Resources The code and data for the marketing optimization found below can be found on my GitHub account by clicking here: Background The problem of optimally spending marketing dollars can be formulated in many ways. The goal of this post is to explain how to minimize advertising investment given a minimum communication goal for a given … More Optimizing Marketing Investment to Reach Communication Goals
The goal of this post is to introduce Fundamental Stock Analysis, specifically this post will focus on introducing key financial, operational, and equity based measures to select a handful of stocks out of thousands. The selection process aims to find a small group of stocks that should be considered as invest-able based on their fundamental … More Screening Stocks Based on Value & Optimizing Portfolio to Minimize Variance
INTRODUCTION There are many instances in business where a portfolio of assets must be evaluated in terms of risk and rewards. The key questions may be: “How much should we invest?” “What should we not invest in?” “What is the risk of different budget allocations and what are the expected rewards?” “What is the optimum … More Minimizing Risk in a Portfolio of Assets
Introduction, Data, and Program Measuring the effectiveness of a marketing channel is difficult due to the large amount of variables and other confounding factors. The field of Marketing Mix Modelling was first developed by econometricians to accurately estimate the impact of marketing on consumer packaged goods, since manufacturers of those goods had access to good … More Measuring Marketing Effectiveness: Cobb-Douglas Production Functions
The WordPress.com stats helper monkeys prepared a 2013 annual report for this blog. Here’s an excerpt: The concert hall at the Sydney Opera House holds 2,700 people. This blog was viewed about 50,000 times in 2013. If it were a concert at Sydney Opera House, it would take about 19 sold-out performances for that many … More 2013 in review
One of the difficulties in accessing the quality of an econometric or regression models is determining if any of the key regression assumptions have been violated. Regression analysis contains several key assumptions in order for the results to actually be in accordance with reality. In regression analysis one is trying to measure the impact of … More Outliers: Statistically detecting influential observations in R.