技术脱钩
The Tech Decoupling
AI总结：
本项目研究了过去二十年技术与非技术部门的协同运动，发现2015年后两部门在水平和波动性上出现脱钩现象，且技术部门是经济增长的领先指标，使用ARIMA建模验证了假设，为理解技术部门劳动力市场波动和投资规划提供了新见解。
摘要：
金融市场波动性是投资规划、期权定价和金融市场监管的关键因素，而技术被广泛认为是经济增长的关键驱动力。在本项目中，我们调查了过去二十年中技术与非技术部门的协同运动。我们识别出2015年后两部门在水平和波动性上的脱钩现象，并认为这不能归因于COVID-19冲击。此外，我们证明技术部门作为经济其他部分增长的领先指标。使用ARIMA建模和平稳性检验，我们处理时间序列数据以检验我们的假设，发现技术部门遵循ARIMA(3,1,3)模型，而非技术部门遵循ARIMA(2,1,4)模型。我们的分析包括数据整理、预处理、缺失值处理和探索性数据分析，并讨论了我们工作的优缺点以辅助解释结果。总体而言，我们的发现为技术与经济增长的关系提供了新见解。我们的结果可用于理解技术部门的劳动力市场波动和投资规划评估。
英文摘要：
Financial market volatility is a crucial factor for investment planning, option pricing, and financial market regulation, and technology is widely recognized as a key driver of economic growth. In this project, we investigate the co-movement of technology and non-technology sectors over the last two decades. We identify a decoupling phenomenon in the levels and volatility of the two sectors after 2015 and argue that this cannot be attributed to the COVID-19 shock. Furthermore, we demonstrate that the technology sector serves as a leading indicator of growth for the rest of the economy. Using ARIMA modeling and stationarity tests, we process time series data to test our hypotheses, finding that the technology sector follows an ARIMA(3,1,3) model, while the non-technology sector follows an ARIMA(2,1,4) model. Our analysis encompasses data wrangling, pre-processing, missing value treatment, and exploratory data analysis, and we discuss the merits and shortcomings of our work to aid in the interpretation of our results. Overall, our findings shed new light on the relationship between technology and economic growth. Our results can be used for understanding labor market fluctuations in the technology sector and investment planning assessments.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
