We've built an econometric model (VAR) to identify leading indicators. Vector autoregression is a workhorse model in macroeconomics that defines each indicator as a function of other indicators. This way, instead of treating each indicator’s impact separately, the model captures interactions between them and their influence on your sales.
By using a lasso penalty through cross-validation, we ensure that only the relevant indicators are represented, delivering the most accurate results.
Forecasting and planning based on historical data and assumptions are no longer sufficient to help your organization meet the challenges that come with volatility.
By conducting a scenario testing, you put sensitivity bounds on your forecast's range,
giving you a clear picture of how extraneous macroeconomic factors and
future assumptions may affect the organization's forecasts.
What-if series
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You've got your baseline numbers calculated for each variable. What if inflation goes up? What if the dollar strengthens?
By identifying specific volatile variables that you suspect could have an impact on your forecast, you can analyze its movement under different scenarios.
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Tweak not just one or two. You have the option to adjust multiple variables simultaneously at each given time range.
By leaving all other variables unchanged, you can conduct a sensitivity analysis and view the impact of the adjusted variable.
You've got your baseline forecast. With the capacity to monitor each and every variable, you get to play out specific scenarios, both pessimistic and optimistic. This gives you the control and capacity to prepare for these situations.
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We are an automated forecasting software that bridges the latest statistical models from academia with the specific leading indicators in an organization's market environment. Helping your organization achieve the highest forecast accuracy.
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