Profiting from FX Fixes

A Quantitative Approach to Trading the Benchmark Price

Introduction

Though Forex market displays a high level of noise, there are still some patterns. These patterns have been analyzed in many research papers. Some of them are exploitable, others are mostly of academic interest. I described one such pattern in a previous article. The pattern is that, the authors of the paper called “Intraday Patterns in FX returns and Order Flow” claim, many currencies tend to depreciate during local trading hours and appreciate outside those hours, or during foreign trading hours. Let’s take EURUSD, the most traded FX pair. If we apply the hypothesis to EURUSD, it implies that EURUSD tends to depreciate during European trading hours, and then rise during US trading hours.

In this article we’ll analyze another variation of this pattern which is even more specific than the previous one. Authors of the paper “Foreign Exchange Fixings and Returns Around the Clock” looked at intraday FX data of major currencies and found a pattern in currency returns. The hypothesis is that USD tends to appreciate before FX fixings and to depreciate following them. But what is FX fixing? Why USD rises prior to fixes and falls following them? And how we can test this claim that exchange rate returns display predictable intraday seasonality?

A FX fix is a predefined time of day when bids and offers for currencies are aggregated and a reference price is published. The most popular fixes are the London, ECB, and Tokyo fixes. Below you can see the fixes in ET (Eastern Time) time.

The first major of fix of the day happens in Tokyo at 20:55 ET or 19:55 ET if Daylight Saving Time is in effect in the US. The next one comes from the continental Europe — ECB fix at 8:15 ET. And the last important FX fix occurs in London at 11:00 ET.

Why does the US dollar tend to appreciate in the run-up to fixes? Although there can be many reasons contributing to this intraday seasonality, the most important one is a structural demand for USD ahead of the fix. USD is accumulated before the fix and is sold to clients at a higher price at the fix.

Testing the hypothesis

We’ll test the claim that US dollar tends to appreciate before fixings and to fall following them. We’ll build a simply strategy of buying EURUSD 15 minutes before the fixing event, closing our position at fixing and shorting EURUSD. The short position will be closed 15 minutes after the fixing event.

I assume you have got EURUSD data from Metatrader 5 or any trading platform. The following code imports libraries pandas as datetime, and makes a tidy dataframe out of csv file I exported from MT 5.

import pandas as pd
from datetime import datetime, timedelta

file_path = 'C:/Users/user/Documents/Python Scripts/Python Scripts/fx data/'

def create_df(file_name):
    full_path = file_path + file_name
    df = pd.read_csv(full_path, sep='\t')
    df.columns = df.columns.str.replace('<', '').str.replace('>', '')
    return df
df = create_df("EURUSD_M15_x.csv")

Since the time in our dataframe is GMT+2, we have to convert it ET.

df['datetime'] = pd.to_datetime(df['DATE'] + ' ' + df['TIME'])

# Convert GMT+2 to ET (GMT-4 during DST, GMT-5 during standard time)
def convert_to_et(dt):
    # DST in US starts second Sunday in March and ends first Sunday in November
    # This is a simplified version - for precise calculations we'd need to check exact DST dates
    if dt.month >= 3 and dt.month <= 11:
        return dt - timedelta(hours=6)  # GMT+2 to GMT-4 (6 hours difference)
    else:
        return dt - timedelta(hours=7)  # GMT+2 to GMT-5 (7 hours difference)

df['datetime_et'] = df['datetime'].apply(convert_to_et)

Now we build our strategy — buy USD 15 minutes up to Tokyo and ECB fixes, and close the positions at fixing times, Short USD at Tokyo fix and London fix, and close short positions 15 minutes later.