Need Help:

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


max. class size

Mode of delivery

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



→ 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
  • 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?

Get in touch

Contact Form

    indicate one main technique and/or concept, if you know (from the list)


    Client’s Feedback