随着我国经济的持续增长,股票市场逐渐成为整个金融业,尤其是证券业不可缺少的一部分。其中股票的价格更是引起众多投资者的关心。基于此,本文利用python在tushare上爬取中信证券(600030) 2022年3月24日到2023年3月24日一年的交易数据,...随着我国经济的持续增长,股票市场逐渐成为整个金融业,尤其是证券业不可缺少的一部分。其中股票的价格更是引起众多投资者的关心。基于此,本文利用python在tushare上爬取中信证券(600030) 2022年3月24日到2023年3月24日一年的交易数据,并选取时间序列ARIMA模型、长短期记忆神经网络(LSTM)模型对中信证券(600030)的股票开盘价格进行训练与预测研究,实证表明ARIMA模型三天预测价格与真实价格最大误差为0.0437855,真实值与预测值非常接近;长短期记忆神经网络(LSTM)模型损失函数MES为0.33125543,并且预测值除了某几个极值点外正确率较高。这表明ARIMA模型短期预测效果较好,LSTM神经网络模型更能拟合所有的股票价格,即说明无论是ARIMA模型还是LSTM模型都能够为股票投资者提供帮助。With the continuous growth of China’s economy, the stock market has gradually become an indispensable part of the whole financial industry, especially the securities industry. Among them, the stock price is causing the concern of many investors. Based on this, this paper uses python to climb in tushare the trading data of Citic Securities (600030) from March 24,2022 to March 24,2023, The time series ARIMA model and long and short-term memory neural network (LSTM) model were selected to train and predict the stock opening price of CITIC Securities (600030), Empirically show that the maximum error of the three-day forecast price and the true price is 0.0437855, The true value is very close to the predicted value. Long- and short-term memory neural network (LSTM) model loss function MES is 0.33125543, and the predicted value is higher except for a few extreme points. This shows that the ARIMA model has better short-term prediction effect, and the LSTM neural network model can fit all stock prices, that both ARIMA model and LSTM model can provide help for stock investors.展开更多
本文结合中国实际情况,利用2002~2022年的相关数据,首先从整体上对我国生产性服务业利用外资对经济增长的影响进行多元线性时间序列回归分析,其次从各种细分行业的角度建立动态VAR模型,探究生产性服务业各行业的外商直接投资和经济增长...本文结合中国实际情况,利用2002~2022年的相关数据,首先从整体上对我国生产性服务业利用外资对经济增长的影响进行多元线性时间序列回归分析,其次从各种细分行业的角度建立动态VAR模型,探究生产性服务业各行业的外商直接投资和经济增长的关系。研究结果表明:生产性服务业外商直接投资对我国经济发展起着正向推动作用。从细分行业的角度来看,短期内,我国生产性服务业的租赁、商务服务业,科学研究业及房地产业的实际使用的外资数量的提升可以明显地促进GDP的值,并且金融业利用外资额的提升对GDP的增长影响不大;从长期来看,六个行业的实际FDI对经济增长都起到促进作用。其中交通运输、仓储和邮政业,信息传输、计算机服务和软件业和技术服务和地质勘查业的实际FDI的增加是GDP增长的强大驱动力。最后根据实证研究结果提出了制定合适的政策指引FDI、推动区域协调发展、提高人力资本的水平等可行的政策建议。Drawing on China’s actual circumstances and utilizing relevant data spanning from 2002 to 2022, this paper first conducts a multivariate linear time series regression analysis to assess the overall impact of foreign direct investment (FDI) in China’s producer services on economic growth. Subsequently, a dynamic VAR model is established from the perspective of various sub-sectors to explore the relationship between FDI in each producer services sector and economic growth. The research findings reveal that FDI in producer services positively contributes to China’s economic development. From a sector-specific perspective, in the short term, the increase in the actual amount of FDI utilized in leasing and business services, scientific research, and real estate within China’s producer services sector significantly promotes GDP growth, while the increase in FDI utilized in the financial sector has a relatively limited impact on GDP growth. In the long term, however, the actual FDI in all six sectors contributes to economic growth. Notably, the growth in actual FDI in transportation, storage, and postal services;information transmission, computer services, and software;as well as technical services and geological exploration emerges as potent drivers of GDP growth. Finally, based on the empirical research findings, feasible policy recommendations are proposed, including formulating appropriate policies to guide FDI, promoting balanced regional development, and enhancing the level of human capital.展开更多
文摘随着我国经济的持续增长,股票市场逐渐成为整个金融业,尤其是证券业不可缺少的一部分。其中股票的价格更是引起众多投资者的关心。基于此,本文利用python在tushare上爬取中信证券(600030) 2022年3月24日到2023年3月24日一年的交易数据,并选取时间序列ARIMA模型、长短期记忆神经网络(LSTM)模型对中信证券(600030)的股票开盘价格进行训练与预测研究,实证表明ARIMA模型三天预测价格与真实价格最大误差为0.0437855,真实值与预测值非常接近;长短期记忆神经网络(LSTM)模型损失函数MES为0.33125543,并且预测值除了某几个极值点外正确率较高。这表明ARIMA模型短期预测效果较好,LSTM神经网络模型更能拟合所有的股票价格,即说明无论是ARIMA模型还是LSTM模型都能够为股票投资者提供帮助。With the continuous growth of China’s economy, the stock market has gradually become an indispensable part of the whole financial industry, especially the securities industry. Among them, the stock price is causing the concern of many investors. Based on this, this paper uses python to climb in tushare the trading data of Citic Securities (600030) from March 24,2022 to March 24,2023, The time series ARIMA model and long and short-term memory neural network (LSTM) model were selected to train and predict the stock opening price of CITIC Securities (600030), Empirically show that the maximum error of the three-day forecast price and the true price is 0.0437855, The true value is very close to the predicted value. Long- and short-term memory neural network (LSTM) model loss function MES is 0.33125543, and the predicted value is higher except for a few extreme points. This shows that the ARIMA model has better short-term prediction effect, and the LSTM neural network model can fit all stock prices, that both ARIMA model and LSTM model can provide help for stock investors.
文摘本文结合中国实际情况,利用2002~2022年的相关数据,首先从整体上对我国生产性服务业利用外资对经济增长的影响进行多元线性时间序列回归分析,其次从各种细分行业的角度建立动态VAR模型,探究生产性服务业各行业的外商直接投资和经济增长的关系。研究结果表明:生产性服务业外商直接投资对我国经济发展起着正向推动作用。从细分行业的角度来看,短期内,我国生产性服务业的租赁、商务服务业,科学研究业及房地产业的实际使用的外资数量的提升可以明显地促进GDP的值,并且金融业利用外资额的提升对GDP的增长影响不大;从长期来看,六个行业的实际FDI对经济增长都起到促进作用。其中交通运输、仓储和邮政业,信息传输、计算机服务和软件业和技术服务和地质勘查业的实际FDI的增加是GDP增长的强大驱动力。最后根据实证研究结果提出了制定合适的政策指引FDI、推动区域协调发展、提高人力资本的水平等可行的政策建议。Drawing on China’s actual circumstances and utilizing relevant data spanning from 2002 to 2022, this paper first conducts a multivariate linear time series regression analysis to assess the overall impact of foreign direct investment (FDI) in China’s producer services on economic growth. Subsequently, a dynamic VAR model is established from the perspective of various sub-sectors to explore the relationship between FDI in each producer services sector and economic growth. The research findings reveal that FDI in producer services positively contributes to China’s economic development. From a sector-specific perspective, in the short term, the increase in the actual amount of FDI utilized in leasing and business services, scientific research, and real estate within China’s producer services sector significantly promotes GDP growth, while the increase in FDI utilized in the financial sector has a relatively limited impact on GDP growth. In the long term, however, the actual FDI in all six sectors contributes to economic growth. Notably, the growth in actual FDI in transportation, storage, and postal services;information transmission, computer services, and software;as well as technical services and geological exploration emerges as potent drivers of GDP growth. Finally, based on the empirical research findings, feasible policy recommendations are proposed, including formulating appropriate policies to guide FDI, promoting balanced regional development, and enhancing the level of human capital.
