Institutional Repository of Vilnius University
Algoritminė prekyba naudojant „prekyba poromis“ /
Abstract
dc:descriptionAlgorithmic Trading using Pairs Training Pairs trading is a market neutral trading strategy that matches long position with short position in a pair of highly correlated two stocks. This is when we buy a share A when its value is very low (long position) and sell a share B when its value is too high (short position). Algorithmic trading – Is such a trade when we programmed trading strategy using algorithms and other calculations. The computer decides when to buy and when to sell. However, there are few serious problems which we have to solve. The main problem is to find pairs which are suitable for make profit. I separated three basic steps that we have to carry out in search of the potential pairs. First of all, we have to find related stocks. Secondly, we have to plot the time series graph using historical data. Finally, we have to calculate the correlation coefficient. If the correlation coefficient is equal to one or approximately one, we have found right pairs. In this thesis, I presented a pairs trading strategy. I used the matlabpool function and optimized the pairs trading strategy .Strategy has generated higher profit. At the end I separated advantages and disadvantages of pairs trading. Advantages of pairs trading are: controlled risk, profit regardless of market direction, no directional risk, smaller drawdowns. Also, there are disadvantages of pairs trading such as twice the commissions and fees and the outcomes of execution risk.
Degree
thesis:*- Grantor dc:publisher
- Institutional Repository of Vilnius University
- Year dc:date
- 2016
Author and committee
dc:creator, dc:contributor.*- Author dc:creator
-
- Rinkevičiūtė, Žydrūnė,
- Contributors dc:contributor
-
- Raudys, Aistis
Rights
dc:rights- Statement dc:rights
-
- info:eu-repo/semantics/openAccess
- Language dc:language
- lit
Identifiers
dc:identifier.*- Repository record dc:identifier
- https://repository.vu.lt/VU:ELABAETD20088182&prefLang=en_US
- OAI identifier oai:identifier
- oai:vu.lt:elaba:20088182