Sökning: "Computational Economics"

Visar resultat 1 - 5 av 25 uppsatser innehållade orden Computational Economics.

  1. 1. Current state of AI Adoption in Swedish Banks: Rationales, Challenges, and Lessons Learned

    Magister-uppsats, Lunds universitet/Företagsekonomiska institutionen

    Författare :Tedo Sanikidze; Alexander Starck; [2023]
    Nyckelord :Artificial Intelligence AI AI Integration AI Applications AI Adoption Motivations AI Integration Challenges Insights from AI Adoption AI in Banking Swedish Banking Sector.; Business and Economics;

    Sammanfattning : The field of Artificial Intelligence (AI) continues to revolutionise numerous sectors, and the banking industry is no different. This study investigates the rationales, challenges, and lessons learned from AI incorporation within Sweden's banking system. LÄS MER

  3. 2. Data Misinterpretation: A Consequence of Data Structure? : A Cognitive Imperfection and Its Economic Implications

    Kandidat-uppsats, Jönköping University/Internationella Handelshögskolan

    Författare :Balázs Faragó; Joakim Ben David; [2023]
    Nyckelord :Data Misinterpretation; Behavioural Economics; Policy Decision-Making; Cognitive Bias; Convex Hull; Agent-Based Computational Economics;

    Sammanfattning : This study examines the claim that individuals misinterpret the mean of a dataset (displayed as a scatterplot) more when the convex hull of the dataset is less representative of the data. In addition, this study also tests whether outliers in the data can predict the magnitude of error that individuals make in interpreting the mean of the dataset. LÄS MER

  4. 3. Forecasting copper price using VAR and the XGBoost model: an experiment with a relatively small dataset

    Magister-uppsats, Lunds universitet/Nationalekonomiska institutionen; Lunds universitet/Statistiska institutionen

    Författare :Juanli Hu; [2023]
    Nyckelord :copper price; Vector autoregressive model; XGBoost; Time series; Business and Economics;

    Sammanfattning : Given the importance of copper prices to investors, governments, and policymakers, this paper investigates short-term price predictability using VAR and XGBoost models. All models are trained with historical data from November 2021 to December 2022 and using MSE, RMSE and MAE for evaluating the model performance. LÄS MER

  5. 4. Designing Effective Derivative Line Filters: Utilizing convolution to extract extra information

    Master-uppsats, KTH/Matematik (Avd.)

    Författare :Gustaf Lorentzon; [2023]
    Nyckelord :Computational Fluid Dynamics; Convolution Filters; Convolution Kernels; Derivatives; Extracting Extra Accuracy; Filtration; Post-processing; Smoothness-Increasing Accuracy-Conserving; Signal-processing; Visualization; Vorticity; Beräkningsbaserad Strömningsdynamik; Faltningsfilter; Faltningskärnor; Derivator; Extrahering av Extra Noggrannhet; Filtrering; Efterbehandling; Kontinuitetsökande; Noggrannhetsbevarande; Signalbehandling; Visualisering; Vorticitet;

    Sammanfattning : The ability to generate accurate approximations of derivatives holds significant importance in numerous scientific fields, including chemistry, economics and fluid mechanics. This thesis is centred around extracting hidden information in data using Smoothness-Increasing Accuracy-Conserving (SIAC) filters. LÄS MER

  7. 5. Multi Agent Reinforcement Learning for Game Theory : Financial Graphs

    Master-uppsats, KTH/Skolan för elektroteknik och datavetenskap (EECS)

    Författare :Bryan Yu; [2021]
    Nyckelord :Multi-Agent Reinforcement Learning; Reinforcement Learning; Game Theory; Financial Networks; Financial Graphs; Machine Learning; Financial Graphs; Computational Economics; Multi-Agent Reinforcement Learning; Reinforcement Learning; Game Theory; Financial Networks; Financial Graphs; Machine Learning; Financial Graphs; Computational Economics;

    Sammanfattning : We present the rich research potential at the union of multi agent reinforcement learning (MARL), game theory, and financial graphs. We demonstrate how multiple game theoretic scenarios arise in three node financial graphs with minor modifications. We highlight six scenarios used in this study. LÄS MER