The 1990s and early 2000s witnessed a remarkable technological transformation in financial markets, ultimately leading to significant advancements in transparency and efficiency on a global scale. This era saw a shift towards electronic trading, with terms like “Quants” and “Algo trading” becoming increasingly prevalent. Today, it’s estimated that over 90% of global currency trading is executed by algorithms in some form or another.
Large financial institutions began hiring quantitative analysts, commonly with backgrounds in mathematics, computer science, or even physics. The purpose of these “quants” was and still is to develop systems capable of rapidly pricing financial assets, such as options. Alongside quants, algorithms emerged, enabling automatic or semi-automatic trading activities, such as buying or selling currency.
The result has been a significant reduction in market mispricings, making it increasingly challenging to exploit opportunities for buying low and selling high, as markets tend to already be efficient. This development has been facilitated by two key factors.
Firstly, the widespread availability of the internet means that pricing information for most financial assets is instantly accessible to anyone with an internet connection.
Secondly, the general globalization of capital movements has led to a significant convergence in prices across countries. With more liquid financial markets, even “small” financial markets are swiftly moving towards what are known as efficient markets, where opportunities for profit are scarce.
Similar trends are now increasingly evident in other markets, for example in the Danish retail sector. Danish supermarket chains report that pricing for common items like milk is nearly impossible to differentiate significantly from competitors. Price tests conducted by for example the Danish news site BT often reveal minimal differences between the prices of competing products.
Apps like “beepr” allow consumers in Denmark to track the prices of a wide range of groceries in real-time, prompting supermarkets to closely monitor their competitors’ pricing strategies. While price disparities still exist between supermarkets, there is a clear trend towards reducing these differences. Both consumers and supermarkets can now track price differentials at minimal costs, reflecting a process known as commoditization.
Commoditization refers to the standardization of goods across various sectors, resembling the pricing mechanisms observed in commodities or currencies. However, these changes also present challenges for sectors currently undergoing transformation. The same developments that accelerated in financial markets during the early 2000s are now unfolding in sectors like retail. It’s undeniable that Danish supermarket chains, in the coming years, will increasingly need to think and act like “quants.” It wouldn’t be surprising to see algorithmic pricing strategies emerge in the Danish retail sector, perhaps even for everyday items like milk.
Furthermore, this evolution is poised to be further propelled by artificial intelligence (AI). AI fundamentally functions as prediction engines, and with the cost of making predictions significantly reduced, we’ll witness a widespread adoption of AI in supermarkets. This adoption won’t be limited to logistics but will extend to navigating a grocery market increasingly resembling the foreign exchange market.
Ultimately, the primary beneficiaries of these developments will be consumers. As market standardization and algorithmic pricing become more prevalent, increased competition will drive prices down and lead to better-quality products. Hence, it’s high time for the traditional “merchant” to embrace the mindset of a quant and perhaps consider hiring mathematicians or physicists to implement algorithmic trading strategies, as this is how prices in supermarkets will be determined in the future.
* This article was first published in Danish on my Linkedin profile. See here.
