High Frequency Trading Overview:
In this post, I would like to talk about a little bit about High Frequency Trading, some of the key players around it and so on.
So what is HFT and how is it different than Traditional Trading?
High Frequency Trading refers to fast allocation/re-allocation or turnover of trading capital. In Traditional trading, a trader will look at some of the components of the trading strategy such as Charts with indicators (moving averages, RSI etc...) before committing capital to the trade. On the other hand, in HFT, computers make the decisions to fire the trade based on some econometric model that is fully tested out (back-tested) by the trader. In HFT, trade execution speed is the key as the trades might be executed in a fraction of seconds/milliseconds/nanoseconds and traditional traders can't operate at such a low latency.
* In HFT, Low latency refers to the speed of executing an order. A low latency can be a trading strategy in its own right when the high speed of execution can be used an arbitrage strategy where there are price difference found on the same security on multiple exchanges for the same security.
There are 4 key characteristics of HFT:
1. Tick by Tick Data Processing
2. High Capital Turnover (HCT)
3. Intraday Entry and Exit
4. Algorithmic Trading
Some of the key players in HFT are: DE Shaw, Renaissance Technologies, and Towa Research Capital
3 Major components of HFT system are:
1. Highly Quantitative, Econometric models that forecast short term price moves based on contemporary market conditions
2. Advanced Computer systems built to quickly execute the complex econometric model
3. Capital applied and monitored with in Risk Management and Cost Management framework
In practice, an HFT firm will use 2 years of tick level data to backtest a strategy before committing live capital on it. Since setting up an HFT strategy requires pretty sophisticated level of understanding in Finance and Economics, most of the staffing at such firms are Ph.D in Quantitative Research (Finance/Economics/Physics)
Finally, an HFT operation is more likely to survive & proper if it had leverage and high Sharpe Ratios. Leverage helps to cover the operational costs and Sharpe Ratio helps in reducingthe risk of catastrophic losses and fund ruin.
Please feel free to comment should you have further questions related HFT.
-Nitin
In this post, I would like to talk about a little bit about High Frequency Trading, some of the key players around it and so on.
So what is HFT and how is it different than Traditional Trading?
High Frequency Trading refers to fast allocation/re-allocation or turnover of trading capital. In Traditional trading, a trader will look at some of the components of the trading strategy such as Charts with indicators (moving averages, RSI etc...) before committing capital to the trade. On the other hand, in HFT, computers make the decisions to fire the trade based on some econometric model that is fully tested out (back-tested) by the trader. In HFT, trade execution speed is the key as the trades might be executed in a fraction of seconds/milliseconds/nanoseconds and traditional traders can't operate at such a low latency.
* In HFT, Low latency refers to the speed of executing an order. A low latency can be a trading strategy in its own right when the high speed of execution can be used an arbitrage strategy where there are price difference found on the same security on multiple exchanges for the same security.
There are 4 key characteristics of HFT:
1. Tick by Tick Data Processing
2. High Capital Turnover (HCT)
3. Intraday Entry and Exit
4. Algorithmic Trading
Some of the key players in HFT are: DE Shaw, Renaissance Technologies, and Towa Research Capital
3 Major components of HFT system are:
1. Highly Quantitative, Econometric models that forecast short term price moves based on contemporary market conditions
2. Advanced Computer systems built to quickly execute the complex econometric model
3. Capital applied and monitored with in Risk Management and Cost Management framework
In practice, an HFT firm will use 2 years of tick level data to backtest a strategy before committing live capital on it. Since setting up an HFT strategy requires pretty sophisticated level of understanding in Finance and Economics, most of the staffing at such firms are Ph.D in Quantitative Research (Finance/Economics/Physics)
Finally, an HFT operation is more likely to survive & proper if it had leverage and high Sharpe Ratios. Leverage helps to cover the operational costs and Sharpe Ratio helps in reducingthe risk of catastrophic losses and fund ruin.
Please feel free to comment should you have further questions related HFT.
-Nitin
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