Daniblit / Ensemble-Predictive-Model-Forecasting-AMGEN-stock-price-at-year-end-31s
The basis of this project involves analyzing Amgen future profitability based on its current business environment and financial performance. Technical Analysis, on the other hand, includes reading the charts and using statistical figures to identify the trends in the stock market. The dataset used for this analysis was downloaded from Yahoo fina…
☆11Updated 5 years ago
Alternatives and similar repositories for Ensemble-Predictive-Model-Forecasting-AMGEN-stock-price-at-year-end-31s:
Users that are interested in Ensemble-Predictive-Model-Forecasting-AMGEN-stock-price-at-year-end-31s are comparing it to the libraries listed below
- Market Risk Management with Time Series Prediction of Stock Market Trends using ARMA, ARIMA, GARCH regression models and RNN for time ser…☆21Updated 7 years ago
- This is a sentiment trading strategy, written in Python, and applying NLP on 10-K's from the SEC EDGAR database.☆10Updated 3 years ago
- Compilation of technical analysis tools (EMA, Bollinger bands), fundamental analysis, machine learning models (LSTM, Random forest, ARIMA…☆13Updated 3 years ago
- Stock closing and opening forecasting using Deep neural network and LSTM(technical indicators included)☆20Updated 7 years ago
- Jupyter Notebooks Collection for Learning Time Series Models☆69Updated 5 years ago
- Stock markets are an essential component of the economy. Their prediction naturally arouses afascination in the academic and financial w…☆21Updated 3 years ago
- Stock Price prediction using news data. The datasets used consists news and stock price data from 2008 to 2016. The polarity(Subjectivity…☆48Updated 7 years ago
- Development space for PhD in Finance☆33Updated 5 years ago
- keywords - Kmeans Clustering, Tsne, PCA, Indian Stocks, Johansen test☆31Updated 6 years ago
- A dataset of financial news is used to fine-tune BERT in order to extract investment opportunities.☆25Updated 3 years ago
- This tool is developed to scrape twitter data, process the data, and then create either an unsupervised network to identify interesting p…☆17Updated last year
- Pythonic S&P 500 Index Prediction (Portfolio Project at DSR)☆26Updated 10 years ago
- In this project, we implement and compare the performance of several machine learning and deep learning algorithms in predicting the US s…☆54Updated 4 years ago
- Project description: https://medium.com/@tzhangwps/measuring-financial-turbulence-and-systemic-risk-9d9688f6eec1?source=friends_link&sk=1…☆26Updated last month
- Capital Asset Pricing Model implementation in python to analyze stock risk and return.☆26Updated 3 years ago
- This Jupyter Notebook illustrates investment portfolio optimization in Modern Portfolio Theory.☆10Updated 3 years ago
- The S&P 500 Market Index is analysed using popular statistical models such as SARIMA, ETS and GARCH. Additionally, a powerful open source…☆26Updated 4 years ago
- —Machine Learning; stock prediction; Deep Learning; styling; LSTM(Long Short Term Memory)☆9Updated 7 years ago
- Source code for Multicriteria Portfolio Construction with Python☆30Updated 3 years ago
- Moody's Bond Rating Classifier and USPHCI Economic Activity Forecast Modeling☆18Updated 5 years ago
- Algorithmic approach to analysing performance and the similarity of different stocks in S&P 500 via cluster analysis.☆9Updated 8 years ago
- Class materials of Credit Risk Management taught by prof. Ed Hayes☆11Updated 7 years ago
- Stock market data can be interesting to analyze and as a further incentive, strong predictive models can have large financial payoff. The…☆23Updated 6 years ago
- Code for Machine Learning for Algorithmic Trading, 2nd edition.☆18Updated 2 years ago
- An investment portfolio of stocks is created using Long Short-Term Memory (LSTM) stock price prediction and optimized weights. The perfor…☆34Updated last year
- Time Series forecasting using Seasonal ARIMA & Prophet. Applied statistical tests like Augmented Dickey–Fuller test to check stationary o…☆26Updated 3 years ago
- Visualising correlations between different ETFs using network analytics and Plotly☆34Updated 2 years ago
- Improve S&P 500 stock price prediction (random forest and gradient boosting trees) with time series similarity measurements: DTW, SAX, co…☆98Updated 3 years ago
- Calculate technical indicators from historical stock data Create features and targets out of the historical stock data. Prepare features …☆31Updated 5 years ago
- This project explores stock trading modelling with the use recurrent neural network (RNN) with long-short term memory (LSTM) architecture…☆26Updated 5 years ago