Prediction of the Future Development of Gold Price

被引:10
|
作者
Brabenec, Tomas [1 ]
Suler, Petr [2 ]
Horak, Jakub [2 ]
Petras, Milos [3 ]
机构
[1] Univ Econ, Fac Finance & Accounting, Nam W Churchilla 1938-4, Prague 13067, Czech Republic
[2] Inst Technol & Business, Sch Expertness & Valuat, Okruzni 517-10, Ceske Budejovice 37001, Czech Republic
[3] Tech Univ Kosice, Inst Earth Resources, Fac Min Ecol Proc Control & Geotechnol, Pk Komenskeho 19, Kosice 04200, Slovakia
关键词
Gold price; prediction; global economic recession; state precautions; liquidity; SAFE HAVEN; FINANCIAL ECONOMICS; OIL; VOLATILITY; HEDGE; DEMAND; SHOCKS; RISK;
D O I
10.46544/AMS.v25i2.11
中图分类号
P [天文学、地球科学];
学科分类号
07 ;
摘要
Gold belongs, thanks to its extraordinary qualities, to the most interesting and well-known precious metals as far as investment is concerned. The paper aims to estimate the future development of the gold price and determine whether the gold price actually increases in times of economic recession. For the purpose of the analysis, data about the daily gold price from 2006 to July 2020 is used. To elaborate this paper, five methods of time series balancing were employed, namely Neural Networks, Decision Tree, Gradient Boosted Tree, Linear Regression, and Nearest Neighbours. The methods are applied to a training data set, and the final model is tested on the testing data set. The respective models' residues are presented in a graphic form as well as the Probability Density Histogram, Training Data Set Residues Histogram, and a graph of testing data set residues. The future development of the gold price for the next calendar year is predicted. Market participants buy gold in the first moments of the economic recession in order to keep the value of their property. Consequently, however, they lack cash and are forced to sell the gold again. A similar development can be expected now too. A global economic recession can be expected. Debtors will have to get rid of their investments, which will cause the gold price to fall dramatically. The gold price reaches its maximum value at the end of the observed period; then, it should decrease progressively to the end of 2020. At the beginning of 2021, the price should slump. Then, in the following six months, it should follow a growth path again.
引用
收藏
页码:250 / 262
页数:13
相关论文
共 50 条
  • [1] THE MAIN GOLD PRICE DETERMINANTS AND THE FORECAST OF GOLD PRICE FUTURE TRENDS
    Gaspareniene, Ligita
    Remeikiene, Rita
    Sadeckas, Alius
    Ginevicius, Romualdas
    [J]. ECONOMICS & SOCIOLOGY, 2018, 11 (03) : 248 - 264
  • [2] Low gold price affects future production
    不详
    [J]. MINING ENGINEERING, 2001, 53 (05) : 19 - 19
  • [3] FUTURE OUTLOOK FOR FREE MARKET PRICE OF GOLD
    JEFFERY, A
    [J]. METALL, 1971, 25 (07): : 811 - &
  • [4] The Prediction of Gold Price Using ARIMA Model
    Yang, Xiaohui
    [J]. PROCEEDINGS OF THE 2ND INTERNATIONAL CONFERENCE ON SOCIAL SCIENCE, PUBLIC HEALTH AND EDUCATION (SSPHE 2018), 2018, 196 : 273 - 276
  • [5] Prediction Possibilities of Future Price Development of Liquid Investment Instruments and Quantification of a Percent Advantage
    Stadnik, Bohumil
    [J]. FINANCIAL MANAGEMENT OF FIRMS AND FINANCIAL INSTITUTIONS, 2011, : 475 - 493
  • [6] Regression and Hidden Markov Models for Gold Price Prediction
    Shen, Li
    Shen, Kun
    Yi, Chao
    Chen, Yixin
    [J]. 2020 IEEE INTERNATIONAL CONFERENCE ON BIG DATA (BIG DATA), 2020, : 5451 - 5456
  • [7] Prediction of Gold Price Movement Using Discretization Procedure
    Banerjee, Debanjan
    Ghosal, Arijit
    Mukherjee, Imon
    [J]. COMPUTATIONAL INTELLIGENCE IN DATA MINING, 2019, 711 : 345 - 356
  • [8] Evaluation and prediction of polyolefin price development
    Vochozka, Marek
    Neuschlova, Lenka
    Janikova, Jana
    [J]. ACTA MONTANISTICA SLOVACA, 2023, 28 (03) : 733 - 751
  • [9] Cryptocurrency Price Prediction Algorithms: A Survey and Future Directions
    John, David L.
    Binnewies, Sebastian
    Stantic, Bela
    [J]. FORECASTING, 2024, 6 (03): : 637 - 671
  • [10] The prediction for London gold price: improved empirical mode decomposition
    Hua, Qiuling
    Jiang, Tingfeng
    [J]. APPLIED ECONOMICS LETTERS, 2015, 22 (17) : 1404 - 1408