Mattia - Financial management teacher - Milano
1st class free
Mattia - Financial management teacher - Milano

Mattia profile and their contact details have been verified by our experts

Mattia

  • Rate ₹5,165
  • Response 1h
  • Students

    Number of students accompanied by Mattia since their arrival at Superprof

    50+

    Number of students accompanied by Mattia since their arrival at Superprof

Mattia - Financial management teacher - Milano
  • 5 (4 reviews)

₹5,165/hr

1st class free

Contact

1st class free

1st class free

  • Financial management

MsC Thesis Support Financial Mathematics, Statistics and Econometrics (Live in Milan + Online)

  • Financial management

Class location

Super Teacher

One of our best tutors. They have a quality profile, experience in their field, verified qualifications and a great response time. Mattia will be happy to arrange your first Financial management classes.

About Mattia

Technical Skills (1) Econometrics: Multivariate Regression, Discrete variable models (ie Logit), Time series models (ie AR / MA, ARCH / GARCH), Vector AutoRegressive model (VAR), Cointegration (Engle -Granger, VECM), Long-memory process (Fractional Integration), Regime switching models (Hamilton Filter), Kalman Filter, Unbserved 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-Spaced Data, Bid-Ask Bounce Bias & Sahalia Method for Microstructure Noise Estimation & Test, Haya shi-Yoshida Lead-Lag Index, D'Aspremont Method for Revolution Portfolios, Market Fragmentation in Financial Markets, High-Low Prices & Pivot Points Trading Rules, 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 Correction 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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About the class

  • Class 11
  • levels :

    Class 11

  • English

All languages in which the class is available :

English

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's Degree Thesis (Risk Management, Mathematics, Computer Science) 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 price is 30 GBP / hour, even if the hourly cost can vary according to topic and project complexity Coverage 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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Rates

Rate

  • ₹5,165

Pack prices

  • 5h: ₹25,823
  • 10h: ₹51,647

online

  • ₹5,165/hr

free classes

This first free class with Mattia will allow you to get to know each other and to specify the exact learning requirements for the upcoming classes.

  • 1hr

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