Forecasting CPI Based on Convolutional Neural Network and Long Short-Term Memory Network
CHEN Yidong, LU Zhonghua
1.High-Performance Computing Department, Computer Network Information Center, Chinese Academy of Sciences, Beijing 100190, China
2.University of Chinese Academy of Sciences, Beijing 100049, China
CHEN Yidong, LU Zhonghua. Forecasting CPI Based on Convolutional Neural Network and Long Short-Term Memory Network[J]. Computer Engineering and Applications, 2022, 58(9): 256-262.
[1] KONTONIKAS A.Inflation and inflation uncertainty in the united kingdom evidence from GARCH modeling[J].Economic Modelling,2003,21(3):525-543.
[2] JONATHAN W,FORECASTING U S.Inflation by Bayesian model averaging[J].Journal of Forecasting,2009,28(21):131-144.
[3] CARSTENSEN K,HAGEN J,HOSSFELD O,et al.Money demand stability and inflation prediction in the four largest EMU countries[J].Scottish Journal of Political Economy,2010,56(1):73-93.
[4] KOOP G,KOROBILIS D.Forecasting inflation using dynamic model averaging[J].International Economic Review,2012,53(3):11-23.
[5] AHMAR A S,ACHMAD G S,LISTYORINI T,et al.Implementation of the ARIMA(p,d,q) method to forecasting CPI data using forecast package in R software[J].Journal of Physics Conference Series,2018,1028(1):012189.
[6] 赵影,周岳.CPI与实体经济状况、货币供应量的关系及对CPI未来走势的预测[J].金融经济,2010(5):130-131.
ZHAO Y,ZHOU Y.The relationship between CPI and economic conditions,money supply and the forecast of the future trend of CPI[J].Financial Economy,2010(5):130-131.
[7] 雷鹏飞.基于季节性ARIMA模型的中国CPI序列分析与预测[J].统计与决策,2014(14):32-34.
LEI P F.Analysis and forecast of CPI series in China based on seasonal ARIMA model[J].Statistics & Decision,2014(14):32-34.
[8] 肖良.基于季节性ARIMA模型的居民消费水平预测[J].统计与决策,2016(8):83-86.
XIAO L.Household consumption forecast based on seasonal ARIMA model[J].Statistics & Decision,2016(8):83-36.
[9] CHEN X,RACINE J,SWANSON N R.Semiparametric ARX neural-network models with an application to forecasting inflation[J].IEEE Transactions on Neural Networks,2001,12(4):674-683.
[10] YE Y,SHAO Y,CHEN W.Comparing inflation forecasts using an ε-wavelet twin support vector regression[J].Journal of Information and Computational Science,2013,10(7):2041-2049.
[11] SERMPINIS G,STASINAKIS C,THEOFILATOS K,et al.Inflation and unemployment forecasting with genetic support vector regression[J].Journal of Forecasting,2014,33(6).
[12] QUAN J.Two-step testing procedure for price discovery role of futures prices[J].Journal of Futures Markets,1992,12(2):139-149.
[13] KAUFMANN R K,ULLMAN B.Oil prices,speculation,and fundamentals:interpreting causal relations among spot and futures prices[J].Energy Economics,2009,31(4):550-558.
[14] WONG W K.Market efficiency of oil spot and futures:a mean-variance and stochastic dominance approach[J].Energy Economics,2010,32(5):979-986.
[15] BIGMAN D,GOLDFARB D,SCHECHTMAN E.Futures market efficiency and the time content of the information sets[J].Journal of Futures Markets,2010,3(3):321-334.
[16] BAILLIE R T,MYERS R J.Bivariate GARCH estimation of the optimal commodity futures hedge[J].Journal of Applied Econometrics,2010,6(3):31-34.
[17] FOSTER A J.Price discovery in oil markets:a time varying analysis of the 1990-91 gulf conflict[J].Energy Economics,1996,18(3):231-246.
[18] 周舟,成思危.沪深300股指期货市场中的宏观经济信息发布与价格发现[J].系统工程理论与实践,2013,33(12):3045-3053.
ZHOU Z,CHENG S W.Macroeconomic announcements and price discovery in the CSl 300 stock index futures market[J].Systems Engineering Theory & Practice,2013,33(12):3045-3053.
[19] 王楠,汪琛德.郑商所农产品期货对通货膨胀的预警作用——基于VAR模型的分析[J].系统管理学报,2015,24(6):854-858.
WANG N,WANG C D.The warning function of future prices of agricultural products in ZCE to the inflation of China:a VAR analysis[J].Journal of Systems & Management,2015,24(6):854-858.
[20] GERS F A,CUMMINS F.Learning to forget:continual prediction with LSTM[J].Neural Computation,2000,12(10):2451-2471.
[21] DENG L,PLATT J.Ensemble deep learning for speech recognition[C]//Proceedings of the Annual Conference of the International Speech Communication Association.New York:IEEE,2014:1915-1919.
[22] BAE S,CHOI I,KIM N.Acoustic scene classification using parallel combination of LSTM and CNN[J].IEEE Signal Processing Magazine,2015,32(3):16-34.
[23] TARA N,ORIOL V,ANDREW S,et al.Convolutional,long short-term memory,fully connected deep neural networks[C]//International Conference on Acoustics,Speech and Signal Processing.Brisbane,Australia:IEEE,2015:4580-4584.
[24] NG Y H,HAUSKNECHT M,VIJAYANARASIMHAN S,et al.Beyond short snippets:deep networks for video classification[C]//Conference on Computer Vision and Pattern Recognition.Boston,USA:IEEE,2015:4694-4702.