Articles and News

Practical Time Series Forecasting – Bounding Uncertainty

By KDD | Feb 12, 2018
practical times series forecasting

“A good forecaster is not smarter than everyone else, he merely has his ignorance better organized.” ― Anonymous Predicting the future is an exercise in probability rather than certainty. As we have mentioned several times over the course of these articles, your forecast model will be wrong. It is just a matter of how useful…

Read More

Practical Time Series Forecasting – Meta Models

By KDD | Feb 5, 2018
practical times series forecasting

“There are two kinds of forecasters: those who don’t know, and those who don’t know they don’t know.” ― John Kenneth Galbraith After an extensive model building and vetting process, along the lines we previously discussed here and here, the practical forecaster may still be left with several strong performing models. These models perform similarly…

Read More

Practical Time Series Forecasting – Know When to Roll ‘em

By KDD | Jan 29, 2018
practical times series forecasting

“Prediction is very difficult, especially if it’s about the future.” ― Niels Bohr, physicist Holdout samples are a key component to estimating a “useful” forecasting model. Set aside data at least equal in length to your forecast horizon (“holdout sample”). Build your models on the remaining data (“modeling sample”). And compare the candidate models’ forecast…

Read More

Practical Time Series Forecasting – To Difference or Not to Difference

By KDD | Jan 22, 2018
practical times series forecasting

“It is sometimes very difficult to decide whether trend is best modeled as deterministic or stochastic, and the decision is an important part of the science – and art – of building forecasting models.” ― Diebold,  Elements of Forecasting, 1998 A time series can have a very strong trend. Visually, we often can see it. Gross…

Read More

Practical Time Series Forecasting – What Makes a Model Useful?

By KDD | Jan 15, 2018
practical times series forecasting

“In God we trust. All others must bring data.” ― W. Edwards Deming, statistician So, you have estimated a bunch of forecasting models and realize (kudos to you!) that they are “all wrong” (ala George Box). But your forecasting deadline is looming, and you need to find some useful models on which to base a…

Read More

Practical Time Series Forecasting – Know When to Hold ‘em

By KDD | Jan 8, 2018
practical times series forecasting

“The only relevant test of the validity of a hypothesis is comparison of prediction with experience.” ― Milton Friedman, economist Holdout samples are a mainstay of predictive analytics. Set aside a portion of your data (say, 30%). Build your candidate models. Then “internally validate” your models using the holdout sample. More sophisticated methods like cross…

Read More

Practical Time Series Forecasting – Data Science Taxonomy

By KDD | Jan 2, 2018
practical times series forecasting

“Big data is not about the data.*” ― Gary King, Harvard University (*It’s about the analytics.) Machine Learning. Deep Learning. Data Science. Artificial Intelligence. Big Data. Not a day goes by that one or all of these buzzwords stream past in our business news feeds. Data analytics has become mainstream. And you better jump on…

Read More

Practical Time Series Forecasting – Potentially Useful Models

By KDD | Dec 18, 2017
practical times series forecasting

“All models are wrong, but some are useful.” ― attributed to statistician George Box This quote pretty well sums up time series forecasting models. Any given model is unlikely to be spot on. And some can be wildly off. But through a careful methodical process, we can whittle the pool of candidate models down to…

Read More

Practical Time Series Forecasting – Some Basics

By KDD | Dec 11, 2017
practical times series forecasting

“The long run is a misleading guide to current affairs. In the long run we are all dead.” ― John Maynard Keynes, A Tract on Monetary Reform Forecasting the future is an exercise in uncertainty. And the further out one looks, the more uncertain the forecast becomes. Most businesses are keenly focused on the next…

Read More

Practical Time Series Forecasting – Introduction

By KDD | Dec 4, 2017
practical times series forecasting

“The only thing I cannot predict is the future.” ― Amit Trivedi, Riding The Roller Coaster: Lessons from financial market cycles we repeatedly forget It goes without saying that every business is keenly interested in knowing what the future will bring. Will sales grow next year? By how much? Will suppliers increase their prices? How…

Read More

How can we help you?

Drop us a line today, we would love to chat!