Topic: time-series-econometrics Goto Github
Some thing interesting about time-series-econometrics
Some thing interesting about time-series-econometrics
time-series-econometrics,Predictive Modelling of Time Series Data using LSTM RNNs
User: archana1998
time-series-econometrics,
User: benjaminbluhm
time-series-econometrics,Calibrate and simulate linear propagator models for the price impact of an extrinsic order flow.
User: felixpatzelt
time-series-econometrics,Testing for bubbles with R
User: itamarcaspi
Home Page: https://itamarcaspi.github.io/rtadfr/
time-series-econometrics,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.
User: jsos17
time-series-econometrics,Code lines to download the updated list of R packages I've used.
User: leomariano
time-series-econometrics,Autoregressor: simple and robust time series model selection
User: martinlyngerasmussen
Home Page: https://github.com/martinlyngerasmussen/auto_regressor
time-series-econometrics,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.
User: nutansahoo
time-series-econometrics,Research Project on "Time Series Analysis and Forecasting"
User: parthsompura
Home Page: https://github.com/ParthPathak27/
time-series-econometrics,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 [email protected]
User: soms98
time-series-econometrics,A framework for detecting misreported returns in hedge funds.
User: tommasobelluzzo
time-series-econometrics,A framework for historical volatility estimation and analysis.
User: tommasobelluzzo
time-series-econometrics,A framework for systemic risk valuation and analysis.
User: tommasobelluzzo
time-series-econometrics,A non-commercial research project - time series analysis for GDP and consumption in Austria (1970-2020)
User: vsevolodkotenyov
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