Something to Read - Quantitative Technical Analysis: An integrated approach to trading system development and trading management
17 February 2015, 06:11
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Quantitative Technical Analysis: An integrated approach to trading system development and trading management
by Dr Howard B Bandy
The book discusses trading system development and trading management.
The perspective of the book is that the goal of the developer of a trading system and of the trader who uses it is to have confidence that the signals issued by the system precede trades that provide rewards adequate to compensate for the risk.
The focus of the book is risk.
The trading system development portion discusses topics including measuring success, issue selection, the two components of a system (the model and the data), identification of patterns that precede profitable trades, in-sample data analysis, out-of-sample system testing, maintaining synchronization between the model and the data, and methods of validation.
The trading management portion discusses a new and unique approach that continually monitors system performance, determines risk of drawdown, assesses the personal risk tolerance of the trader, computes the maximum safe position size, and estimates profit potential.
It includes techniques for determining the health of the system being traded, readjusting the system as necessary, and deciding when to take it offline before serious loss of trading capital.
Use of machine learning techniques, applied to trading systems, is introduced. Examples of classification and estimation are presented, using the Python language and associated application libraries.
by Dr Howard B Bandy
The book discusses trading system development and trading management.
The perspective of the book is that the goal of the developer of a trading system and of the trader who uses it is to have confidence that the signals issued by the system precede trades that provide rewards adequate to compensate for the risk.
The focus of the book is risk.
- Assessing your personal risk tolerance.
- Estimating the risk in a trading system.
- Trade selection to minimize risk.
- Dynamically managing position size to maximize account growth, constrained to hold drawdown within your risk tolerance.
The trading system development portion discusses topics including measuring success, issue selection, the two components of a system (the model and the data), identification of patterns that precede profitable trades, in-sample data analysis, out-of-sample system testing, maintaining synchronization between the model and the data, and methods of validation.
The trading management portion discusses a new and unique approach that continually monitors system performance, determines risk of drawdown, assesses the personal risk tolerance of the trader, computes the maximum safe position size, and estimates profit potential.
It includes techniques for determining the health of the system being traded, readjusting the system as necessary, and deciding when to take it offline before serious loss of trading capital.
Use of machine learning techniques, applied to trading systems, is introduced. Examples of classification and estimation are presented, using the Python language and associated application libraries.
