25 years: Financial technology & algo trading
Nir introduces algorithmic trading by answering the following questions: What is algorithmic trading? How do you develop an algorithmic trading model? What is the future of algorithmic trading?
Nir introduces algorithmic trading by answering the following questions: What is algorithmic trading? How do you develop an algorithmic trading model? What is the future of algorithmic trading?
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9 mins 6 secs
Algorithmic trading is the idea that we create a program that makes trading decision suggestions for humans to execute. This is achieved by taking advantage of systematic biases and patterns within the market. The system created omits human intervention and thus, removes emotion.
Key learning objectives:
Define Algorithmic Trading
Discuss the different patterns and systematic biases within the market.
Explain the key requirements in developing an algorithmic trading model.
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Programming computers to undertake automated trading by pre-programming certain actions in response to changing market data.
An example of a systematic bias in the market is the tendency of people to sell winners and hold on to losers. The reason these biases are of great importance is they are the basis for patterns. From this we can use mathematical rules to take advantage.
Momentum Trading – This pattern follows the assumption that when there is a ‘wave’ and the market is performing well, people will bet that it’ll continue to rise for a little bit longer. An algorithm will realise this pattern and utilise mathematical rules to take advantage of it.
Ensuring Statistical Verification is achieved is vital as there is so much data available, you may become subject to ‘overfitting’ whereby you over-fit the data. Incorrect assumptions can be made when using things that worked in the past. However, that doesn’t ensure it’ll work in the future.
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