THESIS
2018
xii, 82 pages : illustrations ; 30 cm
Abstract
Strategy backtesting which is a process to take some user-defined trading rules and market information
as input, simulate behaviors of market participants under these trading rules and finally
report the strategy performance. Strategy backtesting systems are the most important applications
of algorithmic trading since it provide individual or professional traders flexibility to design and
test their customized ideas. Technical analysis is the most popular way for financial instruments
traders to predict future price movement by researching historical data records. However, technical
analyses highly rely on a various of technical indicators, patterns and personal charting heuristics,
which makes it very difficult to be transformed into algorithmic trading strategies. Most technica...[
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Strategy backtesting which is a process to take some user-defined trading rules and market information
as input, simulate behaviors of market participants under these trading rules and finally
report the strategy performance. Strategy backtesting systems are the most important applications
of algorithmic trading since it provide individual or professional traders flexibility to design and
test their customized ideas. Technical analysis is the most popular way for financial instruments
traders to predict future price movement by researching historical data records. However, technical
analyses highly rely on a various of technical indicators, patterns and personal charting heuristics,
which makes it very difficult to be transformed into algorithmic trading strategies. Most technical
traders especially for individual traders, on the other hand, are lack of knowledge about computer
programming, and find it hard for them to script their strategies by coding. Therefore, a strategy
backtesting system allowing users to describe complex and advanced technical strategies via pure
graphical user interface (GUI) is in very highly demand.
In this thesis, we design and implement a multi-time-frame technical pattern and strategy backtesting
system, that is MTPS, to address the problem of describing complex technical patterns on
GUI and applying these patterns in algorithmic trading strategies. By observing the cases that a
large amount of profitable technical patterns are composed of sequences of characteristic candle
bars, we introduce a hierarchical MTPS strategy description system that promote users to describe
their technical patterns by describing sequences of technical events. This strategy description system
endow users who are not knowledgeable about computer programming a much higher flexibility
to include complicated and advanced patterns in their algorithmic strategies. In addition, we
also provide users interfaces in MTPS to include technical indicators from multiple time-frames in
one strategy which is a unique feature that most of the state-of-the-art strategy backtesting systems
can not achieve. Besides, we present present the complete architecture of MTPS including the implementation
details of all the software components and how they are organized in an event-driven
design pattern. Moreover, we propose an efficient pattern matching algorithm for MTPS to minimize
the delay between market data arrival and order placement. Last but not least, experiments are
conducted showing that MTPS do capable to describe 3 complex and advanced technical pattens
and backtesting strategies based on these 3 patterns to generate profit surpassing the ”buy-and-hold”
strategies.
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