A Study On The King Keltner Model Based Program Trading

Program trading has found extensive use in China’s futures market in recent years, which allows investors to use pre-designed trading model to overcome psychological disruption in real practices, and makes the tracking of investment performance and the development of investment scheme more intuitive. In developing program trading, compared with development of new model, optimizing existing classic models based on the price movement of futures categories in China is more convenient. The King Keltner model studied in this paper represents a successful trading model abroad, which employs the idea of channel breakthrough to track the dynamics of significant volatility. Despite usability in most trading categories in various markets such as foreign exchange, stock and futures, this model has so far been rarely discussed nationwide, with no referrable test results as to whether the model can be applied in China’s futures market.This paper first illustrates the concept of King Keltner model and its application in overseas markets, followed by introduction to the design process, frequent questions and evaluation indicators of program trading models, as well as discussion on the selection and usage of program trading model based on relevant financial theories. Finally, from the perspective of five evaluation indicators including profitability, risk level, stability, investment efficacy and usage cost, this research finds out trading categories suitable with this model by sifting through partial categories in China’s futures market, and discusses the adaptability of the King Keltne model in China’s futures market. In addition, in combination with the author’s investment practices and model development experience, the King Keltner model has been optimized in technical indicator, entry/exit setting and usage index to improve the test performance of the King Keltner model. After testing historical data of PTA contracts, random data generated through Block-Boot Strap method and historical data of multiple portfolios, the optimized model demonstrates reasonable performance and usability in China’s market.