchange Rate Movements based on Conditional Probability―
  Hideki TakayasuMisako TakayasuTakaaki OhnishiTakatoshi ItoTsutomu WatanabeYuko Hashimoto

  Abstract

  Using tick-by-tick data of the dollar-yen and euro-dollar exchange rates recorded in the actual transaction platform, a “run”—continuous increases or decreases in deal prices for the past several ticks—does have some predictable information on the direction of the next price movement. Deal price movements, that are consistent with order flows, tend to continue a run once it started i.e., conditional probability of deal prices tend to move in the same direction as the last several times in a row is higher than 0.5. However, quote prices do not show such tendency of a run. Hence, a random walk hypothesis is refuted in a simple test of a run using the tick by tick data. In addition, a longer continuous increase of the price tends to be followed by larger reversal. The findings suggest that those market participants who have access to real-time, tick-by-tick transaction data may have an advantage in predicting the exchange rate movement. Findings here also lend support to the momentum trading strategy.

  Introduction

  The foreign exchange market remains sleepless around the clock. Someone is trading somewhere all the time—24 hours a day, 7 days a week, 365 days a year. Analyzing the behavior of the exchange rate has become a popular sport of international finance researchers, while global financial institutions are spending millions of dollars to build real-time computer trading systems (program trading). High-frequency, reliable data are the key in finding robust results for good research for academics or profitable schemes for businesses.

  2008.08

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