Peter - Microeconomics tutor - New York
1st lesson free
Peter - Microeconomics tutor - New York

Peter profile and its contact details have been verified by our experts

Peter

  • Rate R1153
  • Response 1h
  • Students

    Number of students Peter has accompanied since joining Superprof

    43

    Number of students Peter has accompanied since joining Superprof

Peter - Microeconomics tutor - New York
  • 5 (2 reviews)

R1153/h

1st lesson free

Contact

1st lesson free

1st lesson free

  • Microeconomics
  • Macroeconomics
  • Finance
  • Financial management
  • Business strategy
  • Econometrics
  • SPSS

Econometrics in R, Stata, SPSS, Eviews, Gretl for Master Thesis support (Online Lessons)

  • Microeconomics
  • Macroeconomics
  • Finance
  • Financial management
  • Business strategy
  • Econometrics
  • SPSS

Lesson location

Recommended

Peter is a respected tutor in our community. He is highly recommended for his commitment and the quality of his lessons. A trusted partner on your learning journey.

About Peter

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. Average cost is 30 GBP/hour, even if the hourly cost can vary according to topic and project complexity Covering university courses all around Europe: Italy, United Kingdom, France, Germany, Spain, Portugal,... Average hourly cost can change according to project complexity

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About the lesson

  • Primary
  • Secondary
  • Matric/GCSE
  • +5
  • levels :

    Primary

    Secondary

    Matric/GCSE

    AS Level

    A Level

    Adult education

    BTech

    MBA

  • English

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

  • R1153

Package rates

  • 5h: R5765
  • 10h: R11530

online

  • R1153/h

free lesson

The free first lesson with Peter allows you to get to know the tutor and discuss your needs and expectations.

  • 1h

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