Next-Generation Investment Research, Today

Last updated on May 14, 2025

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By Investors, For Investors

By Alex King, CEO, Cestrian Capital Research, Inc.

This note is an important one and concerns itself with current breakthroughs in investment research methodologies and the price/performance ratio available to investors and traders.

But first of all, let’s define “investment research” for these purposes.

When we use the phrase here at Cestrian we first of all mean buyside investment research. The kind that we produce here. And what we mean by buyside is that we take the perspective of those managing capital and therefore buying research one way or the other (be that via direct subscription or through soft-dollars like brokerage fees, etc). By contrast when we talk about the sellside we mean the perspective of those issuing securities; this perspective shows up in investment bank analyst notes where the paying customer is, one way or the other, the underlying company or ETF issuer.

And “investment research”? What exactly is that? Well, it can take many forms, from wearing out the shoe leather trudging from store to store to see what is selling and what is not selling, to analyzing financial statements, to drawing charts and beyond. For us the means is less important than the end which is: producing opinions that the buyside – actual investors – can use to assist their investing and trading decisions.

I think we can talk about, broadly, three types of investment research which developed more or less in a serial manner over time. The methods used in these periods are cumulative in their power; as human and machine knowledge of how to more successfully invest and trade piles up there is no need for us to abandon what has gone before in pursuit of the new for novelty’s sake. But neither should we remain rooted in the past for the sake of nostalgia or as a form of worship to false gods.

(1) Fundamental Analysis.

Fundamental analysis is the most intuitive form of investment research. It seeks to better understand the health of the underlying companies that issue securities. The authoritative work on this method remains, I think, Securities Analysis by Graham & Dodd; I favor the Sixth Edition with the foreword by Warren Buffett. This is a large tome and it takes commitment to read; whilst plowing through it you may question why this or that railroad preferred stock or municipal bond from yesteryear could help you with making money from Nvidia today. But if you find yourself thinking that, you’ve missed the point. Fundamentals are, at some level, alwaysrelevant even if only in edge cases. And understanding how to do fundamental analysis correctly will help you spot the edge case on the horizon well before most other investors in the market.

(2) Technical Analysis.

Technical analysis is counter-intuitive and argues that securities pricing is largely a function of securities pricing; that price is a closed system where endogenous factors drive change. The altar of technical analysts is the stock chart, its motif is pattern recognition, and its high priests range from R.N. Elliott to Leonardo Bonacci to John Bollinger, Richard Wyckoff and many more. Technical analysis is, when carried out by a skilled practitioner, very effective in determining optimized entry- and exit points for securities. It works best with large liquid names where crowd psychology can be observed in price patterns. Ultimately all forms of technical analysis can be collapsed into one statement which is that they seek to measure and predict the ebbs and flows of human fear and greed. For this reason despite radically different input methods, it is often the case that multiple technical analysis systems reach broadly similar conclusions on entry and exit prices. Technical analysis is in essence seeking to codify emotion. Investors who believe this is mere voodoo are either wilfully ignorant, lack the patience to learn the craft, or psychologically unable to accept that securities pricing may be unrelated to anything going on at the issuer of those securities. For anyone seeking to learn the basics of why technical analysis works – specifically the notion that price is often endogenously generated – my preferred text is Prechter, Socionomics.

(3) Quantitative Analysis.

Quantitative analysis is another approach based on the notion that securities pricing is only incidentally related to the goings-on at the underlying issuer of those securities. It seeks to use purely numerical methods to understand the likely direction of securities prices.

Quantitative analysis takes many forms but for our purposes we can think about (1) order flow analysis, wherein the real-time bid/ask prices and volumes of orders at each price level are observed and measured; (2) options market analysis, where the order flow of derivatives is used to analyze the potential impact on the underlying security; and (3) statistical analysis of price and volume patterns in the security in question in a bid to identify numerical pattern recognition in the same way that technical analysis seeks to identify visual pattern recognition. Pattern recognition is useful insofar as price patterns have a tendency to repeat constantly, since they are the product of the repeating fear and greed of the humans driving the market (directly or via trading algorithms written, in the main, by humans).

So now that we have a rough schema for the various subtypes of investment research, I want to talk about the brutal deflation that technology has delivered to the cost of such work.

Deflation Of Investment Research And The End Of The Guilds

Technology, as you know, destroys every industry it touches. This has been true since at least the Industrial Revolution but the devastation of this particular tsunami really took a step up when the Internet became usable by normal people in around 2010. By then, broadband access networks had become functional and developers were learning to write applications that could scale across the wide area network without too much difficulty.

Today you pretty much never want to be on the wrong side of the Internet. If today your industry remains largely offline or primarily manual with computer-assist, buckle up, because that is a temporary state of play; and the remaining time you think you have before the machines come for you is an overestimate.

Within investment research, what is now available instantly to almost anyone was once the exclusive preserve of high-end investors with and large budgets. That guild, like so many others, has been destroyed by the Internet.

Fundamental Analysis: where once Mr. Buffett had to peruse textbooks of historic market prices and locate company annual reports in person, today this can be achieved at low cost by using Ycharts.com, Finchat, Koyfin, even Yahoo Finance.

Technical Analysis: no longer do you need a chart room on a trading floor staffed by people with technical drawing skills and decades of finance experience. You can start to learn technical analysis for free with TradingView or Barchart, and if you want the machine to assist, you can pay TrendSpider very modest sums to help you with that.

Quantitative Analysis: The final frontier. This domain has been protected until relatively recently. If you were to visit Renaissance Technologies, D. E. Shaw or the other quant titans, you would find a degree of computing power more commonly found in high-end scientific research environments. These firms were founded at a time when it seemed that more data feeds, more diversity of data sources, and more ways to find correlations between datastream X and securities price Y was the way to go. This meant that the budget for computer hardware, data feeds, quantitative analyst resource, and telecom, was extraordinarily large. Now, whether as a result of method, budget, or both, this proved very successful for the top quant firms. Renaissance is said to have achieved a consistent 60% annual return on their core Medallion fund (not open to outside investors for a very long time). But you have to remember that the manager chose to run that fund at an average of 6x leverage; that means you cannot assign that kind of killer returns to the research alone. On an unlevered basis, the Medallion fund might have returned say 10-15% pa, still very good over a long period of time but not quite as headline grabbing. Today, if you have the skill to do so, you can build your own quantitative models using cloud infrastructure (read – supercomputing resources that you have not had to build yourself). The extraordinary power of GPU-based systems makes that possible at a cost level unimaginably low even five years ago. Quantitative analysis is always going to be more difficult to do well than just reading a balance sheet or spotting geometric patterns on a stock chart. But it is no longer the exclusive preserve of ex-IBM Cornell Ph.D. types.

So What

So what? The so what is, if you want to try to make returns akin to a quant fund then you can now simply subscribe to quantitative analysis that our independent analysts produce.

We have constructed these quant services to be extremely simple to use. Each service produces a signal once per day. We offer single-ticker services covering, eg. $SPY, $BTC, and so on; each day the signal is 1 (Risk On) or 0 (Risk Off). Risk On means the model believes that there is limited risk of a decline in that ticker; Risk Off means the model believes there is material risk of decline.

Our subscribers use this information in different ways. Some follow the signals directly ie. they buy the instrument when the signal flips from Risk Off to Risk On, and sell it when there is a flip from Risk On to Risk Off. Some use the signal to help them understand the background risk environment within which the market is working at that moment.

We also offer long/short index signal services, and rotation services wherein the model selects 1-3 ETFs to own from a menu of 12-15 that it tracks.

We will be expanding our quant offerings over time. We believe that the future of investment research is already here, and it is to combine machine-led research with human-led research. This is how staff personal capital is invested and traded at Cestrian and it is how, we believe, any prudent investor should operate today.

Get Some

To learn more about our human-led research, read all about our Inner Circle service, here.

To learn more about our machine-led research?

You can read about our SignalFlow AI family of services here:

And you can read all about our YX Signal family of services, here.

As always, any questions, reach out using this form on our website. Thanks for reading our work!

Cestrian Capital Research, Inc – 13 May 2025.