Sökning: "long-only"

Visar resultat 1 - 5 av 15 uppsatser innehållade ordet long-only.

1. 1. A Quantitative Framework for Constructing a Multi-Asset CTA with a Momentum-Based Approach

   Uppsats för yrkesexamina på avancerad nivå, Uppsala universitet/Datalogi

   Författare :Rebecca Fällström; [2023]
   Nyckelord :Commodity trading advisors; CTA; trend-following; momentum strategies; risk parity; equally weighted; Markowitz weights; optimization;

   Sammanfattning : Commodity Trading Advisors (CTAs) have gained popularity due to their abilities to generate an absolute return strategy. Little is known about how CTAs work and what variables are important to tune in order to create a profitable strategy. LÄS MER

3. 2. LSTM-based Directional Stock Price Forecasting for Intraday Quantitative Trading

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

   Författare :Isabella Mustén Ross; [2023]
   Nyckelord :Deep Learning; Long-Short-Term-Memory LSTM ; ARIMA; Financial Time Series Forecasting; Algorithmic Trading; Intraday Trading; Stock Prediction; Djupinlärning; LSTM; ARIMA; finansiella tidsserier; algoritmisk aktiehandel; intradagshandel; aktieprediktion;

   Sammanfattning : Deep learning techniques have exhibited remarkable capabilities in capturing nonlinear patterns and dependencies in time series data. Therefore, this study investigates the application of the Long-Short-Term-Memory (LSTM) algorithm for stock price prediction in intraday quantitative trading using Swedish stocks in the OMXS30 index from February 28, 2013, to March 1, 2023. LÄS MER

4. 3. Stockholm Stock Exchange and Environmental Rating – A Multifactor Analysis

   Master-uppsats, Göteborgs universitet/Graduate School

   Författare :Carl Helldén; Julia Lamers; [2022-06-29]
   Nyckelord :ESG; Environmental; asset pricing models; screening strategies;

   Sammanfattning : The thesis investigates if investors can generate positive abnormal performance by investing in Environmental high-rated stocks on the Stockholm stock exchange based on three screening strategies; positive, negative and best-in-class for value-weighted, long-only and long-short portfolios. The sample is between 2010-2020, using CAPM, Fama-French three factor model and Carhart four factor model. LÄS MER

5. 4. Resource-efficient and fast Point-in-Time joins for Apache Spark : Optimization of time travel operations for the creation of machine learning training datasets

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

   Författare :Axel Pettersson; [2022]
   Nyckelord :Apache Spark; Point-in-Time; ASOF; Join; Optimizations; Time travel; Apache Spark; Point-in-Time; ASOF; Join; Optimeringar; Tidsresning;

   Sammanfattning : A scenario in which modern machine learning models are trained is to make use of past data to be able to make predictions about the future. When working with multiple structured and time-labeled datasets, it has become a more common practice to make use of a join operator called the Point-in-Time join, or PIT join, to construct these datasets. LÄS MER

7. 5. Using Machine Learning to Predict Aggregate Excess Returns

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

   Författare :Erik Jonsson; Sebastian Gierlowski Carling; [2021]
   Nyckelord :Equity premium; Machine learning; Non-linear models; Penalized linear models; Prediction;

   Sammanfattning : In this paper we examine whether standard linear regression and machine learning tools can be used to predict the time series of total returns in excess of the risk-free rate on the S&P500 and FTSE100 indices. We have virtually no success in predicting monthly returns. However, we do have some success in predicting annual returns. LÄS MER