High Frequency Trading (HFTs): Explained

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Economics Explained

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Published on November 28, 2019 1:38:01 PM ● Video Link: https://www.youtube.com/watch?v=oUVchh37AO8

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Frequency (2001)

Duration: 14:42

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The New York Stock Exchange is the world's largest and most liquid securities market.

It's where many of world's largest companies list their shares to be traded amongst millions of investors worldwide; ranging from small individual investors to major financial institutions and governments.

But the NYSE isn't the only exchange. In fact, there are hundreds of exchanges around the world that also work to raise capital for corporations.

And while you're probably familiar with the classic imagery of loud bombastic traders in bright uniforms when you think of stock exchanges, the reality is quite different.

The age of the automated trading machines is upon us and most trades executed today aren't coming from humans but rather algorithmic trading machines.

These computer algorithms (or "algos") come in all sorts of shapes and sizes. But the most controversial of all is known as "high-frequency trading" or "HFT".

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📚 Want to learn more about HFTs? We recommend reading "High-Frequency Trading: A Practical Guide to Algorithmic Strategies and Trading Systems", by Irene Aldridge
👉 https://amzn.to/37kIpv6 (as an Amazon Associate, we earn from qualifying purchases)

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#NYSE #Trading #Economics

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Sources & Citations -

Brogaard, J., Hendershott, T. and Riordan, R., 2014. High-frequency trading and price discovery. The Review of Financial Studies, 27

Kirilenko, A., Kyle, A.S., Samadi, M. and Tuzun, T., 2017. The flash crash: High‐frequency trading in an electronic market. The Journal of Finance

Brogaard, J., 2010. High frequency trading and its impact on market quality. Northwestern University Kellogg School of Management Working Paper

Carrion, A., 2013. Very fast money: High-frequency trading on the NASDAQ. Journal of Financial Markets,

Golub, A., Keane, J. and Poon, S.H., 2012. High frequency trading and mini flash crashes

Paddrik, M., Hayes, R., Todd, A., Yang, S., Beling, P. and Scherer, W., 2012, March. An agent based model of the E-Mini S&P 500 applied to Flash Crash analysis. In 2012 IEEE
Conference on Computational Intelligence for Financial Engineering & Economics

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