Utilizing scenario analysis effectively can increase your chances of building resilience, particularly during market turbulence. Additionally, by doing this, you can add some level of nuance to your forecasted data, increase planning flexibility, add safety nets to your plans, and lessen the impact of market fluctuations.

In this case, our focus is on the registration of passenger cars in the EU, and we're looking at the potential consequences it would have on the forecasted registration volumes if these variables change.

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Passenger car registrations tend to move together in line with the changes in the consumer confidence index, interest rate, and consumer income. In this scenario, we’ll be using the #VAR models with #Lasso effects used in Indicio to provide us with a clear indication of which variables are the most meaningful to this forecast.

The ones that prove to have the most significance are: economic consumer sentiment, retail trade confidence indicator regarding the sale of motor vehicles and global semiconductor sales.

Next, we established a baseline with the use of univariate models. The calculations landed at 833.9K (using the Theta model) and 843.3K (using the STL model), respectively.

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Next, we applied the multivariate models 

Here we see an uptrend with 716.711K passenger car registrations in January which represents a 5% YoY increase compared to January 2021.

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‍*It’s good to keep in mind that if you’d like to run a scenario analysis, it’s necessary to have at least 1 valid multivariate model built. In this case, Indicio has built 35 models composed of 13 leading indicators on data from 2003 to 2022.

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In Indicio, we can tweak the variables accordingly and not only get an indication of not only how it would impact the forecasted numbers, but also a clear overview of its relationship with the other variables.

Let’s throw in our first scenario: 

The price of Brent crude oil is still well below the highs we saw in Q1 2022, but just earlier last week, its price rose by almost 2%. What is the impact of this on passenger car registrations should it increase by another 0.5%? Let’s play out this increase by making an adjustment under the scenario simulation tool in Indicio.

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What happens if the retail trade confidence indicator peaks further north by 0.10 points from January’s forecasted results, what effect would this have on passenger car registrations??

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Or if the economic sentiment indicator peaks just slightly by 0.5 points?

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What happens if global semiconductor sales goes on an upward trajectory in a longer horizon? 

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The short-term outlook for semiconductor revenue looks set to be negative, attributed to weakened consumer demand. However, for those preparing for longer-term tactical planning, that piece of information is a variable that’s worth taking into consideration.

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By adjusting all of these variables accordingly in a new scenario, we get an immediate preview of its forecasted impact:

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Now, with these three scenarios at play, we posit that the models selected, in particular the VAR models forecast that the passenger car registrations will come in at 716,693K for January 2023, which represents a 5.1% YoY increase compared to January 2022.

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‍*It’s good to keep in mind that if you’d like to run a scenario analysis, it’s necessary to have at least 1 valid multivariate model built. In this case, Indicio has built 35 models composed of 13 leading indicators on data from 2003 to 2022.

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In Indicio, we can tweak the variables accordingly and not only get an indication of not only how it would impact the forecasted numbers, but also a clear overview of its relationship with the other variables.

We pay special attention to the out-of-sample data to validate our findings. This is important to ensure that we are not overfitting our data to any market noise. 

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*A good guideline is taking a quick look at whether your out-of-sample accuracy error (using RMSE as a measure)  is lower than your in-sample data.

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These are just some relevant examples of what you can do with the scenario analysis functionality. By having the capacity to optimize plans as often, and to do so in any specific time horizon is valuable towards preparing for stability in unstable times.

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