Strategies for High Frequency FX Trading  The choice of bucket size
(2017) FMS820 20171Mathematical Statistics
 Abstract
 This thesis aims at developing and evaluating a model for high frequency foreign exchange data, that beats the TWAP benchmark the majority of the time. This is done by dividing the total order time into smaller time buckets and trading a smaller quantity of the total order volume in each bucket. The second purpose of the thesis is to determine if there is an optimal bucket size in which to trade in order to achieve the best results. Four diﬀerent models were developed and it was found that the model that traded both passively and aggressively without a set order time performed the best. It was discovered that this model always beats the TWAP benchmark on an average day on the market. The best performing model also took the prevailing... (More)
 This thesis aims at developing and evaluating a model for high frequency foreign exchange data, that beats the TWAP benchmark the majority of the time. This is done by dividing the total order time into smaller time buckets and trading a smaller quantity of the total order volume in each bucket. The second purpose of the thesis is to determine if there is an optimal bucket size in which to trade in order to achieve the best results. Four diﬀerent models were developed and it was found that the model that traded both passively and aggressively without a set order time performed the best. It was discovered that this model always beats the TWAP benchmark on an average day on the market. The best performing model also took the prevailing market conditions, modelled as market risk and spread risk, into account. The market risk was modelled using a prediction of the volatility during the time interval of the order and the spread risk was modelled by using a prediction of the spread. The purpose of the risk factors was to get an indication of how to choose the level at which to trade passively and aggressively in the buckets, which will be explained further in this thesis.
It was concluded that an optimal bucket size does not exist. Instead, it was decided that the client’s preferences regarding potential risks and proﬁts should be the deciding factor in determining optimal bucket size for an order. This is achieved by allowing the client to choose a certain probability of succeeding with a passive trade in a bucket and calculating the bucket size based on this probability. Prior to making the choice, the client is presented with the potential proﬁt, market risk and spread risk for each probability. A low probability results in shorter bucket sizes and thus a shorter order time. This in turn results in a low market risk but a high spread risk. A high probability on the other hand, results in longer bucket sizes and a longer order time which implies a low spread risk but a high market risk. This means that a risk averse client chooses the low probability with less risk of market changes at the expense of loosing the spread, and vice versa for a less risk avert client.
The three currency pairs that were considered in this thesis are EUR/SEK, EUR/NOK and EUR/USD. High frequency was in this thesis deﬁned as secondbysecond up to minutebyminute observations. (Less)  Popular Abstract
 The choice of time interval for high frequency FX trading
When a bank is trading a large volume of a currency pair, it is necessary to divide the order into smaller quantities and trade those quantities over time in order to avoid market impact. Better prices can be received when trading small quantities frequently at shorter time intervals and there is a possibility of making small proﬁts for the trades. So how does one choose the optimal time interval for high frequency FX trading?
A bank executes an order on the request of a client. The optimal length of the time interval, referred to as the optimal bucket size, depends on how the client prioritizes risk against potential proﬁt. Usually a longer bucket size infers a higher potential... (More)  The choice of time interval for high frequency FX trading
When a bank is trading a large volume of a currency pair, it is necessary to divide the order into smaller quantities and trade those quantities over time in order to avoid market impact. Better prices can be received when trading small quantities frequently at shorter time intervals and there is a possibility of making small proﬁts for the trades. So how does one choose the optimal time interval for high frequency FX trading?
A bank executes an order on the request of a client. The optimal length of the time interval, referred to as the optimal bucket size, depends on how the client prioritizes risk against potential proﬁt. Usually a longer bucket size infers a higher potential proﬁt at the expense of additional of market risk. In order to receive a higher proﬁt it is necessary to attempt to trade passively, which means placing a certain price to sell or buy a currency pair and waiting for someone to accept that price. The price received when trading passively is typically higher than that achieved when trading aggressively, as using an aggressive trading strategy means accepting a price that someone else has placed.
Having studied a range of bucket sizes it is evident that not one bucket size consistently provides the greatest return, in other words there is no optimal bucket size. Instead, the likelihood of success through a passive trading strategy depends on the market volume. During periods of higher volume it is more probable to succeed with passive trades, therefore receiving a higher price with a shorter bucket size, compared to periods of lower market activity. Due to market activity ﬂuctuations, volumes traded throughout the day vary signiﬁcantly, with the lowest activity during lunch hours and night time. Consequently the probability changes during the day and hence the bucket sizes diﬀer from hour to hour.
As mentioned, the bucket size depends on the client’s preferences. This means that a client with a high risk tolerance will choose a high probability of succeeding with passive trades, which will result in longer buckets. In comparison, a client that has a lower risk tolerance is likely to prefer a shorter bucket size, thus lowering their probability of succeeding with passive trades. The client with the higher risk proﬁle is more likely to receive a higher proﬁt than the client with the lower risk proﬁle, however the longer the bucket size selected by the higher risk client will expose them to a higher risk of market changes.
In addition to client preference and market activity, the ideal bucket size also depends on which currency pair is being traded. EUR/USD is the most traded currency pair in the world and the market activity for EUR/USD is a lot higher compared to the Scandinavian currency pairs EUR/SEK and EUR/NOK. This means the following: ﬁrstly, it is possible to trade EUR/USD at a higher frequency without having market impact and secondly, the probability of succeeding with passive trades is higher. This in turn means that EUR/USD requires a shorter bucket size and total order time in order to complete an order than the other currencies. For instance, an order for EUR/USD can be complete in 8 minutes with a bucket size of 2 seconds while the corresponding order for EUR/NOK takes 6 hours with varying bucket sizes between 65 and 129 seconds. (Less)
Please use this url to cite or link to this publication:
http://lup.lub.lu.se/studentpapers/record/8915501
 author
 Lunsjö, Malin and Riddarström, Malin
 supervisor

 Magnus Wiktorsson ^{LU}
 organization
 course
 FMS820 20171
 year
 2017
 type
 H2  Master's Degree (Two Years)
 subject
 keywords
 Highfrequency, FXtrading, Shiftedgeometricdistribution, MonteCarlo, Time Series Analysis, EWMA, Bucket size, TWAP.
 language
 English
 id
 8915501
 date added to LUP
 20170614 13:58:47
 date last changed
 20170614 13:58:47
@misc{8915501, abstract = {This thesis aims at developing and evaluating a model for high frequency foreign exchange data, that beats the TWAP benchmark the majority of the time. This is done by dividing the total order time into smaller time buckets and trading a smaller quantity of the total order volume in each bucket. The second purpose of the thesis is to determine if there is an optimal bucket size in which to trade in order to achieve the best results. Four diﬀerent models were developed and it was found that the model that traded both passively and aggressively without a set order time performed the best. It was discovered that this model always beats the TWAP benchmark on an average day on the market. The best performing model also took the prevailing market conditions, modelled as market risk and spread risk, into account. The market risk was modelled using a prediction of the volatility during the time interval of the order and the spread risk was modelled by using a prediction of the spread. The purpose of the risk factors was to get an indication of how to choose the level at which to trade passively and aggressively in the buckets, which will be explained further in this thesis. It was concluded that an optimal bucket size does not exist. Instead, it was decided that the client’s preferences regarding potential risks and proﬁts should be the deciding factor in determining optimal bucket size for an order. This is achieved by allowing the client to choose a certain probability of succeeding with a passive trade in a bucket and calculating the bucket size based on this probability. Prior to making the choice, the client is presented with the potential proﬁt, market risk and spread risk for each probability. A low probability results in shorter bucket sizes and thus a shorter order time. This in turn results in a low market risk but a high spread risk. A high probability on the other hand, results in longer bucket sizes and a longer order time which implies a low spread risk but a high market risk. This means that a risk averse client chooses the low probability with less risk of market changes at the expense of loosing the spread, and vice versa for a less risk avert client. The three currency pairs that were considered in this thesis are EUR/SEK, EUR/NOK and EUR/USD. High frequency was in this thesis deﬁned as secondbysecond up to minutebyminute observations.}, author = {Lunsjö, Malin and Riddarström, Malin}, keyword = {Highfrequency,FXtrading,Shiftedgeometricdistribution,MonteCarlo,Time Series Analysis,EWMA,Bucket size,TWAP.}, language = {eng}, note = {Student Paper}, title = {Strategies for High Frequency FX Trading  The choice of bucket size}, year = {2017}, }