Mattia - Economics tutor - Vancouver
1st lesson free
Mattia - Economics tutor - Vancouver

Mattia profile and its contact details have been verified by our team.

Mattia

  • Rate $90
  • Response 1h
  • Students

    Number of students Mattia has accompanied since arriving at Superprof

    10

    Number of students Mattia has accompanied since arriving at Superprof

Mattia - Economics tutor - Vancouver
  • 5 (1 review)

$90/h

1st lesson free

Contact

1st lesson free

1st lesson free

  • Economics
  • Econometrics
  • Risk management

Expert in Econometrics offers private tuition at all levels (MSc, PhD, ...)

  • Economics
  • Econometrics
  • Risk management

Lesson location

About Mattia

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 disciplines 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,...

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About the lesson

  • Elementary School
  • Middle School
  • High School
  • +6
  • levels :

    Elementary School

    Middle School

    High School

    College

    University

    Adult Education

    Masters/ Graduate School

    MBA

    Early childhood education

  • English

All languages in which the lesson is available :

English

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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Rates

Rate

  • $90

Pack rates

  • 5 h: $450
  • 10 h: $900

online

  • $90/h

free lessons

This first lesson offered with Mattia will allow you to get to know each other and clearly specify your needs for your next lessons.

  • 1hrs

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