Horizontal Generalization Properties of Fuzzy Rule-Based Trading Models
نویسندگان
چکیده
We investigate the generalization properties of a data-mining approach to single-position day trading which uses an evolutionary algorithm to construct fuzzy predictive models of financial instruments. The models, expressed as fuzzy rule bases, take a number of popular technical indicators on day t as inputs and produce a trading signal for day t+ 1 based on a dataset of past observations of which actions would have been most profitable. The approach has been applied to trading several financial instruments (large-cap stocks and indices), in order to study the horizontal, i.e., cross-market, generalization capabilities of the models.
منابع مشابه
A QUADRATIC MARGIN-BASED MODEL FOR WEIGHTING FUZZY CLASSIFICATION RULES INSPIRED BY SUPPORT VECTOR MACHINES
Recently, tuning the weights of the rules in Fuzzy Rule-Base Classification Systems is researched in order to improve the accuracy of classification. In this paper, a margin-based optimization model, inspired by Support Vector Machine classifiers, is proposed to compute these fuzzy rule weights. This approach not only considers both accuracy and generalization criteria in a single objective fu...
متن کاملConstructing fuzzy rule-based systems with the R package “frbs”
Fuzzy sets as proposed by Zadeh (1965) are a generalization of classical set theory, in which objects, instead of just being members of a set or not, have a gradual degree of membership. Fuzzy rule-based systems (FRBS) have been used in the past successfully in many applications. They are competitive methods for classification and regression, especially for complex problems. One of their leadin...
متن کاملFinancial Markets Analysis by Probabilistic Fuzzy Modelling
For successful trading in financial markets, it is important to develop financial models where one can identify different states of the market for modifying one’s actions. In this paper, we propose to use probabilistic fuzzy systems for this purpose. We concentrate on Takagi–Sugeno (TS) probabilistic fuzzy systems that combine interpretability of fuzzy systems with the statistical properties of...
متن کاملA Novel Fuzzy Associative Memory Architecture for Stock Market Prediction and Trading
In this paper, a novel stock trading framework based on a neuro-fuzzy associative memory (FAM) architecture is proposed. The architecture incorporates the approximate analogical reasoning schema (AARS) to resolve the problem of discontinuous (staircase) response and inefficient memory utilization with uniform quantization in the associative memory structure. The resultant structure is conceptua...
متن کاملA New High-order Takagi-Sugeno Fuzzy Model Based on Deformed Linear Models
Amongst possible choices for identifying complicated processes for prediction, simulation, and approximation applications, high-order Takagi-Sugeno (TS) fuzzy models are fitting tools. Although they can construct models with rather high complexity, they are not as interpretable as first-order TS fuzzy models. In this paper, we first propose to use Deformed Linear Models (DLMs) in consequence pa...
متن کامل