High-Frequency Trading: How Money Flow Affects Stock Returns
(2010) NEKM01 20102Department of Economics
- Abstract (Swedish)
 - Purpose:
The main purpose with this thesis is to study tick-data in order to see if intra-day volume can predict short-term market movements.
Methodology:
This thesis a quantitative study, using a deductive method and with an exploratory research design.
Theoretical framework:
In the theoretical framework, important theories for this thesis are presented, such as tape reading, high-frequency trading, and previous findings about money flow and measures of floor trading.
Empirical foundations:
The data sample consists of approximately 2.2 million trades during January 1, 2005 to April 22, 2010. The data was retrieved from Six Telekurs database.
Conclusions:
The high-frequency measures used in this thesis showed a... (More) - Purpose:
The main purpose with this thesis is to study tick-data in order to see if intra-day volume can predict short-term market movements.
Methodology:
This thesis a quantitative study, using a deductive method and with an exploratory research design.
Theoretical framework:
In the theoretical framework, important theories for this thesis are presented, such as tape reading, high-frequency trading, and previous findings about money flow and measures of floor trading.
Empirical foundations:
The data sample consists of approximately 2.2 million trades during January 1, 2005 to April 22, 2010. The data was retrieved from Six Telekurs database.
Conclusions:
The high-frequency measures used in this thesis showed a significant relationship between the measures and the stock return at a 1% significance level. The accumulated money flow was highly positively correlated with the stock return until late 2008, and since then it became negatively correlated. Steadily increasing activity by high-frequency trading algorithms, as well as the tick-size changes that occurred during 2009, might be an explanation. The trading model, which used the three measures studied, had almost twice as high risk-adjusted return as the stock itself. (Less) 
        Please use this url to cite or link to this publication:
        http://lup.lub.lu.se/student-papers/record/1730776
    
    
    - author
 - Olaison, Eric
 - supervisor
 - organization
 - course
 - NEKM01 20102
 - year
 - 2010
 - type
 - H1 - Master's Degree (One Year)
 - subject
 - keywords
 - money flow, intra-day volume., tape reading, High-frequency trading
 - language
 - English
 - id
 - 1730776
 - date added to LUP
 - 2010-12-02 10:13:09
 - date last changed
 - 2010-12-02 10:13:09
 
@misc{1730776,
  abstract     = {{Purpose:
The main purpose with this thesis is to study tick-data in order to see if intra-day volume can predict short-term market movements.
Methodology:	
This thesis a quantitative study, using a deductive method and with an exploratory research design.
Theoretical framework:
In the theoretical framework, important theories for this thesis are presented, such as tape reading, high-frequency trading, and previous findings about money flow and measures of floor trading.
Empirical foundations:
The data sample consists of approximately 2.2 million trades during January 1, 2005 to April 22, 2010. The data was retrieved from Six Telekurs database.
Conclusions:
The high-frequency measures used in this thesis showed a significant relationship between the measures and the stock return at a 1% significance level. The accumulated money flow was highly positively correlated with the stock return until late 2008, and since then it became negatively correlated. Steadily increasing activity by high-frequency trading algorithms, as well as the tick-size changes that occurred during 2009, might be an explanation. The trading model, which used the three measures studied, had almost twice as high risk-adjusted return as the stock itself.}},
  author       = {{Olaison, Eric}},
  language     = {{eng}},
  note         = {{Student Paper}},
  title        = {{High-Frequency Trading: How Money Flow Affects Stock Returns}},
  year         = {{2010}},
}