Paul - Maths tutor - County Galway
1st lesson free
Paul - Maths tutor - County Galway

The profile of Paul and their contact details have been verified by our experts

Paul

  • Rate 644 GHS
  • Response 1h
  • Students

    Number of students Paul has accompanied since arriving at Superprof

    18

    Number of students Paul has accompanied since arriving at Superprof

Paul - Maths tutor - County Galway
  • 5 (1 review)

644 GHS/hr

1st lesson free

Contact

1st lesson free

1st lesson free

  • Maths

ARMA GARCH Regression Logistic Regression Machine Learning Artificial Intelligence with R and other softwares

  • Maths

Lesson location

About Paul

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.

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About the lesson

  • Primary school
  • Junior high school
  • SHS 1
  • +19
  • levels :

    Primary school

    Junior high school

    SHS 1

    SHS 2

    SHS 3

    BTS

    Adult Education

    Facultate (Licență)

    Master's degree

    Higher national diploma

    Staatsexamen

    Doctor of philosophy

    Other

    ACCA

    ICAEW

    CIPFA

    AIA

    CIMA

    GDL

    Qualified Lawyer Transfer Scheme

    MBA

    WASCE

  • 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

  • 644 GHS

Pack prices

  • 5h: 3220 GHS
  • 10h: 6440 GHS

online

  • GHS644/h

free lessons

The first free lesson with Paul will allow you to get to know each other and clearly specify your needs for your next lessons.

  • 1hr

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