facebook
favorite button
super instructor icon
Trusted teacher
This teacher has a fast response time and rate, demonstrating a high quality of service to their students.
member since icon
Since October 2019
Instructor since October 2019
Business Management and Economics. Learn how to write research and business proposal.
course price icon
From 38.32 C$ /h
arrow icon
-I specialize in tutoring Business Management and Economics for schools and the International Baccalaureate (IB) SL/HL, IGCSE, SAT and university students.
-This focus is to learn how to analysis business case studies and economics articles.
- Preparing students for their final exams
Extra information
Laptop and note book
Location
green drop pin icongreen drop pin icongreen drop pin icon
|
Use Ctrl + wheel to zoom!
zoom in iconzoom out icon
location type icon
At student's location :
  • Around Nieuwegein, Netherlands
  • Around Utrecht, Netherlands
  • Around Amersfoort, Netherlands
About Me
- Motivated and can deal with different students background and diversity.
- Open minded
- Teaching high school students and university level
- Strong research skills
Education
Master degree in Business Administration from University of Leicester in the UK
BA in Business Management from Dean College of London in the UK
Certificate in Business Management from Dean College of London in the UK.
Experience / Qualifications
Twenty years teaching experience.
Workshops for IB business management and economics
Ten years teaching at university level and eight years teaching IB program at high school level
Age
Children (7-12 years old)
Teenagers (13-17 years old)
Adults (18-64 years old)
Seniors (65+ years old)
Student level
Beginner
Intermediate
Advanced
Duration
60 minutes
The class is taught in
English
Arabic
Availability of a typical week
(GMT -05:00)
New York
at home icon
At student's home
Mon
Tue
Wed
Thu
Fri
Sat
Sun
00-04
04-08
08-12
12-16
16-20
20-24
Similar classes
arrow icon previousarrow icon next
verified badge
Gert
Business process and IT
Within the complexity of the current market, companies can no longer do without properly functioning information and communication technology (ICT). This makes ICT one of the most important instruments to implement the organizational strategy. The most critical points lie with the connection of IT to the business process. This connection is often not optimal. Functional managers and information managers are ultimately responsible for this connection.

The purpose of BiSL®
BiSL® builds a bridge between IT and business process, and between functional managers and information managers. The BiSL process model provides insight into all main processes in their field, and the relationships between the processes. It offers starting points for improving processes, including through 'best practices' and it provides a uniform terminology. (source: aslbislfoundation.org)

The learning objectives for a BISL® training are:

Knowledge in the field of
- The positioning of BISL® in a management organization
- The distinction and relationships with other forms of management
- The structure of the BiSL® model
- The various processes within BiSL®
• Leading processes
• Management processes
• Executive Processes
- The purpose of the various processes
- The activities within the various processes
- The relationships between the processes (coherence)

Skills regarding
- Recognizing BiSL® in practice

Attitude with regard to
- The acceptance of BiSL® as a Service Management method
- The concepts for certification of BiSL®
verified badge
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 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
message icon
Contact Ali
repeat students icon
1st lesson is backed
by our
Good-fit Instructor Guarantee
Similar classes
arrow icon previousarrow icon next
verified badge
Gert
Business process and IT
Within the complexity of the current market, companies can no longer do without properly functioning information and communication technology (ICT). This makes ICT one of the most important instruments to implement the organizational strategy. The most critical points lie with the connection of IT to the business process. This connection is often not optimal. Functional managers and information managers are ultimately responsible for this connection.

The purpose of BiSL®
BiSL® builds a bridge between IT and business process, and between functional managers and information managers. The BiSL process model provides insight into all main processes in their field, and the relationships between the processes. It offers starting points for improving processes, including through 'best practices' and it provides a uniform terminology. (source: aslbislfoundation.org)

The learning objectives for a BISL® training are:

Knowledge in the field of
- The positioning of BISL® in a management organization
- The distinction and relationships with other forms of management
- The structure of the BiSL® model
- The various processes within BiSL®
• Leading processes
• Management processes
• Executive Processes
- The purpose of the various processes
- The activities within the various processes
- The relationships between the processes (coherence)

Skills regarding
- Recognizing BiSL® in practice

Attitude with regard to
- The acceptance of BiSL® as a Service Management method
- The concepts for certification of BiSL®
verified badge
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 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
Good-fit Instructor Guarantee
favorite button
message icon
Contact Ali