ParticleB is hosting a summer research program for under-grad and grad students focused on machine learning and its applications in financial markets. Based on the experience and outcomes of the previous two internship programs, we have revised the program structure: One project is defined and the accepted interns will collaborate in a team focused on the defined project. ParticleB data team will provide required resources and will work alongside the interns team to facilitate the learning process.
Project Title: Information Extraction from Market Price Pattern Reports
In technical analysis, transitions between rising and falling trends are often signaled by price patterns. By definition, a price pattern is a recognizable configuration of price movement that is identified using a series of trendlines and/or curves. When a price pattern signals a change in trend direction, it is known as a reversal pattern; a continuation pattern occurs when the trend continues in its existing direction following a brief pause. Technical analysts have long used price patterns to examine current movements and forecast future market movements.
Several domain experts monitor market behavior and publish their analysis on price patterns online. In this project, we aim at extracting price patterns from reports alongside their associated parameters. Aggregation on reported patterns is then used to signal market prediction based on pattern definition.
Technical Phases
Review price pattern: describe each pattern using a set of parameters and inferred actions
Data preparation: Scrap technical reports from available data sources
Document Classification: extract related price patterns in each document
Information Extraction: Extract pre defined parameters, timeframe, sentiment and predicted market behavior from reports
Aggregation: Aggregate extracted patterns for each market-timeframe and produce market predictions.
Backtest: calculate prediction and historical price correlation.
Requirements
Eager to learn
Interested in machine learning theory and applications
Working knowledge in Statistics and Linear algebra
Python, git and Docker Fluency
Having a good Knowledge in Machine Learning concepts (Feature space, Generalization, Modeling, ...)
Experience in natural language processing and web scraping is a plus
More Information
Please refer to particleB website for more information on the upcoming research program and application submission.
معرفی شرکت
ParticleB is aiming to apply scientific research in AI and data analytics to products using a problem design mindset. We are currently focused on developing an automated trading platform tailored specifically to optimize risk-anchored portfolios. Natural language processing, exploratory data analysis, recommendation systems and data storytelling are also a few domains in which we have ongoing projects