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

Von 86.36 $ /Std

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

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Beim Lehrer zu Hause :

Utrecht, Netherlands

Copenhagen, Denmark

Bruxelles, Belgium

Boston, MA, USA

Miami, FL, USA

Paris, France

Online aus Vereinigtes Königreich

Über mich

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Erfahrung / Qualifikationen

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

Alter

Erwachsene (18-64 Jahre alt)

Seniorinnen und Senioren (65+ Jahre alt)

Unterrichtsniveau

Anfänger

Mittel

Fortgeschritten

Dauer

60 Minuten

Unterrichtet in

Englisch

Italienisch

Fachkenntnisse

Statistik

Wirtschaft für erwachsene

Programmierung

Verfügbarkeit einer typischen Woche

(GMT -05:00)

New York

Beim Lehrer zu Hause und Online

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

86.36 $ /Std

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

86.36 $ /Std

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

Manoj

4.95

(21)

I am a Professional Full Stack Developer with over 15 years of hands-on experience in software engineering, system design, and artificial intelligence.
I’ve worked across frontend, backend, DevOps, and AI, building enterprise-grade systems for real-world applications — from large-scale microservices to cognitive AI platforms.

I’m passionate about teaching the real, modern way of coding — combining deep technical foundations with today’s most advanced technologies: Generative AI, Agentic systems, RAG architectures, cloud automation, and intelligent DevOps.

Whether you are a beginner exploring your first “Hello World,” a professional improving your stack, or a researcher/developer exploring AI systems, I can guide you step-by-step — conceptually, practically, and strategically.

🧩 What You Will Learn
🖥️ Front-End Development

Master how to build responsive, interactive, and high-performance interfaces:

HTML / HTML5 – Structure, semantics, forms, accessibility

CSS / CSS3 / SCSS – Layout, animations, responsive design, Flexbox, Grid

Bootstrap / Tailwind / Material UI – Rapid design frameworks

JavaScript (ES6+) – Functional programming, event loop, closures, async/await

TypeScript – Strong typing, interfaces, decorators, generics

React.js / Next.js – Components, hooks, state management, routing, APIs

Angular (1.x to 17) – Modules, dependency injection, RxJS, advanced architecture

Vue.js (optional) – Reactive programming, lifecycle management

jQuery / AJAX – Legacy support and backend communication

Web Performance – Lighthouse, Core Web Vitals, PWA, caching strategies

⚙️ Back-End & Enterprise Development

Build scalable, secure, and intelligent server-side systems:

C / C++ / Data Structures / Algorithms / OOPS

Java / J2EE / Spring / Spring Boot / Spring Cloud / Hibernate / Struts / Wicket

Microservices Architecture – API gateway, service registry, inter-service communication

Node.js / Express / NestJS – Modern JavaScript/TypeScript backend

REST & SOAP Web Services – API design, security, documentation (Swagger / Postman)

Python (Flask / FastAPI) – REST APIs, ML pipelines, automation

Shell Scripting (Linux/Unix) – Automation, cron jobs, log parsing, DevOps scripting

PHP / Laravel / CodeIgniter – Classic web backend development

Containerization & Orchestration: Docker, Kubernetes, Helm

CI/CD & Cloud: Jenkins, GitHub Actions, Azure DevOps Pipelines

☁️ Cloud & DevOps Mastery

Learn to build, deploy, and scale applications on the cloud:

AWS (EC2, S3, Lambda, DynamoDB, API Gateway, ECS)

Azure (App Services, Functions, CosmosDB, DevOps)

Google Cloud (GCP, Vertex AI, BigQuery, Cloud Run)

Monitoring & Logging: ELK Stack (Elasticsearch, Logstash, Kibana), Grafana, Prometheus

Infrastructure as Code (IaC): Terraform, AWS CDK, Azure Bicep

Version Control & Collaboration: Git, GitHub, GitLab, Bitbucket

CI/CD Pipelines: Build, test, deploy automation, rollback, release management

📱 App Development

Develop mobile and hybrid apps end-to-end:

Android (Java/Kotlin) – UI/UX, activity lifecycle, API integration

Hybrid Frameworks: Ionic, Cordova, React Native

Progressive Web Apps (PWA) – Offline-first, caching, mobile optimization

Firebase Integration: Auth, Firestore, Cloud Messaging

🤖 Artificial Intelligence & Machine Learning

Learn how modern AI systems are built and deployed:

AI Fundamentals: Neural networks, supervised/unsupervised learning

Machine Learning with Python: scikit-learn, TensorFlow, PyTorch

Natural Language Processing (NLP): Transformers, BERT, GPT

Computer Vision: OpenCV, YOLO, Image Classification

AI APIs & Integrations: Google DialogFlow, Azure Cognitive Services, OpenAI API

🧬 Generative AI, RAG & Agentic Systems

Special focus on real-world AI integration and automation:

Generative AI Models (GPT, Claude, Gemini, Llama, Mistral) – Practical implementation

Prompt Engineering – Designing powerful, reusable prompt frameworks

Retrieval-Augmented Generation (RAG) – Hybrid search + generation architectures

Agentic AI Systems – Building autonomous multi-agent workflows (e.g., AutoGPT, CrewAI)

Agentic RAG – Contextual memory, chaining, and reasoning systems

LangChain / LlamaIndex – RAG pipelines, document loaders, embeddings, vector DBs

Vector Databases: Pinecone, Chroma, Weaviate, FAISS

Knowledge Graphs & Context Management – Enterprise data linking with RAG

AI App Deployment: FastAPI + Streamlit + LangServe + Docker

Copilot & AI Tools: GitHub Copilot, ChatGPT API, Code Interpreter, Vertex AI Studio

Google AI Developer Kit (ADK) – Edge AI, TensorFlow Lite, Coral, and model serving

Voice AI & Conversational Design: Dialogflow CX, OpenAI Assistants, ElevenLabs

🔬 Data, Testing & Quality

Database Systems: MySQL, PostgreSQL, MongoDB, Oracle, DB2, Redis

Database Design: ERD, normalization, indexing, performance tuning

Testing Tools: JUnit, Mockito, Selenium, Cypress, Postman

TDD / BDD Practices: Unit, integration, and end-to-end testing

Logging & Monitoring: ELK, Splunk, Prometheus

Performance Optimization: Profiling, caching, concurrency

🧩 Operating Systems & Scripting

Windows / Linux / Ubuntu / Unix Administration

File Systems, Permissions, Networking, Process Management

Shell Scripting / Automation / Log Analysis

System Security and SSH Hardening

🧠 Bonus Topics

Mathematics for Programmers – Logic, combinatorics, probability, graph theory

Game Development Basics: Unity, Phaser.js, HTML5 Canvas

AI Ethics, Data Privacy, Responsible AI Design

Automation Projects & Web Crawling / Scraping: BeautifulSoup, Selenium, Puppeteer

No-Code / Low-Code Integrations: Zapier, Make, AI automations

Jerome

4.95

(21)

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.

Gustave

4.95

(21)

Course introduction
Detailed course plan or well-detailed course material (Internet)
Implementation, exercises
Tips to solve well.
I already have experience in the field, I work as a mathematics teacher for Numéro1scolarité and for Méthodik.

Der richtige Lehrer Garantie

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