time-series-econometrics

There are 15 repositories under time-series-econometrics topic.

  • TommasoBelluzzo/SystemicRisk

    A framework for financial systemic risk valuation and analysis.

    Language:MATLAB156201576

  • TommasoBelluzzo/HistoricalVolatility

    A framework for historical volatility estimation and analysis.

    Language:MATLAB345216

  • felixpatzelt/priceprop

    Calibrate and simulate linear propagator models for the price impact of an extrinsic order flow.

    Language:Python23309

  • itamarcaspi/rtadfr

    Testing for bubbles with R

    Language:R193311

  • TommasoBelluzzo/HFMRD

    A framework for detecting misreported returns in hedge funds.

    Language:MATLAB163113

  • lnsongxf/fecon235

    Computational data tools for financial economics. Keywords: Jupyter notebook pandas Federal Reserve FRED Ferbus GDP CPI PCE inflation unemployment wage income debt Case-Shiller housing asset portfolio equities SPX bonds TIPS rates currency FX euro EUR USD JPY yen XAU gold Brent WTI oil Holt-Winters time-series forecasting statistics econometrics

    Language:Jupyter Notebook13406

  • soms98/Stock-Price-Prediction-Time-Series-LSTM-Model-Keras-Tensorflow

    This is a model that has been trained on historical data obtained from Yahoo Finance. The data set comprises of all data records starting from the launch date of this stock in India (1996). This model aims to pick up key trends in the stock price fluctuations based on Time Series mapping. It is able to render predictions for the upcoming time period. The accuracy as obtained on the training data-set is about 90 percent and it successfully demonstrates key trends. It can be simulated on any stock in the market provided their historical data is made available. (One could use the yfinance API or download manually). Keras is used extensively along with Tensorflow for training. The model features 100 epochs of Base size 64. The training time depends on the hardware being used by the user. It is advisable to be performed on Google Colaboratory. For any issues/suggestions write to somshankar97@gmail.com

    Language:Jupyter Notebook91010

  • archana1998/predictive-modelling

    Predictive Modelling of Time Series Data using LSTM RNNs

    Language:Python3100

  • parthsompura/Time-Series-Analysis-and-Forecasting

    Research Project on "Time Series Analysis and Forecasting"

    Language:Jupyter Notebook3203

  • benjaminbluhm/spark_parallel_forecasting

    Language:TeX2201

  • vsevolodkotenyov/time_series_GDP

    A non-commercial research project - time series analysis for GDP and consumption in Austria (1970-2020)

    Language:Jupyter Notebook2100

  • Jsos17/A_Vector_Autoregressive_Model

    Building a vector autoregressive model with R. My coursework for the course Time Series Analysis II (offered by University of Helsinki's Master's Programme in Mathematics and Statistics), spring 2020.

    Language:TeX1101

  • martinlyngerasmussen/auto_regressor

    Autoregressor: simple and robust time series model selection

    Language:Jupyter Notebook1100

  • nutansahoo/Analysing-and-Predicting-Copper-Prices

    Annual Copper Prices data from the year 1800 to 1997 was downloaded from the time series data library created by Rob Hyndman. I aim to analyse this uni-variate time series data and fit an ARIMA model to it.

    Language:R1100

  • LeoMariano/Getting-R-started

    Code lines to download the updated list of R packages I've used.

    Language:R0100