# Artificial Counselor System for Stock Investment

## TL;DR

This paper introduces an artificial counselor system for stock investment that predicts stock prices using Support Vector Regression and recommends optimal investment portfolios based on risk tolerance, employing Markowitz and fuzzy logic methods.

## Contribution

It presents a novel integrated system combining price prediction and portfolio recommendation using both optimization and fuzzy logic approaches.

## Key findings

- Effective stock price prediction with Support Vector Regression.
- Successful portfolio recommendations considering risk tolerance.
- Positive experimental results on NYSE data.

## Abstract

This paper proposes a novel trading system which plays the role of an artificial counselor for stock investment. In this paper, the stock future prices (technical features) are predicted using Support Vector Regression. Thereafter, the predicted prices are used to recommend which portions of the budget an investor should invest in different existing stocks to have an optimum expected profit considering their level of risk tolerance. Two different methods are used for suggesting best portions, which are Markowitz portfolio theory and fuzzy investment counselor. The first approach is an optimization-based method which considers merely technical features, while the second approach is based on Fuzzy Logic taking into account both technical and fundamental features of the stock market. The experimental results on New York Stock Exchange (NYSE) show the effectiveness of the proposed system.