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On Three-Layer Data Markets
[article]
2024
arXiv
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We study a three-layer data market comprising users (data owners), platforms, and a data buyer. ...
Imposing this mandate on high-cost platforms and banning data sharing for low-cost ones further enhances user utility. ...
We refer to the above game among the platforms, user, and buyer of data as a three-layer data market with parameters (α, β, c, γ). Here is the timing of the game (see Figure 1 ): 1. ...
arXiv:2402.09697v2
fatcat:dfgbaq2owjhdlb23uhvpkz4y6a
Predicting Stock Market Trends Based on Macroeconomic Indicators through Machine Learning Approach: A Case Study of KSE 100 INDEX
2023
iRASD Journal of Economics
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The novelty of the study is forecasting the future value of the stock market using ML. Monthly data was collected for the period from Feb 2004 to Dec 2020. ...
The output layer of our study is the closing price of the KSE 100 index, and the input layer consists of 16 macroeconomic variables of the Pakistan economy, which are the industrial production index (IPI ...
An artificial neural network typically consists of three layers: the input layer, output layer, and at least one hidden layer. ...
doi:10.52131/joe.2023.0504.0185
fatcat:bmnssszkvvakbc4cgo2jdxmmwe
Compare with Three Models for Price Forecasting on Steel Market
2012
2012 International Conference on Computer Science and Service System
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Eight steel products, which extracted from Shanghai Baoshan steel market of China at January, 2011 to December 2011, are selected to forecast the price about one week and compare the Mean Absolute Errors ...
One main parameter of each model's is changed step size by programs automatically. Experiments demonstrate that the ASW model is best model which can get lowest Mean Absolute Errors (MAE). ...
Commodity price forecasts can be seen as based on time series of data processing and data analysis that is divided into data acquisition, data processing and forecasting model in three aspects. ...
doi:10.1109/csss.2012.459
fatcat:mr4d6yxnibbgrgrfmv7ualbpmy
An analysis of BERT-based model for Berkshire stock performance prediction using Warren Buffet's letters
2024
Applied and Computational Engineering
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Therefore, accurate predictions of market trends are important for making investment decisions and risk management. The primary approach involves sentiment analysis of reviews on market performance. ...
This work leverages three BERT-based models which are BERT-Gated Recurrent Units (BERT-GRU) model, BERT-Long short-term memory (BERT-LSTM) model, and BERT-Multi-Head Attention model to analyse the Buetts ...
Unlike traditional analysis methods based on technical indicators and historical price data, this textbased prediction method offers a new perspective on market forecasting. ...
doi:10.54254/2755-2721/52/20241232
fatcat:pnwpkmmuizgwxfp2s7iibmz3iy
The Application of Stock Index Price Prediction with Neural Network
2020
Mathematical and Computational Applications
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The dataset consists of the SP500 index, CSI300 index and Nikkei225 index from three different financial markets representing the most developed market, the less developed market and the developing market ...
Furthermore, all the introduced models have better accuracy in the developed financial market than developing ones. ...
One MLP at least has three layers including input layer, hidden layer, and output layer. ...
doi:10.3390/mca25030053
fatcat:6fabrhrfnngk3hru6icrgxdloa
Dynamic Linkages among Carbon, Energy and Financial Markets: Multiplex Recurrence Network Approach
2022
Mathematics
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among the three markets on the basis of the method of the Multiplex recurrence network. ...
It has become a hot issue to integrate the carbon market, energy market, and financial market into one system and explore the relationship among them. ...
Data Availability Statement: The data involved in the paper are available through public channels.
Conflicts of Interest: The authors declare no conflict of interest. ...
doi:10.3390/math10111829
fatcat:35s22gtc6jgcfajqsicp7bzhuu
Multiplex Networks of the Guarantee Market: Evidence from China
2017
Complexity
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We investigate a multiplex network of the guarantee market with three layers corresponding to different types of guarantee relationships in China. ...
The result of the betweenness centrality shows that central companies in one layer are not necessarily central in another layer. ...
Therefore central companies in one layer are not necessarily central in another layer. ...
doi:10.1155/2017/9781890
fatcat:v2qwfr5u7vcfrasmu52545v25m
Risk Analysis of A-H Share Connect Market Based on Deep Learning and BP Neural Network
2022
Computational Intelligence and Neuroscience
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, technical indicators, and macro indicators based on the CES300 Index. ...
Using deep learning and BP neural network algorithm, this study constructs a three-dimensional A-H share interconnection market risk prediction index system including stock price fundamental indicators ...
We mainly use a three-layer neural network, which in short means that only one layer of neurons (called the hidden layer) exists between the input and output layers. ...
doi:10.1155/2022/1921463
pmid:35909840
pmcid:PMC9334109
fatcat:enamde6a2zcirho2vimdftqoai
Design and Implementation of Enterprise Refined Marketing System Under the Background of Big Data
[chapter]
2022
Atlantis Highlights in Intelligent Systems
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The construction of refined marketing system is based on customer segmentation. ...
Through big data technology operations such as data collection, data preprocessing, data analysis and mining, it has realized the function of improving the convenience and efficiency of enterprise data ...
B/S architecture has three layers. ...
doi:10.2991/978-94-6463-030-5_76
fatcat:cwhk573gzbcexba5pwymvgvdla
Mutual Information between Order Book Layers
2022
Entropy
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), and (iii) the mutual information between layers increases when comparing the uppermost layers to the deepest layers analyzed (i.e., further away from the market price). ...
Here, we approach this topic from a theoretical perspective, estimating the amount of mutual information between order book layers, i.e., different buy/sell layers, which are aggregated by buy/sell orders ...
Instead, we split the the data into three equal-size groups based on the X values. ...
doi:10.3390/e24030343
pmid:35327853
pmcid:PMC8947691
fatcat:annvv33wjbhypp6nfvyqwymuqm
The Use of Neural Networks in the Prediction of the Stock Exchange of Thailand (SET) Index
2008
2008 International Conference on Computational Intelligence for Modelling Control & Automation
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Two years' historical data were used to train and test the models. Three suitable neural network models identified by this research are a three layer, a four layer and a five layer neural network. ...
Neural networks are viewed as one of the more suitable techniques. ...
Some raw data used are based on different stock markets, which have different holidays or non trading days, so some data was missing. ...
doi:10.1109/cimca.2008.83
dblp:conf/cimca/ChaigusinCC08
fatcat:qo3b3nta2be7birtzqdurez2mu
Saudi Arabia Stock Market Prediction Using Neural Network
2018
International Journal on Computer Science and Engineering
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The experimental results based on historical data it is possible to modeling stock price using three layer neural ...
However, to our knowledge, there is a very rare study on stock market prediction on Saudi market. ...
Ou, P., and Wang, H. conducted a research on using ten data mining techniques to predicting stock market index movement. ...
doi:10.21817/ijcse/2018/v10i2/181002024
fatcat:hztrlobperhyjamjdwqaudozda
Day-Ahead Electricity Price Forecasting Using the Wavelet Transform and ARIMA Models
2005
IEEE Transactions on Power Systems
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Proposed model is experienced on Nord Pool electricity market and the results are checked in various stages. Also for expression of system error, an indicator of MAPE has been used. ...
Therefore one of the essential and necessary discussions in competitive environment is prices prediction. ...
The data categorizing of neural network input consists three resolutions and data of four days. 200 times iteration is considered for training and three hidden layers 31, 35, and 37 used for each applied ...
doi:10.1109/tpwrs.2005.846054
fatcat:andc4pui75clzjldmpygphgjz4
Application of Multidimensional Data Analysis in Power Marketing Decision Support System Based on Big Data
2016
International Journal of Database Theory and Application
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data into useful information on. based on the multidimensional data analysis technology to build electric power marketing decision-oriented application of data analysis platform, through the companies ...
With the establishment of the power system in depth and marketing system, the power supply enterprise marketing has become a core business, develop marketing strategies to adapt to market is very important ...
Power Marketing Analysis System Structure Construction of power marketing analysis system requires the data layer to enterprise data sources historical business data services layer, based on the need to ...
doi:10.14257/ijdta.2016.9.10.25
fatcat:kcqxnnf3xrhz3nqrhc5f262ytu
Autoencoder-Based Three-Factor Model for the Yield Curve of Japanese Government Bonds and a Trading Strategy
2020
Journal of Risk and Financial Management
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Central bank monetary policy is one of the significant factors influencing interest rate markets. ...
In addition, we focus on the model parameters of the intermediate layer of the neural network that constitute the autoencoder and confirm that the three automatically generated factors represent the "Level ...
Furthermore, we analyzed interest rate data in the Japanese government bond market, and, in the future, we will conduct similar analyses on other market data, such as in the United States and Europe, as ...
doi:10.3390/jrfm13040082
fatcat:om6oq5jjvzbxrlw6gwi2pjpq4a
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