Sökning: "trading machine"

Visar resultat 1 - 5 av 78 uppsatser innehållade orden trading machine.

1. 1. Dynamik och tillförlighet i finansiell prognostisering : En analys av djupinlärningsmodeller och deras reaktion på marknadsmanipulation

   M1-uppsats, KTH/Hälsoinformatik och logistik

   Författare :Aya Zawahri; Nanci Ibrahim; [2024]
   Nyckelord :LOB; market manipulation; spoofing; layering; DeepLOB; DeepLOB-Attention; TCN; DeepLOB-seq2seq; DTNN; ITCH; parsing.; LOB; marknadsmanipulation; spoofing; layering; DeepLOB; DeepLOB-Attention; TCN; DeepLOB-seq2seq; DTNN; ITCH; parsing.;

   Sammanfattning : Under åren har intensiv forskning pågått för att förbättra maskininlärningsmodellers förmåga att förutse marknadsrörelser. Trots detta har det, under finanshistorien, inträffat flera händelser, såsom "Flash-crash", som har påverkat marknaden och haft dramatiska konsekvenser för prisrörelserna. LÄS MER

3. 2. Predictive Modeling and Statistical Inference for CTA returns : A Hidden Markov Approach with Sparse Logistic Regression

   Master-uppsats, Umeå universitet/Institutionen för matematik och matematisk statistik

   Författare :Oskar Fransson; [2023]
   Nyckelord :Probability theory; Statistical inference; finance; CTA; managed futures; machine learning; statistical learning; stochastic process; sparse logistic regression; Markov Chain Monte Carlo; Hidden Markov model;

   Sammanfattning : This thesis focuses on predicting trends in Commodity Trading Advisors (CTAs), also known as trend-following hedge funds. The paper applies a Hidden Markov Model (HMM) for classifying trends. Additionally, by incorporating additional features, a regularized logistic regression model is used to enhance prediction capability. LÄS MER

4. 3. Predicting the Movement of the S&P 500 Index using Machine Learning

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

   Författare :Bakary Bah; [2023]
   Nyckelord :Machine Learning; S P 500 Index; Random Forest; Logistic Regression; Business and Economics;

   Sammanfattning : Predicting the stock market has been a longstanding topic of interest in financial research. It is regarded as a highly challenging but important task given the vital role the financial markets play in shaping the global economies. In this thesis, the goal is to predict the movement of the S&P 500 Index using machine learning methods. LÄS MER

5. 4. Can Machine Be a Good Stock Picker?: Bridging the Gap between Fundamental Data and Machine Learning

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

   Författare :Tomoya Narita; Povilas Stankevicius; [2023]
   Nyckelord :Machine Learning; XGBoost; Relative Valuation; Convergence Trade;

   Sammanfattning : We investigate the efficacy of historical accounting data and consensus forecasts for relative valuation of stocks, employing tree-based machine learning methods. We run an XGBoost model for monthly cross-sections of financial and pricing data of US equities from 1984 to 2021. LÄS MER

7. 5. CryptoCurrency Time Series analysis : Comparative analysis between LSTM and BART Algorithm

   Uppsats för yrkesexamina på grundnivå, Blekinge Tekniska Högskola/Institutionen för datavetenskap

   Författare :Lakshmi Vyshnavi Nerella; Chiranjeevi Ponnada; [2023]
   Nyckelord :;

   Sammanfattning : Background: Cryptocurrency is an innovative digital or virtual form of money thatuses cryptographic techniques for secured financial transactions within a decentralized structure. Due to its high volatility and susceptibility to external factors, itis difficult to understand its behavior which makes accurate predictions challengingfor the investors who are trying to forecast price changes and make profitable investments. LÄS MER