big data in stock exchange( hft, forex, flash crashes)

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Big Data in Stock Exchange DMYTRO MELNYCHUK

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Page 1: Big Data in Stock Exchange( HFT, Forex, Flash Crashes)

Big Data in Stock Exchange

DMYTRO MELNYCHUK

Page 2: Big Data in Stock Exchange( HFT, Forex, Flash Crashes)

New York Stock Exchange: To be listed on the NYSE, a company must have issued at least a million shares of stock worth $100 million and must have earned more than $10 million over the last three years

Page 3: Big Data in Stock Exchange( HFT, Forex, Flash Crashes)

Who is stockbroker?

A stockbroker is a regulated professional individual, usually associated with a brokerage firm or broker-dealer, who buys and sells stocks and other securities for both retail and institutional clients

Page 4: Big Data in Stock Exchange( HFT, Forex, Flash Crashes)

New York Stock ExchangeOLD NYSE(1920) NEW

NYSE(2016)

Page 5: Big Data in Stock Exchange( HFT, Forex, Flash Crashes)

High-frequency tradingis a type of algorithmic trading characterized by high speeds, high turnover rates, and high order-to-trade ratios that leverages high-frequency financial data and electronic trading tools

Page 6: Big Data in Stock Exchange( HFT, Forex, Flash Crashes)

High-frequency tradingis trading that leverages high-frequency financial data and electronic trading tools

• High-frequency trading firms represented 2% of 20,000 firms in market, but 73% money of all operation at 2016 press on HFT companies

People trad-ing

26%

HFT74%

Peace of many by method of trade in

2009

People trading HFT

According to a study in 2010 by Aite Group, about a quarter of major global futures volume came from professional high-frequency traders

People trading24%

HFT76%

Major global futures volume in 2010

People trading HFT

Page 7: Big Data in Stock Exchange( HFT, Forex, Flash Crashes)

HFT Brokers Dom Maklerski S.A. is an independent brokerage house, that specialize in trading CFD based on Forex, stock indices, commodities and equity market. HFT Brokers – created by Traders for Traders(New York, USA)Founded: 2006Type: Public CompanyIndustry: Capital MarketsCompany Size: 51-200 employeesHeadquarters: Warsaw, PolandSpecialties Forex, Trading, High Speed

Trading, High Frequency

Trading, Education

Website: http://www.hftbrokers.pl

High-frequency trading in Poland

Main office in the picture >>

Page 8: Big Data in Stock Exchange( HFT, Forex, Flash Crashes)

HFT Brokers Dom Maklerski S.A.

Headquarters : Str. Prosta 51, 00-838 Warsaw

Page 9: Big Data in Stock Exchange( HFT, Forex, Flash Crashes)

Nanex is one of the best firm that offers streaming data on all market transactions and distributes the data in real-time to clients (typically, traders and financial analysis firms) and allows them to do analysis and visualization in real-time

Page 10: Big Data in Stock Exchange( HFT, Forex, Flash Crashes)

How does the HFT during 7 secondsat Nanex platform

http://youtube.com/watch?v=a-9A0ar70pI

Page 11: Big Data in Stock Exchange( HFT, Forex, Flash Crashes)

https://www.youtube.com/watch?v=6f486Qg4Fis

High-frequency Trading Model

Page 12: Big Data in Stock Exchange( HFT, Forex, Flash Crashes)

Procent of orders generated by algorithms

*Ultra-low latency direct market access (DMA)

Page 13: Big Data in Stock Exchange( HFT, Forex, Flash Crashes)

High Touch trading so hard today

Page 14: Big Data in Stock Exchange( HFT, Forex, Flash Crashes)

HFT is the reason of flash crashes A flash crash is a very rapid, deep, and volatile fall in security prices occurring within an extremely short time period.

A flash crash frequently stems from trades executed by black-box trading, combined with high-frequency trading, whose speed and interconnectedness can result in the loss and recovery of billions of dollars in a matter of minutes and seconds.

Two notable flash crashes have occurred in history: April 23, 2013, Flash CrashSingapore Exchange which lost $6.9 billion in capitalization and saw some stocks lose up to 87 percent of their value

May 6, 2010, Flash Crash$4.1 billion trade on the NYSE resulted in a loss to the Dow Jones Industrial Average of over 1000 points

Page 15: Big Data in Stock Exchange( HFT, Forex, Flash Crashes)

Market need to control HFT via algorithmic tests

When the market operates normally (left subplot), almost all of the HFT agents are in control of their inventory (greenish color). In crash period (right), most of the HFT agents gain large inventories (red) and the network is highly interconnected: over 85 percent of the transactions are HFT-HFT.

Page 16: Big Data in Stock Exchange( HFT, Forex, Flash Crashes)

Despite the problems, but high-frequency trading is our future