Competitions

CAT Prep

Upskill

Placements

MBA Co'26

RTI Response

Rankings

Score Vs. %ile

Salaries

Campus Tour

Algo-Trading - A Leap Into The Future Of Trading - IFMR

Jun 23, 2017 | 3 minutes |

Join InsideIIM GOLD

Webinars & Workshops

Compare B-Schools

Free CAT Course

Take Free Mock Tests

Upskill With AltUni

CAT Study Planner

1 Day to CAT 2024 (All the best)

Participants: 190

Final 2 Days to CAT 2024 Test-44

Participants: 423

Final 3 Days to CAT 2024 Test-43

Participants: 339

Final 4 Days to CAT 2024 Test-42

Participants: 366

Final 5 Days to CAT 2024 Test-41

Participants: 382

Final 6 Days to CAT 2024 Test-40

Participants: 362

Final 7 Days to CAT 2024 Test-39

Participants: 350

Final 8 Days to CAT 2024 Test-38

Participants: 318

Final 9 Days to CAT 2024 Test-37

Participants: 330

Final 10 Days to CAT 2024 Test-36

Participants: 293

Final 11 Days to CAT 2024 Test-35

Participants: 528

Final 12 Days to CAT 2024 Test-34

Participants: 338

Final 13 Days to CAT 2024 Test-33

Participants: 301

Final 14 Days to CAT 2024 Test-32

Participants: 280

Final 15 Days to CAT 2024 Test-31

Participants: 376

Final 16 Days to CAT 2024 Test-30

Participants: 303

Final 17 Days to CAT 2024 Test-29

Participants: 314

Final 18 Days to CAT 2024 Test-28

Participants: 346

Final 19 Days to CAT 2024 Test-26

Participants: 339

Final 20 Days to CAT 2024 Test-26

Participants: 308

Final 21 Days to CAT 2024 Test-25

Participants: 254

Final 22 Days to CAT 2024 Test-24

Participants: 270

Final 23 Days to CAT 2024 Test-23

Participants: 180

Final 24 Days to CAT 2024 Test-22

Participants: 227

Final 25 Days to CAT 2024 Test-21

Participants: 228

Final 26 Days to CAT 2024 Test-20

Participants: 281

Final 27 Days to CAT 2024 Test-19

Participants: 235

Final 28 Days to CAT 2024 Test-18

Participants: 236

Final 29 Days to CAT 2024 Test-17

Participants: 248

Final 30 Days to CAT 2024 Test-16

Participants: 292

Algo Trading - What is that? It has different names (Automated trading, Black-box trading, or simply Algorithmic-trading). Algorithmic Trading analyses different market conditions from which it can make profits. Then it applies one of its many algorithmic trading strategies created by user or broker, particular to that market situation, and automatically trades and manages positions even if the user is sleeping (No need to constantly watch the Market). This was introduced in India in 2008, still lagging behind the US and Europe in trend, but, it is quickly catching up. In India, one-third of trading happens through this, while in the USA this figure is close to 75-80percentage. This is the trading technique that will increase the performance and at the same time will reduce the portfolio volatility and allows the user to make profits during a rising and falling stock market. It makes work easier for the user as it automatically searches for the hot stocks, sectors, commodities, index according to the market situation. Algo-trading does all the searching, timing and trading for the user automatically. Since there is no human intervention involved, Algo-trading is much faster and efficient than manual trading. Any profitable trading strategy can be executed through an Automated algorithm. In general, many algorithms are being used by Algo-Traders such as Maximum traded value, Time-weighted average, Volume-Weighted Average Price (VWAP), Trades per second, Market-On-Close (MOC), Total traded quantity, Arrival price. Beyond that user can create many other algorithms as per his strategy using different programming languages like Python, Java, C# etc. While creating algorithms, the user needs to understand different strategies to deal wit the financial market because algorithms are meaningless if strategies don't perform. These trading strategies are highly dependent on complex mathematical formulas and high-speed programs. It is extensively used by Mutual funds companies, Investment banks, Pension funds management to hedge funds because these institutions need to execute high-frequency numbers which are not possible every time. It helps them to break the whole amount into small parts and continue to execute in particular time intervals or according to any dedicated strategies. For example, instead of placing 1,00,000 shares at a time, an Algo-trading technique may push 1,000 shares out every 15 seconds and incrementally put small amounts into the market over the period of a time or over entire day. In finance, as we know opportunity goes hand in hand with risk. The famous "Flash Crash " had occurred in US in 2010 due to algorithmic trading. To prevent this, some of the risk management algorithms must be approved by the exchanges like total traded quantity, maximum traded value and trades per seconds. This technique will provide future for the financial people to make a great career with the help of technology. It is going to be a trend for Individual traders, Brokers and Financial institutions to use this High-end strategic mechanism.     ------------------------- About the Author: Ayaskanta An Electronics Engineer with a passion in IT and a knack to study and understand the Indian Financial Markets. Second Year PGDM student at Institute for Financial Management and Research (IFMR)