What if you can overcome that fear in just over a few weekends?

The easiest part of academic writing/manuscript writing/publication in finance and/or economics/econometrics is the empirical sections. However, that is where most people struggle, delay, and sometimes give up. This handicap comes from poor background in basic mathematics/ statistics, econometrics, coding, and the use of statistical and econometric software in general. This breeds a very unhealthy fear for early career researchers, especially.

Well, you should learn from one of the best. Enroll in a crash course to learn and implement one main empirical technique (and supporting techniques) in just over two weekends, by your own hands.
A weekend course provides all you need to complete one empirical chapter or one manuscript.
From theory → method → estimation → results → analysis.

Contents of one Class/Cohort

• One main method/technique
  theory → methodology → estimation → results → analysis.
• 1-2 supporting/auxiliary/motivating methods.
• Bonus – descriptive statistics.

Pre-course training

• 2-hour into R session.

Post class /training side attractions:

• A 90-day mentorship window to complete one manuscript*
• Foolproof codes for your own estimations and practice.
• Error/code fixing.
• Accredited journal suggestions
• Data sourcing suggestions
• Access to recorded sessions

4

max. class size

Mode of delivery

→ Online via Zoom.
→ Onsite delivery can be arranged. Cohort will bear the cost of transportation and logistics.

.

Terms

→ Payment must be made before start of class.
→ Zoom links are shared a day/hours before class begins.

Techniques toolbox

• Quantile regressions
• Causality in-quantiles
• Non-linear causality
• EFA, CFA, SEM
• Entropy
• Wavelets – bi-variate, partial, multiple
• Connectedness indices
•       Diebold – Yilmaz
•       Barunik and Krehlik connectedness indices.
•       VAR, TVP-VAR, QVAR connectedness
• Frequency – domain
• Time – domain
• Time – frequency domain
• Tail risk modelling
• GAS- and GARCH-based on VaR, ES, and VaRES
• Model confidence set for model ranking

• Model Predictive Ability
• Back testing
• Higher moments modeling
• Generalised lambda distribution, asymmetric distributions
• Spatial autocorrelation (Moran’s I)
• Network analysis
• Tree – Assisted Naïve Bayes Network (TAN-BN)
• Panel data modelling
•       Fixed effects, Random effect
•       Instrumentation for Endogeneity
•       Generalised method of moments
• Quantile panel regression
• Linear and non-linear ARDL
• Quantile ARDL
• Quantile cointegration
• Bibliometric analysis

Concepts/ Theories

Addressed By The Techniques

• Linear and non-linear causality
• Non-linearity
• Asymmetry
• Diversification, hedge, safe – haven
• Interdependence, spillover, connectedness, co-movement
• Contagion – time-varying, shifting contagion
• Efficient market hypothesis (EMH), Heterogeneous market hypothesis (HMH), Adaptive market hypothesis (AMH), and Competitive market hypothesis (CMH)
• Tail risk; fat tails

• Volatility clustering
• Predictability
• Network
• Complex causal/relational associations
• Hierarchical explanatory regression for mediation/moderation
• Information transmission
• Event study
• Flight-to-quality, flight-to-safety
• Endogneity and instrumentation
• Long-run relationships
• And many more

Getting In Touch/Setting Up

• If you know the exact techniques/methods you want to use, list them.
• If you need assistance identifying your method, explain your objective and direction of the research. We will suggest techniques for you.
• If you already have a group of 4, we can set up the dates.
• If you are alone, you will have to wait for the class of your identified method to be full.

Have any Questions?

positivecarry.academy@gmail.com

Get in touch

Contact Form

Testimonial

Client’s Feedback

Ratings

Dr. Owusu Junior exhibited an in-depth understanding of the subject matter and was able to communicate even the most difficult concepts in a clear and engaging manner. His mastery of contemporary techniques and methods in Financial Econometrics is unparalleled. He meticulously designed each module to provide a balanced blend of theoretical concepts and practical applications, ensuring that participants acquired a comprehensive understanding of both the underlying theory and its practical applications.

KSO

Assistant Prof. of Finance, International University of Grand-Bassam.

Ratings

Dr Owusu Junior’s online classes are uniquely engaging and well-tailored to address all needs. The few virtual classes we had have paved way for me to flesh out my PhD thesis with ease. I won’t blink in recommending his classes to any interested person.

U-F

A PhD. Candidate, University of the Witwatersrand.

Ratings

Dr Owusu Junior is such an amazing tutor and one of the few I have encountered. He made econometrics using R easy for beginners to understand. His teaching style and technique has left a memorable impression on me and made my PhD journey a lot more easier.

Providence

PhD Candidate, University of South Africa

Ratings

One of the difficult challenges for a PhD candidate can be the use of open-source software for advanced econometrics. However, in-depth knowledge and insightful engagements with Dr. Owusu Junior of selected cutting-edge models for analysis with R have made my PhD thesis very easy. Currently, I have been able publish papers in top-tier journals and at the completion stage of my PhD thesis.

Moh Armah

PhD Candidate, GIMPA