The activity of algorithmic trading is increasing steadily across capital markets due to technological developments. This thesis analyses the common algorithmic intraday trading strategies of momentum, mean reversion, and statistical arbitrage. Conclusions were drawn from a literature review of prior and current research. Algorithmic arbitrage was found to be the most profitable of the three evaluated strategies, because it typically takes place in high frequency trading. Furthermore, this thesis analyses the impact of algorithmic trading on market liquidity and volatility. While the literature mainly agrees that algorithmic trading has a positive effect on liquidity, its impact on volatility is subject to discussion. Algorithmic and high-frequency trading carry risks that will likely lead to new future regulations.:1 INTRODUCTION
1.1 Background
1.2 Problem description and goal of the research
1.3 Structure of the thesis and research questions
2 THEORETICAL FUNDAMENTALS
2.1 Intraday trading
2.1.1 Definition
2.1.2 Characteristics of intraday trading markets
2.1.3 Financial instruments of intraday trading
2.1.4 Goals and profit chances of individual intraday traders
2.2 Algorithmic trading
2.2.1 Algorithm definitions
2.2.2 Algorithmic trading definitions
2.2.3 High-frequency trading
2.2.4 Characteristics of algorithmic trading and high-frequency trading
2.2.5 Trading algorithm characteristics
3 METHODOLOGY
3.1 Data collection
3.2 Data analysis
4 ALGORITHM-BASED INTRADAY TRADING STRATEGIES AND THEIR PROFIT POTENTIAL
4.1 Momentum strategy
4.1.1 Definition and basic principle of the strategy
4.1.2 Underlying theories of the momentum strategy
4.1.3 Selected studies of an algorithmic intraday momentum strategy
4.2 Mean reversion strategy
4.2.1 Definition and basic principle of the strategy
4.2.2 Underlying theories of the mean reversion strategy
4.2.3 Relation of mean reversion and momentum
4.2.4 Selected studies of an algorithmic intraday mean reversion strategy
4.3 Arbitrage strategy
4.3.1 Definition and basic principle of the strategy
4.3.2 Types of Arbitrage
4.3.3 Underlying theories of the arbitrage strategy
4.3.4 Selected studies of an algorithmic intraday statistical arbitrage strategy
4.4 Further trading algorithms and strategy components
4.4.1 Speed Advantage algorithms
4.4.2 Accuracy Advantage Algorithms
5 IMPACT OF ALGORITHMIC TRADING ON MARKET LIQUIDITY AND VOLATILITY
5.1 Market liquidity
5.1.1 Definition
5.1.2 Bid-Ask Spread
5.1.3 Dimensions of liquidity
5.1.4 The impact of algorithmic trading on market liquidity
5.2 Market volatility
5.2.1 Definition and characteristics of volatility
5.2.2 The impact of algorithmic trading on market volatility
6 CONCLUSION AND FUTURE DEVELOPMENTS OF ALGORITHMIC TRADING
PUBLICATION BIBLIOGRAPHY
DECLARATION OF HONOR
| Identifer | oai:union.ndltd.org:DRESDEN/oai:qucosa:de:qucosa:74005 |
| Date | 23 February 2021 |
| Creators | Müller, Luisa |
| Contributors | Hochschule für Technik, Wirtschaft und Kultur Leipzig |
| Source Sets | Hochschulschriftenserver (HSSS) der SLUB Dresden |
| Language | English |
| Detected Language | English |
| Type | info:eu-repo/semantics/acceptedVersion, doc-type:bachelorThesis, info:eu-repo/semantics/bachelorThesis, doc-type:Text |
| Rights | info:eu-repo/semantics/openAccess |
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