Written by: CoolFish A company with 3,000 employees earns more than Citibank and Bank of America. It doesn't advertise, has no CEO, and doesn't have non-competeWritten by: CoolFish A company with 3,000 employees earns more than Citibank and Bank of America. It doesn't advertise, has no CEO, and doesn't have non-compete

Who exactly is Jane Street?

2026/02/26 14:49
20 min read

Written by: CoolFish

On February 24, Terraform liquidators filed a lawsuit against Todd Snyder, who is also suing high-frequency trading giant Jane Street. The lawsuit accuses Snyder of using insider information to trade illegally and ultimately accelerate the collapse of Do Kwon's crypto empire.

Who exactly is Jane Street?

Although Jane Street denied the allegations, calling them baseless, market attention has already begun to turn to the company. At the same time, a Jane Street intern recruitment ad surfaced on Twitter.

The screenshot shows that the company is recruiting quantitative trading interns with a 4-month contract and a base salary of $300,000. Crucially, they don't require a financial background or programming experience; they only ask one thing: Can you solve problems?

I was genuinely surprised when I saw the salary and requirements. Who exactly is this company? Are quantitative intern salaries really this high? How does it make so much money? And what role does it play in the global financial market?

These questions deserve serious answers.

Because once you peel back the layers of secrecy and truly understand this company, you'll realize one thing: Jane Street's very existence is an extreme experiment about information, speed, and the boundaries of rules.

Its name rarely appeared in the news until it appeared in the dock .

A small, windowless hut and four gamblers

New York, 1999.

Three traders who left Susquehanna International Group (SIG), along with a programmer who jumped ship from IBM, rented a small, windowless office and started a business that most people would scorn: ADR arbitrage.

ADRs, or American Depositary Receipts, are stock certificates of foreign companies traded on the U.S. market. Theoretically, their price should be consistent with the original shares listed in the home country. However, time zone differences, exchange rate fluctuations, and information delays can create tiny gaps between the two. The four founders of Jane Street—Tim Reynolds, Robert Granieri, Michael Jenkins, and Marc Gerstein—focused on these gaps, trading algorithms and speed for profits.

This business is almost devoid of color: it has no grand narrative, no ambition to disrupt the industry, only an extreme sensitivity to numbers and a morbid pursuit of execution.

According to research firm Alphacution, the company may have initially registered under the name "Henry Capital," and changed its name to Jane Street in August 2000. They maintained an almost obsessive level of secrecy towards the outside world.

This kind of obsession seems to have been part of the company's DNA from the very beginning.

Of the four founders, three came from the same company and left to start their own business. Susquehanna even sued Jane Street for "stealing proprietary information and poaching key talent"—although the lawsuit ultimately fizzled out. This sensitivity may have profoundly influenced how Jane Street subsequently handled its strategic secrets: no media interviews, no industry conference speeches, and no unnecessary exposure.

They quietly did their homework in that small, windowless room.

ETFs: The Bet That Changed Everything

At the beginning of the 21st century, Jane Street made a decision that would later prove to change everything: to focus its main efforts on ETFs, which were still a niche market at the time.

ETFs (Exchange Traded Funds) were relatively niche products in the early 2000s. They had low liquidity, few participants, and large institutions found them inconvenient to enter and exit, so they generally avoided them. But it was precisely this "unwanted" situation that made it Jane Street's ideal hunting ground.

Market makers are the core logic of this game. Market makers simultaneously post both bid and ask prices, ready to execute trades with any counterparty and profit from the bid-ask spread. While it sounds simple, it requires precise asset pricing at the millisecond level, managing massive inventory risk, and maintaining continuous operation in a global market.

Jane Street did this using algorithms, and did it quickly and accurately.

What followed was one of the classic "choosing the right track" stories in history.

ETFs experienced explosive growth over the next two decades, expanding from hundreds of billions of dollars to tens of trillions of dollars, with institutions, retail investors, and pension funds flocking in. Jane Street has become one of the most indispensable infrastructures in this market.

3,000 people took down Citibank and Bank of America.

There are some figures that can give you a direct sense of Jane Street's earning power.

Jane Street's net transaction revenue in 2024 was $20.5 billion.

In the same year, Citigroup's trading division had net revenue of $19.8 billion. Bank of America's trading division had net revenue of $18.8 billion.

Jane Street won by a margin of $700 million over Citigroup and by a margin of $1.7 billion over Bank of America.

This is an almost abnormal level of efficiency.

Source: MSTIMES

By 2025, the data will be even more astonishing. According to Bloomberg and other reports, Jane Street's net trading revenue in Q2 2025 will reach $10.1 billion, surpassing all major Wall Street banks. Its total revenue for the first three quarters of 2025 will reach $24 billion, exceeding its total revenue for the entire year of 2024...

Compare these figures to industry benchmarks: Citadel Securities had approximately $9.7 billion in trading revenue in 2024, Virtu Financial approximately $2.9 billion, and Flow Traders approximately $500 million. Jane Street lags behind its competitors by at least two times.

Beyond scale figures, there are also market share metrics that can help you understand just how deeply this company has penetrated the market:

In 2024, Jane Street held a 24% share of the primary market for ETFs listed in the United States, 41% of the trading volume of bond ETFs, and 17% of the secondary market for ETFs in Europe. Its average monthly stock trading volume reached $2 trillion, and it accounted for approximately 8% of all trading volume in the US options market and over 10% of North American stock trading.

In other words, every time you, your fund, or your pension buy or sell an ETF, there's a very high probability that the counterparty is Jane Street, and you might not even be aware of its existence.

OCaml, the puzzle, and that real war machine

Jane Street's headquarters are located at 250 Vesey Street in Manhattan's Financial District. Inside the office, there's a genuine World War II-era Enigma encryption machine—the kind Nazi Germany used to encrypt communications.

This machine is not just decoration; it is a declaration.

This company loves encryption, puzzles, and building its own world using a language that only a select few can decipher.

The programming language for Jane Street's core trading system is OCaml.

OCaml is a functional programming language known for its strong typing system and logical rigor, but it's used by virtually no other companies in the financial industry. As of 2023, Jane Street's OCaml codebase exceeded 25 million lines—the Financial Times notes, roughly half the size of the Large Hadron Collider's codebase.

This choice may seem odd, but it has profound engineering logic: in financial trading systems, a single line of code bug can cause losses of hundreds of millions of dollars. OCaml's type system forces the elimination of a large number of potential errors during the compilation phase, making it much harder to write code that crashes at runtime than in C++.

A side effect is that engineers who have worked at Jane Street are often difficult for other companies to "swallow" because of their proficiency in OCaml. As one headhunter described it, "People stay at Jane Street because they love it, but also because no one can poach you with OCaml skills."

This creates an unexpected moat: the technology stack binds talent .

It's worth noting that Jane Street does not have a CEO.

There is no hierarchical bureaucracy, no management levels, and no familiar financial industry titles like "Vice President" or "Managing Director."

The Financial Times described it as: "An extremely profitable anarchist commune."

The company is comprised of 30 to 40 senior employees who make decisions collectively and operate through a management committee and a risk committee. These 40 individuals hold approximately $24 billion in equity and run various trading desks and business units, but they are not called "presidents"; they are simply—owners.

All employee compensation is linked to the company's overall profits, not to individual trading performance. This means that no one will take excessive risks for their own bonus, because losses are shared by everyone, and wins are shared by everyone.

In 2024, Jane Street paid $1.4 million in compensation to its approximately 3,000 employees.

That screenshot of a Jane Street internship recruitment ad wasn't a marketing gimmick, but rather Jane Street's consistent self-perception: they weren't looking for financial experts, but rather "people who enjoy solving interesting problems."

"The interview process is notoriously difficult." Candidates are required to solve probability problems, game theory problems, and expected value calculations under pressure, which tests their underlying logical abilities rather than industry knowledge. According to the company, only a "very small percentage" of applicants are invited to the interview stage.

The company does not use non-compete agreements—a rare exception in the financial industry, where signing non-compete agreements for departing employees is almost standard practice. Jane Street believes that its competitive advantage lies not in a particular algorithm, but in the culture and capability density of its entire system, which cannot be easily replicated.

A veteran hedge fund quantitative analyst pointed out that Jane Street is a trader's paradise, while Citadel Securities is more suitable for quantitative analysts and developers. "Jane Street is trader-oriented, while Citadel Securities is more systematic," he explained. "Traders are more sociable, which is why Jane Street has a relaxed atmosphere and a strong poker culture."

Michael Lewis, author of the SBF biography *Going Infinite*, recalled that when SBF was still on Jane Street, its trading floor retained a "sound system": different prompts corresponded to different trading statuses. There was Homer's "D'oh!" from *The Simpsons*, the 1-Up sound effect from *Mario*, and even the famous line from the 1998 strategy game *StarCraft*, "You must construct additional pylons."

Noise was everywhere. Some even thought the trader they were talking to was playing video games because the noise was so loud.

This relaxed yet deliberately eccentric atmosphere is a cultural marker they deliberately maintain while operating at full capacity.

SBF and Election Night 2016: From the Most Profitable to the Most Losing in History

In 2014, a young man who graduated from MIT joined Jane Street with a starting salary of $300,000.

His name is Sam Bankman-Fried, and he is known as SBF.

He later built FTX, then destroyed it himself, for which he was sentenced to 25 years in prison. But before that, his three years on Jane Street left behind one of the most dramatic nights in the company's history.

During his initial interview, SBF wasn't asked the usual questions like "What did you do during the summer?" Instead, he faced a series of game challenges—actually gambling games. He had to quickly solve math problems or probability problems, such as "What is the probability of rolling at least one three when rolling two six-sided dice?" or "What is the probability of rolling two threes when rolling two dice?" These kinds of questions were a breeze for SBF, and he thrived in them.

As the problems became increasingly complex and the pace quickened, his performance became even more outstanding. He "immediately realized that the key to the game was to quickly assess the expected value of bizarre situations and take action." He understood that his opponent was "testing his judgment and execution in dealing with chaotic situations—rather than getting bogged down in questions he couldn't answer."

This game-theoretic model tests the potential of future traders. But the real reward lies in applying these skills to real-world trading. And that real-world experience came two years later.

During the 2016 presidential election, Jane Street traders predicted a global stock market crash if Donald Trump were elected. According to Lewis, to gain a competitive edge, Jane Street commissioned SBF to develop a project designed to predict election results.

Their goal: to know the election results before CNN, and then to trade faster than anyone else.

SBF assigned different traders to analyze voting data in each state. The system worked remarkably well—Jane Street predicted results minutes or even hours earlier than CNN in several key states.

On election night, the system sent a signal shortly before midnight: Florida voting data heavily favored Trump, with his chances of winning jumping from 5% to 60%.

According to Lewis's account in his book, Jane Street shorted the S&P 500 index with holdings of up to several billion dollars, while also shorting stock markets in multiple countries around the world, betting on a market crash after Trump's election.

When they went to SBF to sleep, they had a paper profit of $300 million. This was the company's largest single profit in history.

Three hours later, he returned to the trading floor and found that the world had changed.

The market priced in Trump's victory, and then... it started to rise.

The US market rose instead of falling—because Trump is seen by many as a pro-business candidate.

Jane Street's short positions were squeezed out during this rally.

From +300 million to -300 million, a net change of $600 million overnight.

Jane Street did not punish SBF. They chose a different evaluation method: SBF's forecasting system was accurate; his model was not wrong. The mistake lay in his judgment of the market reaction direction, which was not a purely mathematical problem. He was even reportedly praised internally for the accuracy of the forecasting machine itself.

Based on his outstanding trading performance, Jane Street paid SBF a $300,000 salary in his first year, which increased to $600,000 in the second year, and a $1 million bonus in the third year. It is estimated that if he continues to maintain this performance, his annual salary will reach $75 million in ten years.

But he chose to leave to establish Alameda Research and FTX.

Then, in another way, history was made again.

Jane Street Exodus List

After the FTX collapse, it was surprising to discover that Jane Street's alumni network almost dominated the list of key figures in the entire event:

SBF himself (Jane Street trader, 2014-2017). Caroline Ellison (Alameda CEO, SBF's ex-girlfriend, former Jane Street trader). Gabe Bankman-Fried (SBF's brother, former Jane Street trader, but briefly and in a somewhat awkward position). Lily Zhang and Duncan Rheingans-Yoo (former SBF colleagues, later founded Modulo Capital, which received approximately $400 million in investment from Alameda and is headquartered in the same building as SBF's Bahamas residence).

The density of this circle is impossible to ignore.

Jane Street has nurtured some of the most important people in the crypto world of our time, in whatever sense they are "important".

*Part of the reason was that his brother had just left his job and started poaching people from Jane Street to join his own competing trading firm. Sources say the brothers went for a long period without speaking to each other.

A $1 billion secret

This story begins with a lawsuit, which unexpectedly ignites an even bigger crisis.

In February 2024, two traders at Jane Street—Douglas Schadewald and Daniel Spottiswood—abruptly resigned and jumped ship to hedge fund giant Millennium Management.

Jane Street then filed a lawsuit against the two individuals and Millennium in April, accusing them of stealing a "highly valuable" proprietary trading strategy.

What is the core of this strategy? A seemingly insignificant detail in court made everyone realize that it was a short-term index options strategy specifically targeting the Indian options market—which brought Jane Street more than $1 billion in profits in 2023 alone.

More specifically, after two traders took this strategy to Millennium, Jane Street's profits in the Indian market plummeted by 50% in March 2024. Meanwhile, Millennium's Indian operations began to expand rapidly.

In December 2024, the case was settled with a confidentiality agreement, the specific terms of which were not disclosed.

However, Jane Street's disclosure of a "$1 billion Indian options strategy" in the lawsuit caught the attention of the Securities and Exchange Commission of India (SEBI). Many Indian retail investors have suffered heavy losses in options trading; how could a foreign company be able to earn such enormous profits?

On July 3, 2025, SEBI issued a 105-page temporary injunction, announcing the conclusion of its investigation.

SEBI's description paints a picture like this:

On the expiration date of each Bank Nifty option, Jane Street's algorithm buys a large number of Bank Nifty constituent stocks and stock index futures after the market opens (9:15-11:46), sometimes accounting for more than 20% of the total market trading volume, including core heavyweight stocks such as Kotak Bank, SBI, and Axis Bank. At the same time, Jane Street establishes a large short position in the options market: selling call options and buying put options.

In the afternoon (from 11:49 to the close), Jane Street began to operate in the opposite direction: it sold off a large number of stocks and futures that it had bought in the morning, artificially putting downward pressure on the index. The closing price on the expiration date shifted lower, and the short option positions established earlier generated substantial profits.

On a particular day that SEBI focused its investigation on, Jane Street lost approximately $7.5 million on spot and futures trading, but gained approximately $89 million on options trading. Net profit: $81.5 million.

From January 2023 to March 2025, SEBI statistics show that Jane Street's total profits across all trading segments reached 365.0212 billion rupees (approximately US$4 billion). Notably, Jane Street earned 432.8933 billion rupees in index options and stock options trading, but incurred a net loss of 72.08 billion rupees in stock futures trading.

SEBI added an unsettling context: the organization itself had previously calculated that 93% of retail options traders in the Indian derivatives market lost money, with annual losses exceeding 1 trillion rupees. Meanwhile, professional trading firms—represented by Jane Street—profited handsomely during the same period.

On July 4, 2025, Jane Street was suspended from all trading privileges in India by SEBI, and its bank accounts were frozen, prohibiting any unauthorized deductions.

On July 14, Jane Street deposited approximately 4.84 billion rupees (about US$560 million) into an escrow account as required, applying to have its trading privileges restored. On July 21, SEBI allowed it to resume trading—on the condition that it continue to be subject to investigation.

Jane Street denied all allegations in an internal memo, calling the Securities and Exchange Commission of India's charges "highly inflammatory" and arguing that its activities involved arbitrage trading of underlying indices, "a core and pervasive mechanism for maintaining price consistency in financial markets," and filed an appeal. As of February 2026, the case was still pending.

A new footnote to Luna's collapse

In May 2022, TerraUSD and Luna collapsed. The UST algorithmic stablecoin plummeted from $1 to worthless, and Luna fell from $116 to near zero, with $40 billion evaporating instantly.

Perhaps we didn’t think about the root cause of the collapse at the time, but four years later, this collapse has a new interpretation.

On February 23, 2026, Todd Snyder, the liquidator of Terraform Labs, filed a lawsuit in Manhattan federal court against Jane Street.

At the heart of the lawsuit is a private chat group called "Bryce's Secret".

The group was created by Bryce Pratt, an employee of Jane Street. He was an intern at Terraform before leaving to join Jane Street, but his old network of contacts remained intact—the other two members of the group are a software engineer and a business development manager at Terraform.

According to the lawsuit, the group chat was created in February 2022 and became an information conduit connecting Terraform's internal operations with Jane Street.

5:44 PM on May 7, 2022.

Terraform Labs quietly withdrew $150 million of UST from the Curve decentralized liquidity pool. This operation was not announced publicly and was unknown to any outsiders.

Ten minutes later, a wallet associated with Jane Street withdrew $85 million of UST from the same liquidity pool.

Terraform and Jane Street together withdrew a total of $235 million of UST from this liquidity pool, directly breaking through the UST's liquidity support. The UST began to decouple, and panic began to spread.

Bloomberg quoted a key statement in the lawsuit: Jane Street's actions enabled it to "cover up hundreds of millions of dollars in potential exposure hours before the Terraform ecosystem collapsed."

Two days later, on May 9th, the UST had already fallen to $0.80, and the collapse was irreversible. Bryce Pratt messaged Do Kwon and the Terraform team via group chat, suggesting that Jane Street "could consider buying Luna at a significant discount."

First, move the valuables out of the house during the fire, then come back and ask the homeowner if they want to sell them off at a loss.

The defendants named in the lawsuit, in addition to Pratt, include Jane Street co-founder Robert Granieri (the only one of the four founders still employed) and employee Michael Huang.

Jane Street's response was succinct: "A desperate lawsuit, transparent extortion."

They added that the losses suffered by Terra and Luna investors stemmed from the "billions of dollars in fraud" perpetrated by Do Kwon and Terraform management, and that a strong counterattack would be launched.

That's true. Do Kwon did plead guilty and was sentenced to 15 years; Terraform did pay a $4.47 billion fine.

However, the statements "Do Kwon is guilty" and "the others are innocent" do not mutually confirm each other.

It is a fact that the building had fatal structural defects. The fact that someone removed the most valuable items beforehand during its collapse is a separate legal issue.

What exactly is this company?

The story of Jane Street is difficult to summarize in a single word.

It is said to be "one of the most profitable companies on Wall Street," and its net income of $20.5 billion in 2024 is enough to prove that.

The extremely low acceptance rate, the OCaml skill stack that cannot be accepted by the external market, and the extremely high annual salaries of senior executives all point to this conclusion.

The conclusion that it is a "deep player in the gray area of ​​the rules" is also drawn by SEBI's 105-page ruling, Terraform's lawsuit, and Millennium's secret settlement.

It could be all of the above at the same time.

Information asymmetry always exists in financial markets. What makes Jane Street unique is that it leverages this asymmetry to a systemic level.

What is the true market price at any given moment? Where are pricing discrepancies? How can one find and trade faster than everyone else? These are questions Jane Street seems to be constantly trying to answer.

The math questions in an interview can be a mystery, the crash of Terra can be a mystery, and the disappearance of Bitcoin's "10 o'clock crash" after it was sued is also a mystery .

Jane Street describes herself as "a collection of puzzle solvers".

But when the market's attention began to turn to Jane Street itself, it too became a mystery.

Related reading: The collapse of 40 billion, the knife at 10 a.m. every day—all point to the same name: Jane Street

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Return: 1) TL;DR (3–5 bullets) 2) Results vs. guidance (what improved/worsened) 3) Forward outlook (specific statements) 4) Risks / watch-outs 5) Q&A takeaways (if present) Text: <<< {section_text} >>> """ return textwrap.dedent(template).format( symbol=symbol, quarter=quarter, year=year, section_text=section_text )def summarize_section(section_text, symbol="NVDA", quarter="Q2", year="2024"): if not section_text or section_text.strip() == "": return "(No content found for this section.)" prompt = build_prompt(section_text, symbol, quarter, year) return call_groq(prompt)# Example usage with the cleaned splits from Section 3prepared_summary = summarize_section(prepared, symbol="NVDA", quarter="Q2", year="2024")qna_summary = summarize_section(qna, symbol="NVDA", quarter="Q2", year="2024")final_one_pager = f"""# {symbol} Earnings One-Pager — {quarter} {year}## Prepared Remarks — Key Points{prepared_summary}## Q&A Highlights{qna_summary}""".strip()print(final_one_pager[:1200]) # preview Tips that keep quality high: Keep temperature low (≈0.2) for factual tone. If a section is extremely long, chunk at ~5–8k tokens, summarize each chunk with the same prompt, then ask the model to merge chunk summaries into one section summary before producing the final one-pager. If you also fetched headline numbers (EPS/revenue, guidance) earlier, prepend them to the prompt as brief context to help the model anchor on the right outcomes. Building the End-to-End Pipeline At this point, we have all the building blocks: the FMP API to fetch transcripts, a cleaning step to structure the data, and Groq LLM to generate concise summaries. The final step is to connect everything into a single workflow that can take any ticker and return a one-page earnings call summary. The flow looks like this: Input a stock ticker (for example, NVDA). Use FMP to fetch the latest transcript. Clean and split the text into Prepared Remarks and Q&A. Send each section to Groq for summarization. Merge the outputs into a neatly formatted earnings one-pager. Here’s how it comes together in Python: def summarize_earnings_call(symbol, quarter, year, api_key, groq_key): # Step 1: Fetch transcript from FMP url = f"https://financialmodelingprep.com/api/v3/earning_call_transcript/{symbol}?quarter={quarter}&year={year}&apikey={api_key}" resp = requests.get(url) resp.raise_for_status() data = resp.json() if not data or "content" not in data[0]: return f"No transcript found for {symbol} {quarter} {year}" text = data[0]["content"] # Step 2: Clean and split clean_text = re.sub(r'\s+', ' ', text).strip() if "Question-and-Answer" in clean_text: prepared, qna = clean_text.split("Question-and-Answer", 1) else: prepared, qna = clean_text, "" # Step 3: Summarize with Groq prepared_summary = summarize_section(prepared, symbol, quarter, year) qna_summary = summarize_section(qna, symbol, quarter, year) # Step 4: Merge into final one-pager return f"""# {symbol} Earnings One-Pager — {quarter} {year}## Prepared Remarks{prepared_summary}## Q&A Highlights{qna_summary}""".strip()# Example runprint(summarize_earnings_call("NVDA", 2, 2024, API_KEY, GROQ_API_KEY)) With this setup, generating a summary becomes as simple as calling one function with a ticker and date. You can run it inside a notebook, integrate it into a research workflow, or even schedule it to trigger after each new earnings release. Free Stock Market API and Financial Statements API... Conclusion Earnings calls no longer need to feel overwhelming. With the Financial Modeling Prep API, you can instantly access any company’s transcript, and with Groq LLM, you can turn that raw text into a sharp, actionable summary in seconds. This pipeline saves hours of reading and ensures you never miss the key results, guidance, or risks hidden in lengthy remarks. Whether you track tech giants like NVIDIA or smaller growth stocks, the process is the same — fast, reliable, and powered by the flexibility of FMP’s data. Summarize Any Stock’s Earnings Call in Seconds Using FMP API was originally published in Coinmonks on Medium, where people are continuing the conversation by highlighting and responding to this story
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Medium2025/09/18 14:40