Sökning: "Financial memory"

Visar resultat 1 - 5 av 42 uppsatser innehållade orden Financial memory.

  1. 1. Explainable Artificial Intelligence and its Applications in Behavioural Credit Scoring

    Master-uppsats, Stockholms universitet/Institutionen för data- och systemvetenskap

    Författare :Robert Iain Salter; [2023]
    Nyckelord :Behavioural Credit Scoring; Deep Learning; Machine Learning; Long Short-Term Memory; Default Prediction;

    Sammanfattning : Credit scoring is critical for banks to evaluate new loan applications and monitor existing customers. Machine learning has been extensively researched for this case; however, the adoption of machine learning methods is minimal in financial risk management. LÄS MER

  3. 2. Aktiemarknadsprognoser: En jämförande studie av LSTM- och SVR-modeller med olika dataset och epoker

    Kandidat-uppsats, Malmö universitet/Fakulteten för teknik och samhälle (TS)

    Författare :Mads Nørklit Johansen; Jagtej Sidhu; [2023]
    Nyckelord :Stock Market Prediction; Long-Short Term Memory; Support Vector Regression; Prediction Accuracy; Financial Investments;

    Sammanfattning : Predicting stock market trends is a complex task due to the inherent volatility and unpredictability of financial markets. Nevertheless, accurate forecasts are of critical importance to investors, financial analysts, and stakeholders, as they directly inform decision-making processes and risk management strategies associated with financial investments. LÄS MER

  4. 3. Modelling Proxy Credit Cruves Using Recurrent Neural Networks

    Master-uppsats, KTH/Matematisk statistik

    Författare :Lucas Fageräng; Hugo Thoursie; [2023]
    Nyckelord :Deep Neural Networks; Credit Risk; Financial Modelling; LSTM; Credit Default Swaps; Credit Valuation Adjustment; Djupa Neurala Nätverk; Kreditrisk; Finansiell Modellering; LSTM; Kreditswappar; Kreditvärderingsjustering;

    Sammanfattning : Since the global financial crisis of 2008, regulatory bodies worldwide have implementedincreasingly stringent requirements for measuring and pricing default risk in financialderivatives. Counterparty Credit Risk (CCR) serves as the measure for default risk infinancial derivatives, and Credit Valuation Adjustment (CVA) is the pricing method used toincorporate this default risk into derivatives prices. LÄS MER

  5. 4. Artificial Neural Networks for Financial Time Series Prediction

    Master-uppsats, Stockholms universitet/Institutionen för data- och systemvetenskap

    Författare :Dana Malas; [2023]
    Nyckelord :artificial neural networks; time series analysis; deep learning; finance; long short-term memory; simple moving average;

    Sammanfattning : Financial market forecasting is a challenging and complex task due to the sensitivity of the market to various factors such as political, economic, and social factors. However, recent advances in machine learning and computation technology have led to an increased interest in using deep learning for forecasting financial data. LÄS MER

  7. 5. Risks, Concerns and Performance of AI Tools on the Stock Market

    Kandidat-uppsats, Blekinge Tekniska Högskola/Fakulteten för datavetenskaper

    Författare :Albin Södervall; David Värmfors; [2023]
    Nyckelord :Artificial intelligence; stock market; issues; problems; risk;

    Sammanfattning : This thesis investigates the impact of artificial intelligence (AI) tools on the stock market, focusing on its effects on risk, performance, and concerns. Through an analysis of existing literature and an experiment, this study aims to provide insights into the potential benefits and drawbacks of using AI in stock market trading. LÄS MER