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

From 62 £ /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

Location

Use Ctrl + wheel to zoom!

At teacher's location :

Utrecht, Netherlands

Copenhagen, Denmark

Bruxelles, Belgium

Boston, MA, USA

Miami, FL, USA

Paris, France

Online from United Kingdom

About Me

Education

Experience / 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

Adults (18-64 years old)

Seniors (65+ years old)

Student level

Beginner

Intermediate

Advanced

Duration

60 minutes

The class is taught in

English

Italian

Skills

Statistics

Economics for adults

Computer programming

Availability of a typical week

(GMT -04:00)

New York

At teacher's location and via 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

62 £ /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

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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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It wasn't until I met an amazing teacher at age 15 that I discovered my mathematical genius and my life was changed forever.

I'm eternally grateful to that teacher.

My teacher knew that self-image and self-belief is the key to unlocking your child's mathematical abilities.

Everyone is good at maths, but we all have different styles of thinking.

Bad teachers teach every child the same way.

My job is to find your child's style of mathematics and allow him to discover that for himself.

When he discovers that, he will begin to enjoy the beauty and power of mathematics...and then you will see as the grades begin to soar.

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Targeted training based on typical exercises and exam problems.

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Whether you've never written a line of code or you're a student who needs to pass a programming course, this is a practical, no-fluff introduction that gets you writing real code from session one.
What we can cover depending on your goals:

Python fundamentals: variables, loops, functions, data structures
- Object-oriented programming (OOP)
- Data manipulation with pandas and NumPy
- Introduction to machine learning with scikit-learn
- Database management with SQL
- C and Java upon request
- MATLAB and R available for engineering/science students

Why learn with me?
I'm not a student teaching on the side — I'm a professional engineer who uses Python daily for data analysis, modeling, and automation. I know exactly which concepts matter in the real world and which ones you can skip for now.
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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.

Why Choose My Courses?

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

Practical Experience: Learn by doing with real-world projects that build your understanding and skills.

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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.

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Are you looking for personalized support to succeed in mathematics, physics or computer science? Whether you are a middle school, high school, university student or simply curious to learn, this multidisciplinary program is for you!

💡 Why Choose this Program?
This course offers comprehensive, tailored support to help you:

Strengthen your foundations and fill in your gaps.
Understand theoretical concepts in depth.
Master problem-solving methods.
Develop your computer skills, from introductory to advanced programming.
Prepare effectively for your exams and competitions.
With a human, motivating and caring approach, you will learn at your own pace in a calm and encouraging environment, without pressure or judgment.

📘 Mathematics – For All Levels
Mathematics may seem complex and abstract, but with the right method and clear explanations, it becomes logical and accessible.
This module covers:

Middle school level: Arithmetic, fractions, proportions, basic geometry, statistics.
High school level: Algebra, functions, equations, analytical geometry, probabilities.
Preparation for exams: Brevet, Bac, entrance exams for grandes écoles.
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This module will guide you through:

Middle and high school level: Mechanics, electricity, optics, thermodynamics.
University Level: Analytical mechanics, advanced electromagnetism, quantum physics, statistical thermodynamics.
Scientific Methodology: Knowing how to analyze a problem, formulate a hypothesis, apply physical laws and interpret the results.
Practical Applications: Virtual experiences, interactive simulations to better understand theoretical concepts.
💻 Computer Science – From Basics to Advanced Skills
In an increasingly digital world, mastering IT is essential. This module adapts to your level and your objectives:

Introduction to Computers: Understand how a computer works, use office software (Word, Excel, PowerPoint).
Programming Beginner: Learn to code in Python, JavaScript or C/C++ with clear explanations and practical exercises.
Advanced Programming: Optimized algorithms, complex data structures, object-oriented programming.
Project Development: Creation of web applications, automated scripts, simple video games.
Preparation for NSI Exams: Complete support to pass the Digital and Computer Science tests.
🎯 Interactive and Motivating Teaching
Dynamic Online Course: Learn from home with an interactive format using audio and screen sharing.
Method Adapted to Your Pace: Each course is designed according to your level and your objectives.
Practical Exercises and Concrete Projects: To apply theoretical concepts and learn while having fun.
Personalized Monitoring: Regular support to monitor your progress and adapt the program to your needs.
Encouragement and Motivation: A positive approach to building your confidence in your abilities.
🔔 For Who?
This program is aimed at:

Middle school and high school students wishing to strengthen their foundations or aim for excellence.
University students in science or computer science looking to deepen their knowledge.
Candidates for exams and competitions preparing for the Brevet, the Bac, or entrance exams to the grandes écoles.
Passionate self-taught people who want to learn to program or better understand the scientific world.
Adults in professional retraining wishing to acquire IT skills.
🚀 Ready to Succeed?
Join the "🎓 Multidisciplinary Program – 📘 Mathematics, 🔬 Physics & 💻 Computer Science for All Levels!" and benefit from personalized support to achieve your goals. Whether you want to improve your grades, pass your exams or develop programming skills, this program will give you knowledge, confidence and motivation.

Register today and take the first step towards success!

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Hello,
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Why choose me?
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Featured Review :
Been trying to learn Java on my own for about 1 year and I couldn't get a grasp on it. Aniket make learning Java a fun experience and challenges you to think for yourself to reinforce the concepts you've learned. I am truly excited for our meetings and he makes time go by so fast that I'm upset when they end. Great teacher and he is genuinely passionate about your success. If I could give him more stars I would!!!

Thanks
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A mathematics teacher with experience teaching algebra, statistics, and probability at the university level, I am passionate about sharing knowledge and now wish to use my teaching skills to serve secondary school students within the French national education system. Rigorous, patient, and pedagogically sound, I place great importance on the success and progress of each student.

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I offer private mathematics lessons tailored to the level and objectives of each student: middle school, high school and higher education.

The courses may cover subjects such as algebra, analysis, calculus, probability, and statistics.

I begin by identifying the concepts that are causing difficulty, then we review the material clearly and progressively before working on appropriate exercises. I can also help students with their homework, preparing for tests and exams, or exploring specific concepts in greater depth.

My goal is for the student to truly understand the methods used and gradually become capable of solving exercises independently.

Demo

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You will learn from basic to advanced,
You will learn from basic to advanced,
You will learn from basic to advanced,
You will learn from basic to advanced,
You will learn from basic to advanced,
You will learn from basic to advanced,
You will learn from basic to advanced,