Hiring at $200K Annual Salary: Wall Street Advances into Prediction Markets

marsbitPublicado a 2026-01-15Actualizado a 2026-01-15

Resumen

Wall Street firms are aggressively entering the prediction markets, with trading giants like DRW, Susquehanna, and Tyr Capital building specialized teams. DRW is offering up to $200,000 in base salary to hire traders who can monitor and trade on platforms like Polymarket and Kalshi. Trading volume in these markets surged from under $100 million in early 2024 to over $8 billion by December 2025, attracting institutional interest. Unlike retail traders who often bet on single events, institutions focus on cross-platform arbitrage and structural opportunities. For example, hedge funds can use prediction markets to hedge investments with greater precision by pairing positions—such as buying "no recession" contracts on Polymarket while shorting overvalued bonds in credit markets. Market makers like Susquehanna, which has privileged access to lower fees and higher limits on platforms like Kalshi, are set to reduce arbitrage opportunities and improve liquidity. This professionalization may lead to more complex products, such as multi-event combos and conditional probability contracts. The entry of well-capitalized, technologically advanced institutions signals a maturation of prediction markets, mirroring the historical pattern of散户-driven innovation eventually dominated by professional players. While retail traders may find niches in long-tail events, the era of easy profits from informational edges is likely over.

Author: Niusike, Deep Tide TechFlow

It has finally arrived. The prediction markets, once built by political supporters, speculative retail investors, and airdrop hunters, are now welcoming a group of silent yet deadly new players.

According to a Thursday report by the Financial Times, several well-known trading firms, including DRW, Susquehanna, and Tyr Capital, are forming specialized prediction market trading teams.

DRW posted a job advertisement last week, offering a base annual salary of up to $200,000 for traders capable of "monitoring and trading active markets in real-time" on platforms like Polymarket and Kalshi.

Options trading giant Susquehanna is recruiting prediction market traders who can "detect incorrect fair value," identify "anomalous behavior" and "inefficiencies" in prediction markets, and is also building a dedicated sports trading team.

Crypto hedge fund Tyr Capital is continuously hiring prediction market traders who are "already running complex strategies."

Data supports this ambitious expansion.

Monthly trading volume surged from less than $100 million at the beginning of 2024 to over $8 billion by December 2025, with a record single-day trading volume of $701.7 million on January 12.

When the pool of funds becomes deep enough to accommodate the size of giants, Wall Street's entry becomes inevitable.

Arbitrage First

In prediction markets, institutions and retail investors are not playing the same game.

Retail investors often rely on fragmented information to predict single events, which is essentially gambling, while institutional players focus on cross-platform arbitrage and structural market opportunities.

In October 2025, Boaz Weinstein, founder of hedge fund Saba Capital Management, stated at a closed-door meeting that prediction markets allow portfolio managers to hedge investments with greater precision, particularly regarding the probability of specific events occurring.

Standing next to Polymarket CEO Shayne Coplan at the time, he said, "A few months ago, Polymarket showed a 50% probability of recession, while the credit market indicated a risk of about 2%. You can think of countless paired trades that were previously impossible."

According to Weinstein's view, a fund manager could buy the "no recession" contract on Polymarket. Because the market believed there was a 50% chance of recession, this contract was relatively cheap.

At the same time, in the credit market, one could short some bonds or credit products that would fall sharply in a recession. Because the credit market only assigned a 2% probability to a recession, these products were still priced high.

If a recession did occur, you would lose a small amount on Polymarket, but make a large profit in the credit market as those overvalued bonds plummet.

If no recession occurred, you would make money on Polymarket and might incur a small loss in the credit market, but overall still profit.

The emergence of prediction markets has provided traditional financial markets with a new "price discovery tool."

The Arrival of the Privileged Class

What tilts the scales even further is privilege at the regulatory level.

Susquehanna is the first market maker on Kalshi and has reached an event contract agreement with Robinhood.

Kalshi offers market makers numerous benefits: lower fees, special trading limits, and more convenient trading channels. The specific terms are not public.

The entry of market makers will quickly change this market.

Previously, prediction markets often suffered from insufficient liquidity, especially for niche events. When you wanted to buy or sell a large number of contracts, you might face wide spreads or simply no counterparty.

Professional institutions will quickly eliminate obvious pricing errors. For example, price differences for the same event on different platforms, or clearly unreasonable probability pricing, will be rapidly smoothed out.

This is not good news for retail investors. Previously, you might find that "Trump wins" was at a 60% probability on Polymarket and 55% on Kalshi, allowing for simple arbitrage. In the future, such opportunities will基本ally not exist.

With Wall Street's PhDs earning hundreds of thousands of dollars, future prediction contracts may also enter an era of specialization and diversification, not just单一 event prediction, such as:

1. Multi-event combination contracts, similar to parlays in sports betting

2. Time series contracts, predicting the probability of an event occurring within a specific time period

3. Conditional probability products, e.g., if A happens, what is the probability of B happening

......

Looking back at financial history, from foreign exchange to futures, to cryptocurrencies, the development of every emerging market follows a similar trajectory: ignited by retail investors, eventually taken over by institutions.

Prediction markets are repeating this process. Technological advantages, capital scale, and privileged access will ultimately determine who stays in this game of probability until the end.

For retail investors, although there may still be a glimmer of hope in long-cycle predictions or niche areas, they must face reality. When Wall Street's精密 machines start running at full speed, the狂欢 period of easy profits from information asymmetry may be gone forever.

Preguntas relacionadas

QWhat is the reported base salary that DRW is offering to traders for monitoring and trading on prediction market platforms?

A$200,000

QWhich specific prediction market platforms are mentioned in the article as being targeted by the new trading teams from firms like DRW?

APolymarket and Kalshi

QAccording to Boaz Weinstein, how can hedge fund managers use prediction markets to hedge their investments more precisely?

AThey can use prediction markets to hedge against the probability of specific events occurring, such as by creating trades that pair a position on a prediction market with an opposite position in a traditional market like credit.

QWhat advantage does the article state that market makers like Susquehanna have on platforms such as Kalshi?

AThey receive benefits such as lower fees, special trading limits, and more convenient trading channels, the specific terms of which are not publicly disclosed.

QWhat does the article suggest is the likely outcome for retail traders as large institutional players enter the prediction market space?

AThe era of easy profits from information asymmetry is likely over for retail traders, as institutions will quickly eliminate pricing errors and arbitrage opportunities, though some opportunity may remain in long-cycle predictions or niche areas.

Lecturas Relacionadas

Understanding Hash in One Article: The "Browser Miner" on Ethereum

Hash is an Ethereum-based ERC-20 token described as a "browser-minable post-quantum token." Its key features include enabling browser-based GPU mining without specialized hardware, a fixed supply cap of 21 million tokens, immutable and permissionless smart contracts with no team allocation or pre-mining, and an emphasis on post-quantum security using Keccak256 hashing. The mining mechanism is a simplified on-chain proof-of-work where miners solve unique challenges tied to their wallet address. Key design elements prevent answer theft, with epochs resetting every 100 blocks (~20 minutes) and a per-block minting limit. Emission follows a Bitcoin-like halving schedule every 100,000 mints, starting at 100 tokens per mint. Projections suggest all tokens could be mined within approximately 294 days if a target rate of one mint per minute is sustained. Hash emphasizes "post-quantum" security by leveraging hash-based primitives like Keccak256, which are considered more resistant to quantum attacks compared to elliptic-curve cryptography. While not a fully post-quantum asset, it aligns with Ethereum's broader post-quantum research narrative. The project completed its Genesis sale at $0.03 and began trading on Uniswap, with its price reaching around $0.19. The initial circulating supply is small, with 5% sold in Genesis and 5% allocated to liquidity. The majority (47.6% of total supply) is allocated to early-stage mining, leading to a front-loaded emission schedule. This structure, combined with low initial liquidity, makes Hash a high-volatility, high-risk project dependent on sustained miner participation and market demand to absorb new supply.

marsbitHace 6 min(s)

Understanding Hash in One Article: The "Browser Miner" on Ethereum

marsbitHace 6 min(s)

OpenAI's Largest Internal Wealth Creation: 600 People Cash Out a Total of $6.6 Billion, 75 Take Home the Maximum $30 Million Each

A Wall Street Journal report reveals OpenAI's unprecedented pre-IPO wealth creation. In a single employee stock sale last October, over 600 current and former employees sold shares, collectively cashing out approximately $6.6 billion. Due to high investor demand, the company tripled the individual sale cap to $30 million, with about 75 employees selling the maximum amount. This event represents the largest such transaction in tech industry history for a private company. OpenAI's valuation was $500 billion for this tender offer. Employees with over two years of tenure were eligible, allowing many post-ChatGPT hires their first liquidity event. The company's stock has reportedly grown over 100-fold in seven years. Following a restructuring, employees collectively hold about 26% of OpenAI. The scale of executive wealth is also staggering. In court testimony related to Elon Musk's lawsuit, President and co-founder Greg Brockman confirmed his OpenAI stake is worth around $30 billion. Analysis indicates about 165 current and former employees hold a combined ~$164.9 billion in equity, averaging nearly $1 billion per person in paper wealth. OpenAI's per-employee stock-based compensation is estimated to be 34 times the average of major tech firms before their IPOs. OpenAI continues its rapid ascent, closing a $122 billion funding round at an $852 billion valuation in March. With monthly revenue hitting $2 billion, over 900 million weekly ChatGPT users, and plans for a potential trillion-dollar IPO in late 2026, this wealth-creation engine shows no signs of stopping.

链捕手Hace 29 min(s)

OpenAI's Largest Internal Wealth Creation: 600 People Cash Out a Total of $6.6 Billion, 75 Take Home the Maximum $30 Million Each

链捕手Hace 29 min(s)

Trading

Spot
Futuros
活动图片