Pain of Payment for … the First Date
This concludes the interview with Professor Avni Shah regarding consumer behaviour and the connection we feel to the stuff we buy. And, possibly, to the people we buy it for. Click here to read the first half of the interview. Q: Did you look at other aspects of the connection? I said, let’s see how long this effect persists. I got data for the years 2004 to 2013 from an alumni association. What I was interested in is how alums make donations: by cheque versus card. Cheque feels more painful because you have to write out that amount. I wondered […]
Pain of Payment for … Coffee
“Me? Why do I have to pay for the falafels? I barely have two dollars to rub together,” said Morty. Tuesday is the two-for-one special at our local take-out Mediterranean shop. “Take it from me—you’ll enjoy them more!” I said, tapping the article I had just been reading in the New York Times. In a nutshell, it reported on new research in the Journal of Consumer Research that said having some difficulty in payment increased the consumer’s connection with the item purchased. He grabbed the section to read while we wolfed down our falafels. “You’ve gotta interview these people,” he […]
Data Science 2. The Roadmap
“The core concept for data science is hypothesis testing,” said Nima Safaian, team lead for Trading Analytics at Cenovus Energy. The data scientist must identify trends, generate hypotheses, and test, test test. The scientist’s bent toward hypothesis testing should be even stronger than their math skills. Safaian was speaking at the Data Science webinar on August 2, 2016, sponsored by the Global Association of Risk Professionals (GARP). “Attitude is everything,” Safaian said. “Think like a startup. Have an agile mindset,” he urged, referring to the books The Lean Startup by Eric Ries and The Lean Enterprise by Humble, Molesky, and […]
Data Science 1. Trading Analytics
At the end of the day, what do you produce? If you are a knowledge worker, your “product” could be something as intangible and significant as decisions. That is the thinking behind the “decision factories” discussed in Roger Martin’s seminal Harvard Business Review article. If we labour in decision factories, then we are decision engineers, and our chief raw material is data, according to Nima Safaian, team lead for Trading Analytics at Cenovus Energy. “We need the capacity to produce many good decisions,” he said at the webinar on August 2, 2016, sponsored by the Global Association of Risk Professionals […]
Fast Turnaround of Complex Math
Imagine you are driving your brand-new mini-van, the latest Drake album cranked on high, the windshield wipers at top tempo, and the heater keeping things toasty. You go to switch the headlights to high-beam—and you are suddenly hit by the unmistakable odour of melting circuits…. Not a happy situation. It’s one that automotive designers the world over try to avoid by extensive testing of many different usage scenarios. Problem-solving tools have dramatically changed the way engineers advance their knowledge, for financial, automotive, chemical, and other sectors. Many products and technologies we take for granted—such as the electronic circuitry in a […]
Worst Case Analysis Made Easy
Can symbolic computing improve real-world design? Definitely yes, according to the product development team at the automotive firm Delphi. “Each time the circuits were changed, the electrical equations changed. We turned to symbolic computing so that we could quickly deal with design changes,” said Michael G. McDermott, Senior Development Engineer at Delphi. He was the second speaker in a webinar on May 25, 2016, titled “How Far Can Your Math Knowledge Go?” Lights, heating, movies for kids in the back to watch… Over time, vehicles have come to have more and more elaborate electronics. These can lead to unpredictable stresses […]
The Case for Symbolic Computing
Should you care about symbolic computing? If your work involves concepts that are expressed in math, and if you want to reduce errors and routine work, then Samir Khan says, yes, you should. Khan, Product Manager at Maplesoft, was the first speaker in a webinar on May 25, 2016, titled “How Far Can Your Math Knowledge Go?” “Symbolic computing allows you to automatically derive system equations using well-defined rules,” said Khan. “It allows you to mechanize your work with equations, such as the routine manipulations that are done in algebra.” The traditional design process means the designer (or engineer or […]
War, Kidnapping, Data Theft
War, kidnapping, and data theft: Is it some fiction pot-boiler that’s come over the transom? No, it’s the chapter on how the gross domestic product (GDP) came into being in Germany. Today’s excerpt comes from pages 117-8 of the book The Power of a Single Number: A Political History of GDP by Philipp Lepenies, translated by Jeremy Gaines (Columbia University Press, 2016). “[John Kenneth] Galbraith was surprised by the results of his calculations and surveys because they, for the first time, provided a clear picture of the Nazi economy. Because no set of tools comparable to gross national product calculation existed on […]
Platform of the Future
What will be the ideal modelling platform of future bankers? It will need to contain key functionalities in model execution, scenario management, and a “risk engine” that will deliver answers for multiple horizons at the loan level. Furthermore, it should implement the most advanced modelling suites, reduce the quants’ time to develop models, and contain simulation capabilities for stress testing and beyond. This bold vision of the future was presented by Martim Rocha, Advisory Business Solution Manager at SAS. He was the second of two presenters at the February 25, 2016, webinar offered by the Global Association of Risk Professionals […]
Integrated Data and Modelling
How can today’s bankers prepare for tomorrow’s challenges? Consider the financial models built using available data. Data collection and financial modelling used to be conducted in each different silos of the bank, with credit separate from market, which was separate from treasury and other groups). Then data became “managed” and modelling was moved to “platforms” which did not mix well between the various silos. A few brave souls began to integrate the data management for different groups of the bank. Other brave souls tried to integrate the modelling. This was the phase of integration achieved through batch calculations. Now, the […]