No-code is coming to the investing world

No-code is coming to the investing world

For the first time since the advent of the Excel spreadsheet, the playing field is leveled.

IA Fintech Member Insights: Jacobi

Tony Mackenzie, CEO & Co-Founder — Jacobi


Spreadsheet interrupted

A wise and retired portfolio manager once told me about the way in which Microsoft transformed the investment world in the late 80’s. As spreadsheets took hold, the role of traditional investment research disrupted. Analysts could suddenly create their own tools and models to assess “fair value” for equities, bonds and other assets.


Through the 90’s, every analyst become an expert in Discounted Cash Flow (DCF) modelling in pursuit of the “intrinsic value” of securities. Yet as time went on, DCF models lost their shine – any market advantage from that analysis evaporated. Markets were efficient after all, well mostly.


Three decades on, the investment world is in the midst of a new disruption. Modelling methods have evolved and talk of algorithmic trading, Artificial Intelligence (AI) and automation dominate investment media. Yet despite this, a labyrinth of spreadsheets remain in many organisations. And while spreadsheets are useful for doing individual bits of work, they are a barrier to integrating processes and they don’t resolve today’s desire to automate. Finally, there is growing realisation that spreadsheets are not scalable.
Python is the new spreadsheet


As a result, Python is now the buzz tool in the investment world. As a relatively intuitive coding language, Python allows users to perform mathematical analysis and integrate this with different types of inputs and outputs. It can be used to interrogate data, create models or automate tasks. It is also the common coding language that underpins many AI trading applications and is the backbone of shiny new tools entering the investment world. Being taught at universities and championed by investment firms, seasoned industry professionals are now warning that we must each learn to code in Python or risk becoming redundant. But we disagree.


Not everyone needs to be a coder

Beyond the Python trend, a more fundamental disruption is taking place. The models, math and statistical methods that underpin coding languages are becoming ubiquitous. Despite all the talk about AI and quantitative investing, there is a risk that models become somewhat commoditised.


Free source code libraries mean that many of the most complicated financial techniques are now freely accessible. And the gap between academic research and industry application is also closing – code behind any new innovation in academia can be rapidly created, copied and deployed by investment firms.


With that in mind, value in the future will lie less in the ability to write code, but rather the ability to join dots – that is, to bring together disparate bits of information, data, models and processes. Think conducting the orchestra, rather than playing an instrument. The winners will be “conceptualizers”, not number-crunchers.


A “no-code” revolution is brewing

To empower that, a new technology trend is entering the investment world: “no-code”. No-code refers to systems in which non-coders can build and create tools, systems and applications. It’s actually nothing new. Spreadsheets themselves are an early form of no-code. For example, the formula bar which allows someone with limited mathematical grounding to perform complex analysis at the click of a button.
In future, all investment workers will need a much wider mix of tools at their disposal. And while many investment firms are encouraging greater use of Python among workers, few are focusing on where that all lands. Most important will be platforms that allow non-experts to better interact with investment data, models and tools.


In the same way that spreadsheets made all analysts an expert in DCF models in the 90’s, a no-code world will make all investment professionals more proficient in quantitative approaches. No doubt some quants will be horrified at the thought of non-quants leveraging their models. However, they should see it as an opportunity to get their unique insights more widely applied, adopted and understood.


To learn more about how Jacobi works with asset managers, owners and consultants to solve investment technology challenges, visit

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