The Pearson Trend
My name is Murat Yazici. I am a purely mathematical trader. I have B.Sc. Statistics and M.Sc. Quantitative Methods degrees. I have several scientific papers, conference presentations in Texas, Toronto, London, Istanbul, books and book chapters studies, and many projects about mathematical and statistical modelling. I am also journal reviewer at some scientific journals such as Open Science Journal of Statistics and Application, Mathematical and Statistical Sciences, International Journal of Computational and Data Sciences, International Journal of Computers & Technology (IJCT), Biostatistics and Biometrics Open Access Journal (BBOAJ), and Biomedical Journal of Scientific & Technical Research (BJSTR).
What is The Pearson Trend's Logic?
It is based on A Fuzzy Model developed by me.
Vague or fuzzy data and application in several fields, such as psychometry, reliability, marketing, quality control, ballistics, ergonomy, image recognition, artificial intelligence, etc. A typical problem where vague data arise is that of assigning numbers to subjective perceptions or to linguistic variables (such as “enough”, “good”, “sufficiently”, etc.). In fact, there are many cases where observations cannot be known or quantified exactly, and, thus, we can only provide an approximate description of them, or intervals to enclose them. For instance, “in measuring the influence of character size on the reading ability of a video display terminal [ … ] the reading ability of the subject, which is essentially the experimental output, depends on his/her eyesight, age, the environment, individual responses, and even how tired is the individual. Some of these factors cannot be described accurately and [ … ] the best description of these kinds of output is that they are fuzzy outputs”  .
The Pearson Trend is suitable for M15 and above time frames. You can prefer to use H1 time frame and above for more robust results and reduce losses. You can use it on all major parity. I generally use The Pearson Trend on my trading with a take profit as 10 pips.
If you have any current and/or further questions you can send me a message.
Murat YAZICI, M.Sc.
- H. Tanaka, H. Ishibuchi, Identification of possibilistic linear systems by quadratic membership functions of fuzzy parameters, Fuzzy Sets Systems 41 (191) 145-160.
- H. Tanaka, H. Ishibuchi, S. Yoshikawa, Exponential possibility regression analysis, Fuzzy Sets Systems 69 (1995) 305-318.