"Observer Pattern Framework" And Its Application In The Quantitative Investment

Quantitative investment guidelines are built on modern financial theory which is built on the random uncertainty assumptions about financial markets. However, the financial market is a dynamic, non-linear complex adaptive system. Fuzzy uncertainty is more in line with this characteristic, and this fuzzyness is also discouraging people from running for more details on the financial markets. In order to quantify this kind of fuzzyness, we proposed a novel quantitative framework called "Observer Pattern Framework (OPF)" based on quantum mechanics and do some related applied research in this paper by defining basic concepts, setting functions and equations, estimating parameters, building quantitative technical environment, implementing numerical examples and launching a series of practical application work. Mainly as follows:(1)by introducing the main ideas of quantum mechanics and defining the observer equation, observation information source, observation window period, observation function and quantum Phi, we give the logic of the framework model and all mathematical equations. Parameter estimation method and quantitative computing engine are also built based on Matlab, Java and MySQL.(2) Applying the observer pattern framework to asset allocation and market-timing trading scenarios in quantitative investment, we propose the Observer pattern portfolio model (OPPM) and the Observer pattern market-timing model (OPMM).(3) In order to solve models and test their validity, we give numerical examples of all mentioned models in this paper using Chinese A-share market data and quantitative computing engine which is developed independently.