“I have always looked for an advantage or an edge in markets, and I still do,” says Peter Warren. Over more than four decades in markets, that search has taken him from early technology-driven arbitrage in metals to options market-making, hedge fund management and systematic trading. Along the way, he has seen market edge shift from trading floors and manual calculations to data, models and computing power. 

One of Warren’s first market edges came with a handheld calculator. In 1980, while trading metals, he programmed a Texas Instruments calculator to calculate the cost of carry on LME-warehoused copper against the forward price. The program gave him a small but profitable speed advantage over traders doing the same calculations on paper. 

Before Data Was Abundant 

Before systematic trading became associated with large datasets, advanced algorithms and infrastructure, Warren recalls that obtaining usable data required “great difficulty and loads of labour.” At the time, datasets were not readily available, meaning traders had to collect, structure and analyse information themselves. “But that said, if you got compute in any form, you were a bit quicker than people around you. So, you were rewarded for the effort,” Warren notes. This readiness to build the data and tools he needed would remain a recurring theme in Warren’s search for market edge. 

Two years later, in 1982, Warren created what he describes as the first database of stock prices in Norway, allowing him to conduct time-series analysis on the local market. That approach later carried into options. In 1987, Warren built the first options market in Norway, including a functioning clearing system. With insight from leading firms in the U.S. options market, including Timber Hill, Susquehanna, CRT and O’Connor, Warren acted as a market maker for 12 years while continuously improving systems designed to identify arbitrage opportunities.  

The early use of data and technology did not remove the human element from markets. While these tools gave Warren a way to analyse markets more systematically, execution still took place in an environment shaped by brokers, pit traders, reputation and psychology, as well as the flow of information. 

From Testosterone to Data

Warren describes the markets of that era as more “testosterone-driven than data-driven.” Data and analysis were gaining ground, but trading still took place in a physical and often noisy environment where reputation and psychology could influence short-term market behaviour. 

Execution itself could become a source of information leakage, as orders often had to pass through multiple people before being filled, exposing information to pit traders and other market participants. “The more predictable you were, the more of a liability it became, as pit traders front-ran orders all the time,” Warren explains. As a result, managing how orders were executed became a key component of protecting the edge itself. 

Warren argues that one of the misunderstood aspects of that era was the role of reputation. In the short term, reputation could move markets more than capital, as certain traders were able to shape behaviour simply because others knew their names, trading styles and willingness to take risk. Being right on the underlying market was not always enough. “It did not matter if you were right in the long run, they would kill you in the short run because they had that power,” Warren recalls.

The shift toward a more data-driven market became increasingly visible to Warren in the 1980s, particularly when he first walked into the Chicago trading room of O’Connor, one of the U.S. options firms that had influenced his approach to technology and market-making. Used to noisy dealing rooms and trading floors, he recalls being struck by the silence of a room dominated by screens and computers. The contrast captured how markets were beginning to move away from trading-floor culture and reputation, and toward data, models and technology. Warren does not describe himself as a quant or developer. Instead, his role was often to work with people who had those skills and could challenge and improve his ideas. One of them was Øyvind Tvilde, a quant and former colleague, who recently said on a conference call: “I am a better quant when I work with Peter.” Warren adds, “I was genuinely touched by those words.” 

The Shorter Life of a Market Edge 

Across Warren’s career, the search for a market edge has remained constant, but the time available to exploit it has narrowed. The half-life of a market edge has generally shortened over time, he argues, as compute and speed have made it easier for others to identify the same opportunities. “Whenever you think you found the holy grail, you will enjoy that for shorter and shorter periods of time before somebody else is onto it,” Warren explains.

At the same time, the opportunity set has broadened. Warren recalls being struck by the number of markets that firms such as Renaissance Technologies, a quantitative investment firm, were able to analyse and trade, a sign of how compute and data were expanding the scope of systematic strategies. As data became cheaper and market coverage widened, the industry moved further away from what Warren describes as “the world of testosterone-driven traders” and toward what he fondly calls “the world of the nerds,” where mathematics, statistics and technology increasingly became the primary drivers of market edge. 

Whether in earlier market eras or today, Warren sees curiosity as the most important trait of any trader. “Everything changes, so you need to be curious. That’s the only way to stay ahead of the game,” he explains. Curiosity alone, however, is not enough. As edges fade and market conditions change, Warren also stresses the importance of humility, particularly in a field where conviction can turn into overconfidence. “If you think you are going to be right every time, you’re going to have a very short career,” Warren notes.

Execution Still Defines the Edge 

Since Warren’s early years in markets, execution has shaped whether an edge could actually be captured. In earlier markets, execution itself could give away information to pit traders and other market participants. Today, the mechanics have changed, but predictable behaviour can still be detected and exploited. Warren points to high-frequency and medium-frequency traders analysing order books for patterns, making execution a continuing part of protecting market edge. 

This makes liquidity and timing central to implementation. For Warren, this typically translates into activity around the opening of the U.S. market, when liquidity and order flow can create more favourable conditions. If analysis shows that the vast majority of profits are generated within a narrow time window, Warren argues that traders should question the need to remain active outside that period and instead focus on the window where the edge is strongest.

The challenge of protecting and developing an edge begins in the research process. Warren points to overfitting as one of the most common pitfalls in systematic trading. “There’s an old saying: I’ve never seen a backtest that’s lost money,” he notes. The risk of overfitting does not weaken the case for data, but rather raises the bar for how data is used. Warren points to a remark by Leda Braga, CEO of the systematic investment firm Systematica Investments, asking, “How can you make decisions without data?” Warren adds that “we did this on gut feeling in the old days, but you would be in peril if you tried this today.” 

For Warren, the lesson from decades in markets is clear: systematic does not mean static. Models, data and computing power should help traders adapt faster as markets change. “Charles Darwin said it was not the strongest or fastest that survived. It was the one that had the ability to adapt,” Warren notes. The same applies in markets, where edges fade, conditions shift and assumptions must constantly be tested.