Nothing Special   »   [go: up one dir, main page]

Alamatian et al., 2021 - Google Patents

Using Market Indicators to Eliminate Local Trends for Financial Time Series Cross-Correlation Analysis.

Alamatian et al., 2021

View PDF
Document ID
18054990991466780065
Author
Alamatian Z
Jahan M
Fard A
Publication year
Publication venue
Canadian AI

External Links

Snippet

Multifractal detrended cross-correlation analysis (MFDCCA) is largely used to analyze non- stationary financial time series. Existing methods for such analysis utilize the time series itself as the detrending function with a polynomial. We propose a technique for a more …
Continue reading at assets.pubpub.org (PDF) (other versions)

Classifications

    • G—PHYSICS
    • G06—COMPUTING; CALCULATING; COUNTING
    • G06Q—DATA PROCESSING SYSTEMS OR METHODS, SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL, SUPERVISORY OR FORECASTING PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL, SUPERVISORY OR FORECASTING PURPOSES, NOT OTHERWISE PROVIDED FOR
    • G06Q40/00—Finance; Insurance; Tax strategies; Processing of corporate or income taxes
    • G06Q40/06—Investment, e.g. financial instruments, portfolio management or fund management
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING; COUNTING
    • G06Q—DATA PROCESSING SYSTEMS OR METHODS, SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL, SUPERVISORY OR FORECASTING PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL, SUPERVISORY OR FORECASTING PURPOSES, NOT OTHERWISE PROVIDED FOR
    • G06Q40/00—Finance; Insurance; Tax strategies; Processing of corporate or income taxes
    • G06Q40/02—Banking, e.g. interest calculation, credit approval, mortgages, home banking or on-line banking
    • G06Q40/025—Credit processing or loan processing, e.g. risk analysis for mortgages
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING; COUNTING
    • G06F—ELECTRICAL DIGITAL DATA PROCESSING
    • G06F17/00—Digital computing or data processing equipment or methods, specially adapted for specific functions
    • G06F17/10—Complex mathematical operations
    • G06F17/18—Complex mathematical operations for evaluating statistical data, e.g. average values, frequency distributions, probability functions, regression analysis
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING; COUNTING
    • G06F—ELECTRICAL DIGITAL DATA PROCESSING
    • G06F17/00—Digital computing or data processing equipment or methods, specially adapted for specific functions
    • G06F17/10—Complex mathematical operations
    • G06F17/11—Complex mathematical operations for solving equations, e.g. nonlinear equations, general mathematical optimization problems
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING; COUNTING
    • G06Q—DATA PROCESSING SYSTEMS OR METHODS, SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL, SUPERVISORY OR FORECASTING PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL, SUPERVISORY OR FORECASTING PURPOSES, NOT OTHERWISE PROVIDED FOR
    • G06Q40/00—Finance; Insurance; Tax strategies; Processing of corporate or income taxes
    • G06Q40/04—Exchange, e.g. stocks, commodities, derivatives or currency exchange
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING; COUNTING
    • G06F—ELECTRICAL DIGITAL DATA PROCESSING
    • G06F17/00—Digital computing or data processing equipment or methods, specially adapted for specific functions
    • G06F17/30—Information retrieval; Database structures therefor; File system structures therefor
    • G06F17/30286—Information retrieval; Database structures therefor; File system structures therefor in structured data stores
    • G06F17/30386—Retrieval requests
    • G06F17/30424—Query processing
    • G06F17/30477—Query execution
    • G06F17/30507—Applying rules; deductive queries
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING; COUNTING
    • G06Q—DATA PROCESSING SYSTEMS OR METHODS, SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL, SUPERVISORY OR FORECASTING PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL, SUPERVISORY OR FORECASTING PURPOSES, NOT OTHERWISE PROVIDED FOR
    • G06Q40/00—Finance; Insurance; Tax strategies; Processing of corporate or income taxes
    • G06Q40/08—Insurance, e.g. risk analysis or pensions
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING; COUNTING
    • G06N—COMPUTER SYSTEMS BASED ON SPECIFIC COMPUTATIONAL MODELS
    • G06N99/00—Subject matter not provided for in other groups of this subclass
    • G06N99/005—Learning machines, i.e. computer in which a programme is changed according to experience gained by the machine itself during a complete run
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING; COUNTING
    • G06Q—DATA PROCESSING SYSTEMS OR METHODS, SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL, SUPERVISORY OR FORECASTING PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL, SUPERVISORY OR FORECASTING PURPOSES, NOT OTHERWISE PROVIDED FOR
    • G06Q10/00—Administration; Management
    • G06Q10/06—Resources, workflows, human or project management, e.g. organising, planning, scheduling or allocating time, human or machine resources; Enterprise planning; Organisational models
    • G06Q10/063—Operations research or analysis
    • G06Q10/0635—Risk analysis
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING; COUNTING
    • G06N—COMPUTER SYSTEMS BASED ON SPECIFIC COMPUTATIONAL MODELS
    • G06N5/00—Computer systems utilising knowledge based models
    • G06N5/04—Inference methods or devices
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING; COUNTING
    • G06K—RECOGNITION OF DATA; PRESENTATION OF DATA; RECORD CARRIERS; HANDLING RECORD CARRIERS
    • G06K9/00—Methods or arrangements for reading or recognising printed or written characters or for recognising patterns, e.g. fingerprints
    • G06K9/62—Methods or arrangements for recognition using electronic means
    • G06K9/6217—Design or setup of recognition systems and techniques; Extraction of features in feature space; Clustering techniques; Blind source separation
    • G06K9/6232—Extracting features by transforming the feature space, e.g. multidimensional scaling; Mappings, e.g. subspace methods
    • G06K9/6247—Extracting features by transforming the feature space, e.g. multidimensional scaling; Mappings, e.g. subspace methods based on an approximation criterion, e.g. principal component analysis

Similar Documents

Publication Publication Date Title
Wang et al. Modeling and forecasting realized volatility with the fractional Ornstein–Uhlenbeck process
Ruan et al. Long-term correlations and multifractal nature in the intertrade durations of a liquid Chinese stock and its warrant
He et al. Forecasting exchange rate using variational mode decomposition and entropy theory
Horst et al. Stochastic volatility models including open, close, high and low prices
Kristoufek On spurious anti-persistence in the US stock indices
Gong et al. Forecasting return volatility of the CSI 300 index using the stochastic volatility model with continuous volatility and jumps
Alamatian et al. Using Market Indicators to Eliminate Local Trends for Financial Time Series Cross-Correlation Analysis.
Gu et al. An automated financial indices-processing scheme for classifying market liquidity regimes
Ismail et al. Overview of Long Memory for Economic and Financial Time Series Dataset and Related Time Series Models: A Review Study.
Chen et al. Forecasting intraday trading volume: a kalman filter approach
Isenahd et al. Forecasting Nigerian stock market returns using ARIMA and artificial neural network models
Kuo et al. Improving pairs trading strategies using two-stage deep learning methods and analyses of time (In) variant Inputs for trading performance
Kim Parameter estimation in stochastic volatility models with missing data using particle methods and the EM algorithm
US20210304310A1 (en) System and method for estimating multifactor models of illiquid, stale and noisy financial and economic data
Bianchi et al. The dynamics of expected returns: Evidence from multi-scale time series modeling
Bosque et al. Probability of informed trading: a Bayesian approach
Dima et al. Mutual information and persistence in the stochastic volatility of market returns: An emergent market example
Rodriguez et al. A non-parametric statistic for testing conditional heteroscedasticity for unobserved component models
Subramoney et al. Var estimation using extreme value mixture models for cryptocurrencies
Ozun et al. Modeling long‐term memory effect in stock prices: A comparative analysis with GPH test and Daubechies wavelets
Woźniak et al. HCR & HCR-GARCH-Novel Statistical Learning Models for Value at Risk Estimation
Letchford et al. Optimizing the moving average
Kola et al. The (De) merits of using Integral Transforms in Predicting Structural Break Points
Babiš et al. Time series clustering based on time-varying Hurst exponent.
Kamalov et al. Comprehensive hybrid regression model for financial forecasting in neutrosophic logic