Various quantitative approaches have been attempted to predict the shipping market conditions. In particular, various recent attempts to reveal causality using multivariate models seek to present empirical results for models not presented in existing theories by expanding quantitative analysis, and to raise the need for big data analysis in shipping theory. Big data is expected to have a great impact in the field of logistics and distribution, and various utilization possibilities are suggested. Since the importance of information and information systems has already been emphasized in the existing logistics field, linking with big data is expected to be more efficient. In particular, analysis of exchange rates and stock prices is difficult due to the volatility of various variables in the short and long term. The shipping industry has low flexibility in adjusting fleet volume, but it is difficult to predict the market and manage risks because the volume of maritime transport is affected by various factors. It is an industry. Accordingly, research on new econometric techniques that can analyze and utilize big data related to financial time series is emerging. In this study, we analyzed stock price and exchange rate fluctuations of shipping companies by using R program, which is provided as an open source based on big data, to contribute to understanding future stock price trends and understanding the impact of exchange rate fluctuations.
Ⅰ. 서론
Ⅱ. 해운·물류 및 환율의 선행연구와 현황
Ⅲ. 빅데이터 활용 금융 분석
Ⅳ. 실증분석
Ⅴ. 결론
참고문헌