This project is about float, fixed and mixed exchange rates differences, you can expect: working on the real data (from fxtop.com) analysis period selection data analysis (realizations plots) cointegration testing (two-step Engle-Granger procedure (1987)) statistical tests (Augmented Dicky-Fuller, Breusch-Godfrey, F, Ljung-Box) model selection (information criteria) Markov switching modelling hypotheses verification (rate swings) inference and interpretations quality paper-style report in Polish GitHub repository

This project is about volatility models comparison, you can expect: working on the real market data (from stooq.pl) time series data EDA (logarithmic returns transform, realization plots, ACFs, PACFs, descriptive statistics) statistical tests (ARCH LM, Jarque-Bera) GARCH modelling with prior assumptions about epsilon distribution (hypotheses) 4 GARCH models (standard, exponential, threshold, component) with 4 different epsilon distributions each (normal, t-student, skewed t-student, generalized error) 3 naive models (random walk, historical average, moving average) 9 performance metrics (ME, MAE, RMSE, AMAPE, TIC, MME(U), MME(O), DCP, DCPU) quality paper-style report in Polish GitHub repository

This project is about hedonic price model for different price distribution quantiles (German real estate) estimation, you can expect: short data analysis (dependent variable distribution and its moments) data transforms (logarithm, ordinal, nominal transforms) standard hedonic price model estimation (OLS) statistical tests (Jarque-Bera, White) outliers detection (Cook’s distance, standarized and studentized residuals) quantiles hedonic price models estimation (with bootstraped covariance matrix - 999 replications) extremely interesting Beta coefficients estimates vs price quantiles plots with interpretation and inference quality paper-style report in Polish GitHub repository

This project is about boosting Neural Networks with PCA (other ML algorithms as benchmarks), you can expect: data preparation (renaming labels, balance check, standarization) Random Forest based data imputation algorithm development n-Fold Cross Validation study Machine Learning algorithms (Random Forest, XGBoost with hiperparameters optimization) 6 feature selection methods to spot non-significant features (RF importance, Mutual Information, Spearman correlation between features and with target, General to Specific econometrics procedure, Lasso logistic regression) Neural Networks development (architecture, optimizers, activations, regularization, dropout, batch norm, hyperparameters) Principal Component Analysis of the dataset PCA integration with Nets in CV hypothesis verification using the Wilcoxon test for equality of medians models comparison Python notebook in English (a ton of Python code) quality paper-style report in English project presentation in English GitHub repository

This project is about Rainfall modelling and assumptions testing, you can expect: working on real data from Polish Institute of Meteorology and Weather Management data cleaning and analysis econometric modelling (OLS, Kernel Regression) OLS assumptions testing (RESET (several alternatives), Breusch-Pagan, Breusch-Godfrey, Jarque-Bera, Rescaled Moments, VIFs) model selection (information criteria) performance measurement (MSE, RMSE, MAE, MAPE, R squared and adjusted R squared, F test, scatterplots) data transformations (Principal Component Analysis, Box Cox power transform) “forecasting” (see the report why quotation marks used ;)) discussion about endogeneity Python notebook (and many HTML files with models for many weather stations) quality paper-style report in Polish GitHub repository

This project is about companies bankruptcy probability modelling with econometric methods, you can expect: paper-style report (in Polish) with quality tables, literature review, methodology description etc. statistical analysis (distributions, correlations, VIFs) econometric modelling (linear probability model, logit regression, probit regression) hypotheses testing (t-student, z tests, linktest) marginal effects (computation, interpretation) ROC curves cutoff optimization bootstrap simulation (Altman Z-Score follow up) huge Jupyter Notebook in Polish (lots of Python code) GitHub repository

This project is about christmas problem solving, you can expect: terminal app SQL queries error handling procedures app documentation, guide in English idea for future Xmas ;) GitHub repository