Formation/Cours

None

Forecasting is the capacity to predict future trends and events. This course will examine the variety of tools used by analysts in their attempt to decipher short, medium, and long term trends. Accurate forecasting must be scientific but also avoid the traps of a host of conceptual and behavioral biases. Moreover, extrapolating from the past to project the future can be of value in charting patterns of behavior but this can also lead to disastrous and inaccurate miscalculations. Forecasting is also decision-making and this is another set of challenges revolving around the accuracy of the information received, the process of reporting, time constraints, and structures of authority and responsibility. Risk analysis – which is a whole field in itself, also be examained. And finally, whether one works for McKinsey or the Direction générale de la sécurité extérieure, predicting megatrends is vital. Avoiding disasterous decisions is a prime focus of this class.

Grading: Class attendence and participation: 30%

Final presentation: 70%

Texts: All readings are embedded in the syllabus and available on-line.

Weekly topics and readings:

Weeks 1 and 2 : Introducing the course

Why forecast?

What can be forecasted

Examples of good and terrible forecasts, or

how could Madoff’s predictions be believed?

Forecasting methods

https://mech.at.ua/Forecasting.pdf

Week 3 “Black Swans” and how to predict the unpredictable (or how to see what is hidden).

https://www.amati-associates.com/black-swans/

Week 4 Upside and downside risks in economic forecasts.

What is positive risk?

https://hbr.org/2009/10/the-six-mistakes-executives-make-in-risk-management

https://www.huawei.com/minisite/explore/en/forecasting_future.html#:~:text=In%20recent%20years%2C%20the%20term,books%20on%20uncertainty%20and%20probability.&text=To%20have%20a%20gorilla%20imagine,on%20this%20in%20the%20industry.

Week 5 and 6 Perceptual bias and biased reporting.

Stakeholders, the bureaucracy, leadership, decision-making.

Cognitive biases

https://www.visualcapitalist.com/11-cognitive-biases-influence-politics/

Week 7

A look at the Pacific Economic Outlook (PEO) report on forecasts

https://pecc.org/resources/publications/regional-cooperation-1/2608-pecc-apec-2020-vision/file

Note: I was a member of the Pacific Economiuc Outlook Japan Committee which prepared a yearly economic projection. This was a sub-ministerial level structure which reported up to the ministerial level.

Weeks 8 and 9 Presentations

Possible presentation topics:

There are a variety of competitions that you can join regarding stock, housing prices,

Stock market predictions

Predicting commodity prices: oil, copper, frozen orange juice, etc.

The housing bubble: a case study

Forecasting the economic recovery from Covid

The Iraq War – decision-making

Simulations and case studies:

ACER Computer Case Study – Slide Share (https://www.slideshare.net/Fabian8a/acer-china-manufacturing)

Air travel demand forecasting: before and after COVID-19 (https://datascience.aero/air-travel-demand-forecasting-covid-19/)

We must also consider the assumption that events proceed in a logical and contained way but the literature on inadvertent escalation leads us to unhappily conclude that circumstances can easily spin out of control despite our best efforts. The outbreak of World War 1 is a prime example.

There are many case studies in how forecasting and risk analysis have failed. Five examples are: 1) The Cuban Missile Crisis is a case study of how easily so-called logical men could have started a nuclear war. 2) The 2008 Financial Crisis. 3) The recent pandemic. 4) Both the Afghan and Iraq wars.

And finally, insurance companies and their actuarial analysts are experts in analyzing date and calclulating the probability of and costs associated with certain events, such as product failure, accidents, property damage, injury, and death.