MsC in Engineering with top marks and research assistant of Econometrics for Italian top University. Business Expert in Risk Management. Academic Research in Quantitative Finance and Algorithmic Trading. Common discipline covered: Econometrics (with applications in R, Stata, SPSS, Eviews, Gretl), Statistics, Financial Mathematics, Quantitative Support for Master Degree Thesis (from Regressions to all statistical applications), Risk Management, Mathematics, Computer Science I help with assignments, exams, presentations, advanced research, dissertations, big programming projects and general skill enhancement. Proficient in all major statistical packages: R, SPSS, Stata, Matlab, EViews, Gretl Technical Skills (application and often implementation from scratch): 1) Econometrics: Multivariate Regression, Discrete variable models (i.e. Logit), Time series models (i.e. AR/MA, ARCH/GARCH), Vector AutoRegressive model (VAR), Cointegration (Engle-Granger, VECM), Long-memory process (Fractional Integration), Regime switching models (Hamilton Filter), Kalman Filter, Unobserved Components ARIMA model, Beveridge-Nelson decomposition (Hansen's approach), Copula methods, Metropolis-Hastings algorithm, Black-Litterman model (Meucci's approach), Hierarchical Risk Parity 2) Quantitative Trading (Mid-High Frequency Trading): Stat Arb & Pairs Trading models, Order Imbalance & Order Replenishment effects on intraday returns, Optimal Setup of Entry-Exit Trading Triggers for Quant Trading Strategies, Stat Arb Bertram Model, Data sampling rules for non equally-spaced data (time vs. volume clock for high freq data), Bid-Ask Bounce Bias & Sahalia Method for Microstructure Noise Estimation & Test, Hayashi-Yoshida Lead-Lag Index, D'Aspremont Method for Mean Rev Portfolios, Market Fragmentation in Financial Markets, High-Low prices & Pivot Points trading rule, Trend Following Strategy, Avellaneda-Stoikov Model for Optimal Trading Execution 3) Risk Management: P&L production & analysis for energy trading, VaR & Profit at Risk for energy trading, Merton approach for Credit VaR with/without credit rating migrations, EVT & Copula-based VaR, Stress Test models, Structured Credit Models for Regulatory Risk-Transfer, Additional Value Adjustments for Balance Sheet, Risk Aggregation, Model Risk, Interpolation Methods for multi-year PD Term Structure, Methods for Semidefinite-Positive Corr Matrix Adjustment 4) Financial Mathematics: Longstaff-Schwartz, HJM model (Glasserman's scheme), Greeks with Finite Difference Method, CPPI Products & Cushion Multiplier Setup 5) Machine Learning: Support Vector Machine, Decision Tree, Principal Component Analysis & Regression, XGBoost, Random Forest

Physics, math and programming are amazing tools for creativity. I see them as hammers and saws; once you've mastered the basics, you can start building your own stuff only limited by your own creativity. Whether you want to build a computer game in Unity or simulate lava flowing from a volcano etc., I can help you. If you need some introductory level math or university level physics, I'm there too! I can even help you build your very first machine learning algorithm, or simply teach you how to program in the first place. I love to teach and have been doing it for a while! I do computational physics and statistics in bio-complexity (that's stuff like simulating ant farms or bacterial colonies etc.) and I'm currently working on my masters thesis.

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I hold two MSc degrees: the first in Mathematical Engineering from KU Leuven (Belgium) and the second in Industrial Engineering from Duth (Greece). I offer courses on a wide variety of subjects, for Univerisity or High-school students, ranging from applied math and artificial intelligence, up to physics, programming languages like python, C++ and Fortran. In my teaching approach, I rely heavily on visual aids such as videos and illustrations to ensure that students get a clear understanding of the various concepts, along with personalized exercises.

This Python course teaches you the basics of programming in Python, including variables, data types, operators, control structures (if, for, while), functions, and lists. You will also learn how to manipulate data with libraries such as Pandas and NumPy, create graphs and visualizations with Matplotlib and Seaborn, and even develop simple web applications with Flask or Django.

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Hi! Welcome to my class on Matlab programming! As a PhD student in Geophysics my main tool is my computer. In order to do science one needs to know how to program. I often use Matlab in order to analyze data, run numerical models, plot results and much more. So, let's embark on the journey of learning Matlab and explore its diverse capabilities together! For beginners: I have designed it for absolute beginners to become at ease with the language within 5 sessions of 1h. Message me to know the 5 classes curriculum and I will be more than happy to share it with you! For intermediate users: If you already know the basics of Matlab but want to go more in-depth on certain packages this is the right place! Message me and we can discuss what your needs are!

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