kenluck2001 / pySmoothLinks
A unique time series library in Python that consists of Kalman filters (discrete, extended, and unscented), online ARIMA, and time difference model.
☆32Updated 7 years ago
Alternatives and similar repositories for pySmooth
Users that are interested in pySmooth are comparing it to the libraries listed below
Sorting:
- Evaluation of Hybrid MODWT-MARS framework for financial time series forecasting☆18Updated 11 months ago
- Dynamic lead/lag inference for time series☆17Updated 6 years ago
- Python for Random Matrix Theory: cleaning schemes for noisy correlation matrices.☆75Updated 7 years ago
- Multivariate Adaptive Regression Splines for Time Series Prediction☆18Updated 2 years ago
- Implementation of Monte Carlo Optimization Selection from the paper "A Robust Estimator of the Efficient Frontier"☆58Updated 2 years ago
- Python Copula Module☆43Updated 2 years ago
- WATTNet: Learning to Trade FX with Hierarchical Spatio-Temporal Representations of Highly Multivariate Time Series☆73Updated 5 years ago
- Estimation of the Covariance Matrix - linear and nonlinear shrinkage☆23Updated 3 years ago
- As described in Advances of Machine Learning by Marcos Prado.☆121Updated 2 years ago
- Necessary code to reproduce the experiment in "Mitigating Overfitting with Generative Adversarial Networks"☆37Updated 2 years ago
- Estimation of the lead-lag parameter from non-synchronous data.☆128Updated 4 months ago
- Code and examples for the project on risk-constrained Kelly gambling☆27Updated 4 years ago
- Talk Materials for "Convex Optimization for Finance"☆28Updated 2 years ago
- ☆27Updated 6 years ago
- (Work In Progress) Implementation of "Financial Time Series Prediction Using Deep Learning"☆16Updated 7 years ago
- Code examples for pyFTS☆51Updated 5 years ago
- Source code for Deep Fundamental Factor Models, https://arxiv.org/abs/1903.07677☆64Updated 3 years ago
- Implementation of Log Gaussian Cox Process in Python for Changepoint Detection using GPFlow☆31Updated 2 years ago
- Rapid large-scale fractional differencing with NVIDIA RAPIDS and GPU to minimize memory loss while making a time series stationary. 6x-40…☆57Updated 5 years ago
- This is a non-official implementation of the trend labeling method proposed in the paper "A Labeling Method for Financial Time Series Pre…☆49Updated 7 months ago
- Random Forest-based "Correlation" measures☆15Updated 3 years ago
- Improve S&P 500 stock price prediction (random forest and gradient boosting trees) with time series similarity measurements: DTW, SAX, co…☆99Updated 3 years ago
- Python code for Bayesian Conditional Cointegration☆18Updated 8 years ago
- Unsupervised Learning to Market Behavior Forecasting Example☆42Updated 5 years ago
- Advancing in Financial Machine Learning☆16Updated 5 years ago
- Non-parametric method for estimating regime change in bivariate time series setting.☆14Updated 8 years ago
- Python Kalman filters vectorized as Single Instruction, Multiple Data☆187Updated last year
- SdePy: Numerical Integration of Ito Stochastic Differential Equations☆43Updated 4 years ago
- L1 Trend Filtering☆19Updated last year
- DATA-AIDED PAIRS TRADING VIA LEARNED KALMAN WITH BOLLINGER BANDS☆35Updated 2 years ago