Pinned Repositories
aave_liquidations
AdaptiveEnbMIMOCQR
adaptivegp
Fully nonstationary, heteroscedastic GP for Matlab
Advanced-Cpp-And-Modern-Design
My solutions to the "Advanced C++ and Modern Design" course offered by Baruch College.
allocator
A set of memory allocators for use with the C++ Standard Template Library
AllocatorBuilder
Policy Based C++ Allocator Library
atomic_patterns
Common atomic patterns
Awesome-Quant-Machine-Learning-Trading
Quant/Algorithm trading resources with an emphasis on Machine Learning
Waiting_Times_and_Number_of_Directional_Changes
Code and experiments described in the "Waiting Times and Number of Directional Changes in Intrinsic Time framework" paper (to be published)
goldstar111's Repositories
goldstar111/AdaptiveEnbMIMOCQR
goldstar111/Advanced-Cpp-And-Modern-Design
My solutions to the "Advanced C++ and Modern Design" course offered by Baruch College.
goldstar111/aws-sa-associate-saac02
Course Files for AWS Certified Solutions Architect Certification Course (SAAC02) - Adrian Cantrill
goldstar111/cookstock
Mark Minervini's volatility contraction pattern detection, stage 2 template searching
goldstar111/EnbPI
Code for ICML 2021 Oral Paper: Conformal Prediction Interval for Dynamic Time-Series AND the extended version under review by the Journal of Machine Learning Research
goldstar111/EPI-to-LC
Mappings of problems from the book Elements of Programming Interviews (EPI) to Leetcode
goldstar111/fractal-interpolation
Analysis of Fractal Interpolation Functions for Large Datasets
goldstar111/gann-swing
Python module to calculate Gann swings
goldstar111/gasoline-trading
System for trading RBOB Gasoline futures contracts based on CFTC data.
goldstar111/High-Frequency-Trading-Model-with-IB
A high-frequency trading model using Interactive Brokers API with pairs and mean-reversion in Python
goldstar111/ib_insync
Python sync/async framework for Interactive Brokers API
goldstar111/ibkr-options-volatility-trading
goldstar111/ImprovedConformalizedQuantileRegression
goldstar111/jumpdiff
JumpDiff: Non-parametric estimator for Jump-diffusion processes for Python
goldstar111/magic-trace
Easy Intel Processor Trace Visualizer
goldstar111/MambaStock
MambaStock: Selective state space model for stock prediction
goldstar111/MFDFA
Multifractal Detrended Fluctuation Analysis in Python
goldstar111/Multifractality
Multi-Fractal Detrended Fluctuation Analysis (MFDFA) for fractal and long-range correlation analysis of time series
goldstar111/notebooks
Analysis on systematic trading strategies (e.g., trend-following, carry and mean-reversion). The result is regularly updated.
goldstar111/pykan
Kolmogorov Arnold Networks
goldstar111/qdownload
IQFeed CSV market data download tool
goldstar111/relative-strength
IBD Style Relative Strength Percentile Ranking of Stocks (i.e. 0-100 Score).
goldstar111/RelativeRotationGraphs
goldstar111/RRGPy
RRGPy is a Python script for displaying Relative Rotation Graph.
goldstar111/Rule-based-forex-trading-system
goldstar111/stockpredictionai
In this noteboook I will create a complete process for predicting stock price movements. Follow along and we will achieve some pretty good results. For that purpose we will use a Generative Adversarial Network (GAN) with LSTM, a type of Recurrent Neural Network, as generator, and a Convolutional Neural Network, CNN, as a discriminator.
goldstar111/trade-frame
C++ 17 based library (with sample applications) for testing equities, futures, etfs & options based automated trading ideas using DTN IQFeed real time data feed and Interactive Brokers (IB TWS API) for trade execution. Some support for Alpaca & Phemex. Notifications via Telegram [irc: Libra #tradeframe ]
goldstar111/Transformers_Are_What_You_Dont_Need
The best repository showing why transformers might not be the answer for time series forecasting and showcasing the best SOTA non transformer models.
goldstar111/vcp_screener.github.io
A program screens stocks following Mark Minervini's strategy.
goldstar111/volgpt
Explores use of text-to-text LLMs for vol prediction, something normally done with number-to-number stochastic volatility model such as the MSM or Heston, with high frequency data. Implementation of nanoGPT, training on high-frequency tick data for JPM and AAPL.