DUCKQUANT / THE QUANT & AI DIRECTORY
14,444 resources, ranked by in-directory PageRank
Showing 7,129–7,164 of 14,444 resources
Modelling Contentedness of Firms in Financial Markets with Heterogeneous Agents
accompanying materials for book on top of basic machine learning models i.e. nlp/reinforcement learning/supervised & unsupervised learning it covers wider…
Correlation between mutual fund investment decision and earning call transcripts
Estimate Value-at-Risk for market risk management using Keras and TensorFlow
Finance and Risk Engineering (NYU Tandon)
Machine learning algo to detect anomaly in equities data. Uses sklearn model and price/volume based technical signals as features using library. Opensourced by…
Insight into a new founder to make data-driven investment decisions
Risk measures and factors for alternative and responsible investments
Stanford Advanced Financial Technologies Laboratory
Identify social/historical cues for short term stock movement. Sklearn SVM model is used and good visualization coded in matplotlib
Finance risk engagement course resources
Riskiness of portfolios and assets
CEU python for finance course material
Efficient financial risk estimation via computer experiment design (regression variance-reduced sampling)
Valuation of Vanilla and Exotic option strategies (Butterfly, Risk Reversal etc.) with widget animations
Courant Institute of Mathematical Sciences, New York University
Mixture models and stock trading
Mixture models to predict market bottoms and regime changes based on a seminar given to quantinsti in 2017 and summary and video is .…
repo for article not very scalable and not maintained
A futures trend following portfolio investment strategy
list of technical indicators implemented in c#. Full list and explanation available . This list contains several indicators that ta-lib does not cover
Relative importance of each component of the OLMAR algorithm
Variational Reccurrent Autoencoder for Embedding stocks to vectors based on the price history
sentiment analysis baed on twitter data. Relevant topics include data cleaning/tokenization/data aggregation using mangodb etc
Deep reinforcement learning for financial trading using and on FX dataset (EURUSD) not actively maintained
code to predict crypto prices using machine learning models. Two models used here tensorflow DNNClassifier and sklearn randomforest. Exposes the functionality…
Building an Agent to Trade with Reinforcement Learning
Hedging portfolios with reinforcement learning
Reinforcement Learning for Portfolio Management
Finding pairs with cluster analysis
Curating quantitative finance papers using machine learning
Neural networks to predict stock prices
Explore this resource at its source website for documentation and current information.
Analysis of luxury watch data to classify whether a certain model is likely to be over-or undervalued
Exercises to book advances in financial machine learning . Relevant topics include data cleaning and outlier detection (using MAD)
Institutional-only crypto exchange backed by major Wall Street firms, offering non-custodial spot trading.
