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금융 지표와 파라미터 최적화를 통한 로보어드바이저 전략 도출 사례

Title
금융 지표와 파라미터 최적화를 통한 로보어드바이저 전략 도출 사례
Other Titles
A Case of Establishing Robo-advisor Strategy through Parameter Optimization
Author
임규건
Keywords
Robo Advisor; Markov Chain Monte Carlo (MCMC); Optimization; Financial Indicators; Market Forecasts; Artificial Intelligence
Issue Date
2020-04
Publisher
한국IT서비스학회
Citation
한국IT서비스학회지, v. 19, no. 2, page. 109-124
Abstract
Facing the 4th Industrial Revolution era, researches on artificial intelligence have become active and attempts have been made to apply machine learning in various fields. In the field of finance, Robo Advisor service, which analyze the market, make investment decisions and allocate assets instead of people, are rapidly expanding. The stock price prediction using the machine learning that has been carried out to date is mainly based on the prediction of the market index such as KOSPI, and utilizes technical data that is fundamental index or price derivative index using financial statement. However, most researches have proceeded without any explicit verification of the prediction rate of the learning data. In this study, we conducted an experiment to determine the degree of market prediction ability of basic indicators, technical indicators, and system risk indicators (AR) used in stock price prediction. First, we set the core parameters for each financial indicator and define the objective function reflecting the return and volatility. Then, an experiment was performed to extract the sample from the distribution of each parameter by the Markov chain Monte Carlo (MCMC) method and to find the optimum value to maximize the objective function. Since Robo Advisor is a commodity that trades financial instruments such as stocks and funds, it can not be utilized only by forecasting the market index. The sample for this experiment is data of 17 years of 1,500 stocks that have been listed in Korea for more than 5 years after listing. As a result of the experiment, it was possible to establish a meaningful trading strategy that exceeds the market return. This study can be utilized as a basis for the development of Robo Advisor products in that it includes a large proportion of listed stocks in Korea, rather than an experiment on a single index, and verifies market predictability of various financial indicators.
URI
http://koreascience.or.kr/article/JAKO202021741260602.pagehttps://repository.hanyang.ac.kr/handle/20.500.11754/165387
ISSN
1975-4256
DOI
10.9716/KITS.2020.19.2.109
Appears in Collections:
GRADUATE SCHOOL OF BUSINESS[S](경영전문대학원) > BUSINESS ADMINISTRATION(경영학과) > Articles
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