In scenarios such as high-frequency trading, asset allocation, and risk linkage identification in finance, there is an increasing need to leverage the similarity between financial time series for querying. However, traditional CPU architectures easily encounter computationally and memory-intensive problems when handling large-scale sliding windows, distance matrix creation, and candidate verification processes. Based on three years of research on GPU parallel computing, time series distance calculation, and financial sequence similarity modeling, this paper proposes a collaborative optimization scheme for batch query execution. Window-level standardization, batch distance calculation, shared memory caching, candidate filtering, and result compression and write-back are used to achieve hierarchical parallelism of the query path. Using real financial samples of Apple's historical daily closing price series, statistical analysis and connectivity metrics are conducted. Candidate size and distance distribution under different window lengths are constructed to analyze the necessary conditions for thread bundle division, memory access continuity, and kernel function fusion in GPU mapping. Research shows that financial sequence connectivity optimization cannot be achieved simply by speeding up a single operator; rather, it requires a combined design of data layout, threshold pruning, and batch processing strategies. This research can provide engineering references for similar event retrieval, pattern tracking, and risk propagation identification in quantitative finance.

Huilin Zhang. A GPU-Parallel Optimization Method for Financial Time Series Similarity Linkages: A Study Based on a Collaborative Mechanism of Batch Distance Calculation and Candidate Filtering. Socio-Economic Statistics Research (2026), Vol. 7, Issue 1: 48-57. https://doi.org/10.38007/SESR.2026.070106.

[1] Liu, D., Shen, Q., & Liu, J. (2026). The Health-Wealth Gradient in Labor Markets: Integrating Health, Insurance, and Social Metrics to Predict Employment Density.

[2] Lu, Z. (2025). Design and Practice of AI Intelligent Mentor System for DevOps Education. European Journal of Education Science, 1(3), 25-31.

[3] Hui, X. (2026). Research on the Design and Optimization of Automated Data Collection and Visual Dashboard in the Medical Industry. Journal of Computer, Signal, and System Research, 3(1), 27-34.

[4] Wang, Y. (2026). Research on Optimization of Neuromuscular Rehabilitation Program Based on Physiological Assessment. European Journal of AI, Computing & Informatics, 2(1), 21-30.

[5] Ding, J. (2026). Optimization Strategies for Supply Chain Management and Quality Control in the Automotive Manufacturing Industry. Strategic Management Insights, 3(1), 17-23.

[6] Zhang, Q. (2026). How to Improve Marketing Efficiency and Precision through AI-Driven Innovative Products. Strategic Management Insights, 3(1), 1-8.

[7] Liu, Y. (2026). The Promoting Role of Fintech and Product Innovation in the Context of the Digital Economy. Strategic Management Insights, 3(1), 9-16.

[8] Lu, C. (2026). Research on 3D Reconstruction Methods of Remote Sensing Images Combined with Deep Learning and GIS. International Journal of Engineering Advances, 3(1), 15-22.

[9] Cai, Y. (2026). Design and Implementation of System Extensibility under High Concurrency Environment. International Journal of Engineering Advances, 3(1), 31-37.

[10] Liu, Y. (2026). The Application of Data-Driven Financial Risk Management in Multinational Enterprises. Economics and Management Innovation, 3(1), 20-26.

[11] Huang, J. (2026). Practice of Public Space Optimization and Functional Enhancement in Cultural Architecture. European Journal of Engineering and Technologies, 2(1), 9-21.

[12] Xu, D. (2026). AI-Driven Video Content Optimization Strategies for Immersive Media. European Journal of Engineering and Technologies, 2(1), 1-8.

[13] Qi, Y. (2026). AI Driven Payment System Security Improvement and User Privacy Protection Mechanism. Journal of Computer, Signal, and System Research, 3(1), 35-41.

[14] Qi, Y. (2026). High Reliability Architecture and Compliance Design of Enterprise Level Financial Infrastructure. International Journal of Engineering Advances, 3(1), 8-14.

[15] Lu, Z. (2025). Design and Practice of AI Intelligent Mentor System for DevOps Education. European Journal of Education Science, 1(3), 25-31.

[16] Lu, Z. (2025). AI-Driven Cross-Cloud Operations Language Standardisation and Knowledge Sharing System. European Journal of AI, Computing & Informatics, 1(4), 43-50.

[17] Wang, C. (2025). Research on Market Evaluation Strategies for Financial Institutions Based on Big Data Analysis.

[18] Hou, Y. (2026). Research on BIOS and BMC Compatibility Optimization Methods for Cross-Generation Servers in Production Environments.

[19] Zhang, X. (2025). Optimization and Implementation of Time Series Dimensionality Reduction Anti-fraud Model Integrating PCA and LSTM under the Federated Learning Framework. Procedia Computer Science, 262, 992-1001.

[20] Hou, Y. (2026). Research on Server Performance Stability Assurance Mechanisms during Cross-Generation Computing Platform Upgrades.

[21] Zhang, X. (2025, May). Automobile Finance Credit Fraud Risk Early Warning System based on Louvain Algorithm and XGBoost Model. In 2025 3rd International Conference on Data Science and Information System (ICDSIS) (pp. 1-7). IEEE.

[22] Hong, Y. (2025). Architecture Design and Performance Optimization of a Large-scale Online Simulation Platform for Business Decision-making. Advances in Computer and Communication, 6(4).

[23] Truong, T. H. (2025). Research on the Application of Digital Healthcare Platforms in Chronic Disease Management. Advances in Computer and Communication, 6(5).

[24] Huijie Pan. Discussion on Low-Latency Computing Strategies in Real-Time Hardware Generation. International Journal of Neural Network (2025), Vol. 4, Issue 1: 57-64.

[25] Yixian Jiang. Performance Optimization and Improvement of Advertising Machine Learning Platform Based on Distributed Systems. International Journal of Big Data Intelligent Technology (2026), Vol. 7, Issue 1: 9-17

[26] Zhengle Wei. Research on Innovative Design of Financial Derivatives and Market Risk Management Strategies. International Journal of Social Sciences and Economic Management (2026), Vol. 7, Issue 1: 19-27

[27] Yilin Fu. Research on the Application of Innovative Financial Technologies in Capital Market Risk Management. Socio-Economic Statistics Research (2026), Vol. 7, Issue 1: 1-9

[28] Linwei Wu. Data Visualization and Decision Support Analysis Based on Tableau. Socio-Economic Statistics Research (2026), Vol. 7, Issue 1: 10-18

[29] Han, X. (2026). Research on Process Decision-Making Behavior under Incomplete Information Conditions in Automobile Manufacturing Systems.

[30] Yin, J. (2026). Research on Financial Time Series Prediction and Multiscale Correlation Based on the Fusion of Network Big Data and Deep Learning.

[31] Zhou, Y. (2024, November). Construction of a Multi-factor Quantitative Stock Selection System for the New Energy Industry Based on Microservices Architecture and Machine Learning Components. In International Conference on Cognitive based Information Processing and Applications (pp. 163-174). Singapore: Springer Nature Singapore.

[32] Huang, J. (2025, August). Research on Multi-Model Fusion Machine Learning Demand Intelligent Forecasting System in Cloud Computing Environment. In 2025 2nd International Conference on Intelligent Algorithms for Computational Intelligence Systems (IACIS) (pp. 1-7). IEEE.

[33] Hua, X. (2024, November). Design and Implementation of a Game QoE Monitoring and Evaluation System Driven by Network Traffic Analysis. In International Conference on Cognitive based Information Processing and Applications (pp. 149-161). Singapore: Springer Nature Singapore.

[34] Qi, Y. (2025, October). Research on Privacy Protection of AI Models in Big Data Using Differential Privacy Technology. In 2025 2nd International Conference on Software, Systems and Information Technology (SSITCON) (pp. 1-5). IEEE.

[35] Truong, T. H. (2026). Research on Risks and Countermeasures of Enterprise E-Commerce Transformation in the Cross-Border E-Commerce Environment.

[36] Wu, L. (2025, December). Design and Application of Automatic Data Set Generation Tool Based on KLEE in Embedded Memory Management Performance Test Framework. In 2025 IEEE 17th International Conference on Computational Intelligence and Communication Networks (CICN) (pp. 1111-1117). IEEE.

[37] Wu, L. (2025, December). Design and Application of Automatic Data Set Generation Tool Based on KLEE in Embedded Memory Management Performance Test Framework. In 2025 IEEE 17th International Conference on Computational Intelligence and Communication Networks (CICN) (pp. 1111-1117). IEEE.

[38] Dingyuan Liu. Measuring the Sensitivity of Local Skill Structures to AI Substitution Risks Based on Occupational Task Decomposition. Socio-Economic Statistics Research (2025), Vol. 6, Issue 2: 177-184

[39] Hong, Y. (2026). Research on Warehouse Capacity Optimization Methods Based on Predictive Modeling. Engineering Advances, 6(1).

[40] Yu, X. (2026). Strategy Models and Practical Research of Growth Marketing under the Background of Digital Transformation.