Sökning: "Intra-day Data"

Visar resultat 1 - 5 av 8 uppsatser innehållade orden Intra-day Data.

  1. 1. Volatility & The Black Swan : Investigation of Univariate ARCH-models, HARRV and Implied Volatility in Nasdaq100 amid Covid19

    Master-uppsats, Uppsala universitet/Nationalekonomiska institutionen

    Författare :Karl Tingstedt; [2022]
    Nyckelord :SV; ARCH; GARCH; TARCH; EGARCH; HARRV; IV; RV; Integrated Volatility; TINA;

    Sammanfattning : Covid19 hit the world’s financial markets by surprise in March 2020 and ensuing volatility marked an end to the prior low-volatility environment. This Black Swan engendered numerous publications establishing how the equity market responded to the exogenous shock. LÄS MER

  3. 2. Not Just Noise: An Empirical Study of Irrational Noise Trading and its Role in Financial Markets

    D-uppsats, Handelshögskolan i Stockholm/Institutionen för finansiell ekonomi

    Författare :Valter Ehrström; Linus Sigurdson; [2022]
    Nyckelord :Microstructure theory; Noise trading; Retail trading; Sports; Transaction costs;

    Sammanfattning : This paper explores the role of irrational 'noise' traders in financial markets. Theory suggests that a lower share of irrational or uninformed trading in the market should lead to higher adverse selection costs, and that irrational trading should be more susceptible to exogenous, non-economic events that capture traders' time and attention. LÄS MER

  4. 3. Tick data clustering analysis establishing support and resistance levels of the EUR-USD exchange market

    Master-uppsats, Lunds universitet/Matematisk statistik

    Författare :Karl Tengelin; [2020]
    Nyckelord :Tick data; Support-and resistance levels; Clustering methods; Gaussian mixture model; Kmeans; EUR-USD exchange rates; Clustering performance metrics; Market activity; Mathematics and Statistics;

    Sammanfattning : Our aim is to use clustering algorithms in order to compute support and resistance levels within an intra-day trading setting. To achieve this we use a tick data set from the EUR-USD exchange market during 2019 as a measure of market activity. LÄS MER

  5. 4. Predicting Exchange Rate Value-at-Risk and Expected Shortfall: A Neural Network Approach

    Magister-uppsats, Lunds universitet/Nationalekonomiska institutionen

    Författare :Anna Bijelic; Tilila Ouijjane; [2019]
    Nyckelord :Value-at-Risk; Expected Shortfall; Recurrent Neural Networks; GRU; GARCH 1; 1 ; Exchange Rate Volatility; Intra-day Data; Business and Economics;

    Sammanfattning : On the basis of the recommendation of the Basel Committee on Banking Supervision to transition from Value-at-Risk (VaR) to Expected Shortfall (ES) in determining market risk capital, this paper attempts to investigate whether a Recurrent Neural Network provides more accurate VaR and ES predictions of the EUR/USD exchange rate compared to the conventional GARCH(1,1) model. A number of previous studies has confirmed the forecasting ability of a plain vanilla Feedforward Neural Network over traditional statistical models. LÄS MER

  7. 5. Online intra-day portfolio optimization using regime based models

    Uppsats för yrkesexamina på avancerad nivå, Lunds universitet/Matematisk statistik

    Författare :Sara Hafström Fremlin; [2019]
    Nyckelord :Multi-period portfolio selection; Model predictive control; Hidden Markov model; Mathematics and Statistics;

    Sammanfattning : In this thesis model predictive control (MPC) is used to dynamically optimize a portfolio where the data is sampled every 5 minutes. Previous research has shown how MPC optimization applied to daily sampled financial data can generate a portfolio that exceeds the value of standard portfolio strategies such as Strategic asset allocation. LÄS MER