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Algorithmic Trading

Date post: 15-Jul-2015
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Page 1: Algorithmic Trading
Page 2: Algorithmic Trading

• A pre-defined step-by-step method to accomplish a task

• A computer model that takes an order and structures asequence of trades

• Computer programs that generate buy and sell ordersand make lightning-quick trades

• It is the automated execution of trading orders decidedby quantitative market models.

Page 3: Algorithmic Trading

Objectives:

• Minimize cost compared to a defined benchmark

• Maximizing fill rate

• Minimizing execution risk

• More reliable and faster execution platforms (computer sciences)

• More comprehensive and accurate prediction models (mathematics)

Page 4: Algorithmic Trading

What are the trends behind it?

• Regulatory Changes

• Electronification of Markets

• Improve Scale & Efficiency

• Desire for Anonymity

• Realization that Trading Is a Source of “Incremental Alpha”

• Desire to Reduce Explicit and Implicit Trading Costs

Page 5: Algorithmic Trading

Various Types of Algorithms in the Market

• Arrival price

• Time weighted average price (TWAP)

• Volume weighted average price (VWAP)

• Market-on-close (MOC)

Page 6: Algorithmic Trading

Areas of Concern while setting Algorithms

• Lack of Visibility

• Algorithms Acting on Other Algorithms

• Which Algorithm to Use?

• Missing Ingredient—The Trader’s Gut Feel

Page 7: Algorithmic Trading

What is the process?

1. Generate or improve a trading idea.

2. Quantify the idea and build a model for it.

3. Back test the strategy.

4. Collect the performance statistics.

5. If the statistics are not good enough, go back to #1.

6. If the strategy does not add significant value to the existing portfolio,go back to #1.

7. Implement the strategy on the execution platform.

8. Trade.

Page 8: Algorithmic Trading

Simple trading system design

a strategya strategy a strategy a strategy a strategy a strategy a strategy

BROKER

Exchanges

Page 9: Algorithmic Trading

What are the advantages?

• Move First

• Customise Quickly

• Rapidly Evolve

• Gain Access to Multiple Liquidity Pools

• Operate within Multiple Asset Classes

...

Page 10: Algorithmic Trading

Cont…

• Integrate Real-time News into Algorithmic Trading

• Design for Low Latency Decisions

• Research and Back test Strategies

• Learn from Experience

• Integrate Risk Management with Algorithmic Trading

Page 11: Algorithmic Trading

Issue with the Algorithmic Trade

• Filtration

• Consistency

• Internal Order Matching

• Rapid Strategy Implementation

• Safety

Page 12: Algorithmic Trading

Conclusion

• Algo trading is a very competitive field in which technology isa crucial factor.

• With the help of the algorithmic trading system the tradeactivity becomes faster.

• But after all it is totally depends on the technology

• There are lots of example of crashing in the market due toalgorithmic trade system.

• So one has to not depend fully on the algorithmic system.

Page 13: Algorithmic Trading

ThankYou…


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