Econometrics & Statistics (R, SPSS, Eviews, Gretl, Stata) for master thesis and assignments

Àpd 116.71 C$ /h

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

Lieu

Utilisez Ctrl + molette pour zoomer !

Cours chez le professeur :

Utrecht, Netherlands

Copenhagen, Denmark

Bruxelles, Belgium

Boston, MA, USA

Miami, FL, USA

Paris, France

En ligne depuis Royaume-Uni

Présentation

Education

Expérience / Qualifications

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

Age

Adultes (18-64 ans)

Seniors (65+ ans)

Niveau du Cours

Débutant

Intermédiaire

Avancé

Durée

60 minutes

Enseigné en

anglais

italien

Compétences

Statistiques

Economie pour adultes

Programmation informatique

Disponibilité semaine type

(GMT -04:00)

New York

Cours chez le professeur et par webcam

Mon

Tue

Wed

Thu

Fri

Sat

Sun

00-04

04-08

08-12

12-16

16-20

20-24

Finance, Statistics, Econometrics, Algorithmic Trading Tutor for master thesis and assignments

116.71 C$ /h

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.

Covering university courses all around Europe: Italy, United Kingdom, France, Germany, Spain, Portugal,...

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

Statistics for Master Thesis & Assignments with R SPSS Eviews Gretl

116.71 C$ /h

Expert offers private lessons in statistics and econometrics for master thesis and assignments. Regression ARIMA ARMA GARCH ARCH TOBIT LOGIT PROBIT and many other econometrics models. I have a strong experience that can help you to find your solution

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A highly experienced Franco-Belgian teacher (ook in het nederlands!) offers private lessons in mathematics (including finance), probability and statistics, as well as physics, chemistry, and biology for secondary and higher education levels. For physics, chemistry, and biology, the instruction is tailored to the secondary level, specifically up to the 5th year of secondary education in Belgium.

Whether you prefer lessons at your place, my place, or remotely, I am flexible to accommodate your needs. If necessary, I can travel to your home in Brussels, Walloon and Flemish Brabant, with a minimum duration of 2 hours per session. The lessons are designed to provide extensive practice with numerous exercises. Distance learning options are also available through platforms such as Skype, Facebook, etc. Please note that for students in France, only distance learning courses are provided.

In mathematics, I specialize in various topics and frequently provide lessons covering the entire secondary school curriculum, including math 6 and higher. These topics encompass factorization, equations of the 1st and 2nd degree (with in-depth study of parabolas), limits, derivatives, integrals, exponentials and logarithms, as well as trigonometry. Additionally, I am occasionally called upon to teach analytical geometry in space, including equations of lines and planes.

For statistics and probabilities, I provide instruction in descriptive and inferential statistics (univariate and bivariate), covering confidence intervals and hypothesis tests, applicable to secondary and higher education levels.

Feel free to reach out to me to discuss and arrange the lessons based on your specific needs and availability. My aim is to help you enhance your skills effectively and provide personalized instruction. By tailoring the lessons to your requirements, we can ensure rapid progress in your studies.

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Doctor in cognitive psychology graduated from the University of Strasbourg, holder of a master 2 of research in Biology and a master 2 professional in scientific communication, I propose courses of statistics (descriptive and inferential, theoretical and applied it is according to your requests) with a pedagogy and methodologies rigorous and personalized according to your needs and your potentialities. My courses are divided into 3 possible approaches: 1 / Theoretical courses / methods and practice 2 / Help with data analysis 3 / Through a scientific popularization approach and a rigorous and effective method (references available) to answer to the expectations of the students and to reach or exceed the objectives set, my courses are easy to understand and appropriate. I propose in addition a training on varied and targeted exercises as well as annals of examination to optimize your preparation. Thus, what seems complex, abstract and incomprehensible to you will become concrete, and you will be able to answer questions without hesitation. I also integrate a coaching method to optimize the learning and training necessary to pass the university exams in statistics.

My courses are aimed at students in psychology or from other courses (university, medicine, engineering schools, BTS, MBA, Business School, Business School, international finance, etc.) wishing to optimize their performance and grades in exams and competitions.

Teacher and trainer at the Ecole Polytechnique, at the Universities of Strasbourg and Paris 8, ESSEC Business School, ISTH, IONIS Education Group, EEEA, Institut Tocqueville etc.

I receive many requests from students at Paris 8 University (IED or not) Paris 5 and Nanterre because I am very familiar with the program and the expectations of the exam jury.

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Engineer and senior professor of engineering sciences provides support courses in analog and digital electronics at all levels, engineering schools. having a scientific and technical knowledge, five years of experience in the field of teaching, teaching and a sense of listening and analysis, I am able to help pupils and students and train them in the chapters of which they have difficulties. for more info please contact me

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(FR/ENGL) Experienced and passionate tutor, I have been supporting students for 6+ years in their mathematics journey, from high school through the beginning of higher education.

🔎 Why choose my lessons?
• Guaranteed progress: my students not only improve their grades, but also gain confidence and independence.
• Personalized teaching: I adapt to each student’s needs (remedial support, exam preparation, advanced learning).
• Engaging and practical lessons: thanks to my degree in Business Engineering (ULB – Solvay School) and my experience as both a high school teacher and a tutor, I enrich my explanations with numerous real-life examples.

🏫 Lesson formats
• At-home tutoring (individual or small group) – available anywhere in Brussels and Wallonia.
• At the teacher’s location – in a classroom near ULB.
• Online or hybrid lessons – interactive and adapted to all profiles using effective digital tools.

💡 My goal: to share not only knowledge, but also a love for learning and solid study methods that will benefit students far beyond the classroom.

Feel free to contact me for any further information; I’ll be happy to help.

Looking forward,
Ryan

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doctoral student in engineering sciences provides support courses in analog and digital electronics at any DEUG level and engineering schools. having scientific and technical knowledge, three years of experience in the field of teaching, pedagogy and a sense of listening and analysis, I am able to help pupils and students and train them in the chapters of which they are having difficulty. for more info please contact me

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Are you a university student, engineer, or professional who needs to actually use data — not just learn theory about it?
This course is built around real problems and real code. We skip the textbook formulas and go straight to applying statistics and data science the way professionals do: with Python (pandas, NumPy, scikit-learn, matplotlib) and R (RStudio).
What we cover, adapted to your level and goals:
- Descriptive and inferential statistics (the ones that actually matter)
- Data cleaning, exploration, and visualization
- Regression, classification, and intro to machine learning
- Time series and forecasting basics
- R for statistical analysis and academic research

Who this is for:
- University students in statistics, economics, engineering, or biology
- Professionals wanting to move into data analysis or data science
- Researchers who need to process and present data properly

I use Python and R professionally as a working engineer — everything I teach comes from real application, not just academic exercises.

Dafnis

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Bonjour,

Je suis un professeur de machine learning avec 5 ans d'expérience et je suis capable d'enseigner à tous les niveaux. Je suis spécialisé en utilisant Python et R pour enseigner les différents algorithmes de machine learning, y compris les réseaux de neurones, les arbres de décision et les algorithmes de clustering.

J'ai également une expérience approfondie dans l'utilisation de libraries Python et R populaires comme TensorFlow, Keras, Scikit-learn et ggplot2.

En plus de mon enseignement en matière de machine learning, je suis également capable d'aider mes étudiants à lire et à comprendre des articles de recherche pour leurs exposés, ainsi qu'à travailler sur des projets en Python et R.

Je suis passionné par l'apprentissage automatique et j'aime partager mon savoir avec mes étudiants. Si vous êtes intéressé par mes services en tant que professeur de machine learning pour tous les niveaux, n'hésitez pas à me contacter.

Je suis en mesure de vous enseigner les sujets suivants :

1.Python ou R
2.Exploration des données
3.Machinea learning
3.1. Intro ML
3.2. Linear Model
-> Linear Models for Regression and Classification
3.3. Kernel
-> Kernelization
3.4. Model selection
3.5. Ensemble model,
-> Bagging / RandomForest, Boosting (XGBoost,LightGBM,...) , Stacking
3.6. Data préprocessing
-> Data preprocessing
-> Pipelines: choose the right preprocessing steps and models in your pipeline
-> Cross-validation
3.7. Neural Networks
-> Neural architectures
-> Training neural nets: Forward pass: Tensor operations and Backward pass: Backpropagation
-> Neural network design: Activation functions, weight initialization and Optimizers
-> Neural networks in practice: Model selection, Early stopping, Memorization capacity and information bottleneck, L1/L2 regularization, Dropout, Batch normalization
3.8. Convolutional Neural Networks
-> Image convolution
-> Convolutional neural networks
->Data augmentation
-> Model interpretation
-> Using pre-trained networks (transfer learning)
3.9. Neural Networks for text
-> Bag of words representations, Word embeddings, Word2Vec, FastText, GloVe

En plus de mon enseignement en matière de machine learning, je peux également aider mes étudiants à se préparer pour les entretiens d'embauche pour des postes de data scientist.

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Master Python with Personalized Courses

Discover the art of programming with Python courses tailor-made to meet your specific needs. Whether you are a beginner, intermediate or professional, my lessons are suitable for all levels.

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Personalized Teaching Approach: Each course is tailored to your skill level and individual goals.

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As a Python expert, I have a passion for teaching and sharing my knowledge. My goal is to guide you effectively in your learning journey.

Book Your First Lesson:

Start your journey to Python mastery now by booking your first lesson. Whether you aspire to enter the development field or hone your existing skills, these courses are designed for you.

Francisco

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Hi!

Welcome to my class on Python 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 use Python everyday in order to analyze data, run numerical models, plot results and much more. So, let's embark on the journey of learning Python 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 Python 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! I am a professional user of Numpy, Pandas, Matplotlib, os, scipy and many more packages!

Are you not sure Python is the right language for you? Check the following out and let me know if you have any questions!

First of all, what is Python? According to its creator, Guido van Rossum, Python is a:

“high-level programming language, and its core design philosophy is all about code readability and a syntax which allows programmers to express concepts in a few lines of code.”

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This versatility makes Python a powerful tool for those eager to delve into different aspects of programming. If this caught your curiosity message me and I'll make you a Python hero! Welcome to the community!

Sebastien

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Vous souhaitez apprendre à programmer en Python et devenir un expert en codage ? Que vous soyez totalement novice ou que vous ayez déjà quelques connaissances, ce cours particulier est fait pour vous !

Avec une méthode personnalisée et interactive, vous apprendrez à maîtriser Python à votre propre rythme, tout en acquérant des compétences pratiques pour réaliser vos propres projets. Grâce à des exercices adaptés à votre niveau et un accompagnement sur mesure, vous progresserez rapidement et efficacement.

🎯 Pourquoi choisir ce cours ?
Cours particuliers entièrement personnalisés : Le contenu et le rythme d'apprentissage sont adaptés à vos besoins et objectifs spécifiques.
Méthodologie interactive : Vous bénéficierez d'explications claires, d'exemples concrets et d'exercices pratiques pour une compréhension approfondie des concepts.
Projets pratiques : Appliquez vos connaissances en réalisant des projets concrets qui renforceront vos compétences en programmation.
Flexibilité des cours en ligne : Apprenez depuis chez vous, à votre propre rythme, grâce à des séances en ligne interactives avec audio et partage d'écran.
Accompagnement complet : Recevez des conseils personnalisés pour progresser rapidement et surmonter vos difficultés en programmation.
Préparation aux examens et certifications : Un entraînement intensif pour vous aider à réussir vos examens ou à obtenir vos certifications en Python.

Ce cours aborde tous les fondamentaux de Python, ainsi que des concepts avancés pour vous amener à un niveau professionnel.

🐍 Contenu du Cours :
1. Notions de Base en Python – De Débutant à Intermédiaire
✏️ Introduction à Python : Installation, IDE, premiers scripts.
🔠 Syntaxe et Structure de base : Variables, types de données, opérateurs.
🔄 Structures de contrôle : Conditions (if, else), boucles (for, while).
📦 Fonctions et Modules : Création de fonctions, importation de modules.
🗃️ Gestion des Collections : Listes, tuples, dictionnaires, ensembles.
📂 Fichiers et Entrées/Sorties : Lecture et écriture de fichiers.
🔍 Débogage et Gestion des erreurs : Try, except, assertions.

Programmation Orientée Objet (POO) en Python
🧩 Classes et Objets : Apprendre à créer et à utiliser des classes et des objets.
🔐 Encapsulation, Héritage et Polymorphisme : Exploration des concepts avancés de la POO.
📚 Méthodes et Attributs : Comprendre les méthodes d'instance, de classe et statiques.
🔄 Surcharge d'opérateurs : Adapter le comportement des opérateurs selon vos besoins.

3. Projets Pratiques et Applications Réelles
🎲 Jeux en Python : Créez vos propres jeux en utilisant Pygame.
🌐 Applications Web : Découvrez Flask et Django pour développer des sites web dynamiques.
📊 Analyse de Données : Apprenez à manipuler et analyser des données avec Pandas et NumPy.
🤖 Intelligence Artificielle et Machine Learning : Initiez-vous à Scikit-learn pour élaborer des modèles de prédiction.
🔗 API et Web Scraping : Apprenez à interagir avec des API et à extraire des données web grâce à BeautifulSoup et Requests.

4. Concepts Avancés en Python
⚡ Programmation Asynchrone : Utilisation d'Asyncio pour créer des applications rapides et réactives.
📦 Gestion des Packages et Environnements Virtuels : pip, venv, et gestion des dépendances.
🧪 Tests Unitaires : Utilisation de pytest pour assurer la fiabilité de votre code.
🔒 Sécurité et Optimisation : Rédaction de code à la fois sécurisé et performant.

🧑‍🏫 Méthodologie et Approche Pédagogique :
Apprentissage par la pratique : Chaque concept théorique est immédiatement mis en œuvre à travers des exercices pratiques pour ancrer efficacement les connaissances.
Enseignement interactif en ligne : Utilisation de l'audio et du partage d'écran pour assurer une communication fluide et un apprentissage dynamique.
Suivi personnalisé : Un accompagnement régulier pour évaluer votre progression et répondre à toutes vos questions.
Projets concrets : Élaboration de projets complets pour appliquer vos compétences en programmation.
Motivation et confiance : Une approche positive et encourageante pour renforcer votre confiance en vos capacités.

🎓 Pour qui ?
Ce cours est destiné à :

- Des débutants complets qui n'ont jamais touché à la programmation.
- Des étudiants en informatique ou en sciences désireux d'apprendre Python pour leurs études.
- Des professionnels souhaitant acquérir des compétences en programmation pour faire avancer leur carrière.
- Des autodidactes passionnés de programmation qui veulent réaliser leurs propres projets.
- Des candidats aux certifications en Python à la recherche d'un entraînement intensif.

🔔 Inscrivez-vous dès maintenant ! Ne ratez pas l'occasion de maîtriser Python et d'acquérir des compétences en programmation très prisées sur le marché du travail. Participez à "🐍 Maîtrisez Python – 🚀 Cours Particuliers Personnalisés pour Devenir un Pro du Code !" et avancez à votre rythme avec assurance et motivation !

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Courses delivered by a laureate of the Louvain School of Management (one of Belgium’s leading business schools) with 5+ years’ experience in management.
All courses are customisable and delivered based on your needs from one-off workshops to multi-day in-company programmes.

Maritime & Port Operations : A practical course that explains how ports and maritime services work in real life. You will learn berth booking, port-call procedures, stakeholder roles and how to coordinate suppliers and authorities to avoid delays.
Key outcomes: berth & port-call checklists; supplier coordination best practices; simple compliance & documentation routines.

Logistics & Transportation : Hands-on training on planning, executing and monitoring transport operations across road, sea and air. Focus on routing, inventory control, supplier selection and basic cost optimisation.
Key outcomes: route & inventory planning templates; procurement for transport; incidence handling and documentation.

Marketing Strategy : Clear, actionable marketing strategy course for organisations that need a focused plan. Learn how to define positioning, segment customers, build value propositions and convert strategy into measurable actions.
Key outcomes: positioning canvas; 90-day go-to-market plan; KPI dashboard to track progress.

Business Plan (Build & Pitch) : Step-by-step course to build a solid business plan and pitch it confidently to partners or funders. Covers financial assumptions, go-to-market, operational plan and investor-ready pitch decks.
Key outcomes: completed one-page business plan; financial assumptions template; 7–10 slide pitch deck.

Market Studies & Competitive Intelligence : Practical methodology to conduct fast market scans, map competitors and extract insights that inform strategic decisions. Teaches data sources, analysis frameworks and reporting for decision-makers.
Key outcomes: competitor map; SWOT & Ansoff analysis; 1-page market intelligence brief.
Format: half-day workshop or 2-day deep-dive.

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Création d'un site web.
Sous une distribution Linux ou Windows.
Installation de la dernière version de django
Installation de la dernière version de python, sous windows
Sous Linux configuration de environnement python.
Installation d'un IDE VSCODE

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Are you looking for a reliable and experienced Economics teacher to support your child at secondary school level in Belgium? I offer comprehensive and personalised Economics tutoring, fully aligned with the Belgian secondary school curriculum. With solid experience in secondary education, I help student s understand key economic concepts, build confidence, and achieve better academic results, whether for regular follow-up, homework support, or exam preparation.

Topics Covered – Full Secondary Economics Curriculum
• Introduction to Economics
(needs, scarcity, economic agents, decision-making)
• Market Economy and Firms
(supply and demand, price formation, production, competition)
• Money, Banking and Basic Finance
(functions of money, banks, credit, savings, inflation – secondary level)
• Labour Market and Economic Policies
(employment, unemployment, wages, role of the State)
• Household Economics and Consumption
(household budget, purchasing power, responsible consumption)
• Basics of Accounting and Management
(income and expenses, costs, basic financial management)
• Economics and Sustainable Development
• Belgian and European Economy – Key Concepts
• Economic Methodology and Exam Skills
(reading graphs, analysing texts, structuring answers)
• Applied Economics: exercises and case studies

Teaching Approach
✔ Clear and structured explanations
✔ Step-by-step progression
✔ Adapted to the student’s level and learning pace
✔ Practical exercises and real-life examples
✔ Focus on exam techniques and methodology
✔ Supportive and confidence-building environment

Learning Objectives
• Improve understanding of Economics
• Achieve better school results
• Gain confidence and autonomy
• Prepare effectively for exams
• Develop strong analytical and study skills

For Parents
I provide a serious, supportive and structured learning framework.
Regular feedback can be shared with parents regarding the student’s progress and areas for improvement.

Practical Information
• Level: Secondary school (all grades)
• Curriculum: Belgium (FWB)
• Format: Online or in-person
• Language: English or French