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FinLlama: Financial Sentiment Classification for Algorithmic Trading Applications
arXiv.orgThere are multiple sources of financial news online which influence market movements and trader's decisions. This highlights the need for accurate sentiment analysis, in addition to having appropriate algorithmic trading techniques, to arrive at better ...
Thanos Konstantinidis +4 more
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Robotics and Algorithmic Trading: A New Era in Stock Market Trend Analysis
Global Disclosure of Economics and Business, 2021This paper uses machine learning to examine how robots and algorithmic trading have transformed stock market trend analysis. The main goals are to assess how these sophisticated systems improve prediction accuracy, trading efficiency, market liquidity ...
Jaya Chandra Srikanth Gummadi +4 more
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2013
Preface ix CHAPTER 1 Backtesting and Automated Execution 1 CHAPTER 2 The Basics of Mean Reversion 39 CHAPTER 3 Implementing Mean Reversion Strategies 63 CHAPTER 4 Mean Reversion of Stocks and ETFs 87 CHAPTER 5 Mean Reversion of Currencies and Futures 107 CHAPTER 6 Interday Momentum Strategies 133 CHAPTER 7 Intraday Momentum Strategies 155 CHAPTER 8 ...
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Preface ix CHAPTER 1 Backtesting and Automated Execution 1 CHAPTER 2 The Basics of Mean Reversion 39 CHAPTER 3 Implementing Mean Reversion Strategies 63 CHAPTER 4 Mean Reversion of Stocks and ETFs 87 CHAPTER 5 Mean Reversion of Currencies and Futures 107 CHAPTER 6 Interday Momentum Strategies 133 CHAPTER 7 Intraday Momentum Strategies 155 CHAPTER 8 ...
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Active Trading in ETFs: The Role of High-Frequency Algorithmic Trading
, 2021In the study reported here, we explored high-frequency algorithmic trading and its effect on exchange-traded funds (ETFs). Using the cancel rate, the trade-to-order ratio, percentage odd-lot volume, and trade size as proxies for algorithmic trading, we ...
Archana Jain +2 more
semanticscholar +1 more source
2015 IEEE 13th International Symposium on Intelligent Systems and Informatics (SISY), 2015
Although many of the world's markets have rebounded since the crash of 2008, it is believed a major correction is overdue. Some even claim that the markets are rigged in favor of those who employ high speed fiber network connections with the exchanges to front run trades.
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Although many of the world's markets have rebounded since the crash of 2008, it is believed a major correction is overdue. Some even claim that the markets are rigged in favor of those who employ high speed fiber network connections with the exchanges to front run trades.
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TradeZilla Using Algorithmic Trading
2021 IEEE India Council International Subsections Conference (INDISCON), 2021As everything in the future is getting automated and the stock market which is a very important part of the economic engine, which keeps a big part of globalization moving, needs its own revolution in automation/AI. Pundits and experts alike of this field have likened it to algorithmic trading which is considerably speeding up the trading process by ...
Dheeraj Othalasseril, Sana Shaikh
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The virtue of simplicity: On machine learning models in algorithmic trading
Big Data & Society, 2020Machine learning models are becoming increasingly prevalent in algorithmic trading and investment management. The spread of machine learning in finance challenges existing practices of modelling and model use and creates a demand for practical solutions ...
Kristian Bondo Hansen
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Algorithmic Trading and Fragmentation
The Journal of Trading, 2017Prior studies on algorithmic trading (AT) have mostly focused on a single exchange. The authors use a public dataset provided by the Securities and Exchange Commission (SEC) covering all major U.S. exchanges to study the impact of AT and its fragmentation on market liquidity.
Archana Jain +2 more
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Optimal Trading Stops and Algorithmic Trading
SSRN Electronic Journal, 2014Trading stops are often used by traders to risk manage their positions. In this note, we show how to derive optimal trading stops for generic algorithmic trading strategies when the P&L of the position is modelled by a Markov modulated diffusion. Optimal stop levels are derived by maximising the expected discounted utility of the P&L.
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Algorithmic trading and high frequency trading /
2017Thesis (PhD(Finance and related studies A))--University of South Australia, 2017. Includes bibliographical references (pages 121-135) This thesis provides one standalone survey essay and three empirical essays on algorithmic trading (AT) and its effect on market qualities.
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