Nasdaq Ventures into Prediction Markets: Wall Street Bets on Tech Index with 'Yes or No'

Odaily星球日报Опубліковано о 2026-03-03Востаннє оновлено о 2026-03-03

Анотація

Nasdaq has filed a proposal with the SEC to launch binary options, or "outcome-related options," on its flagship Nasdaq-100 and Nasdaq-100 Micro indexes. These contracts allow investors to make "yes or no" predictions on whether specific conditions will be met by the index at expiration. Priced between $0.01 and $1.00, the contract value reflects the perceived probability of the outcome—settling at $1 if true and $0 if false. This simplifies trading to a direct bet on event outcomes, rather than price movements. The Nasdaq-100, heavily weighted toward major tech stocks like Apple and Nvidia, is highly sensitive to market sentiment, making it an ideal underlying asset for such products. This move signals traditional exchanges' growing interest in prediction markets. Unlike the Intercontinental Exchange's recent strategic investment in Polymarket, Nasdaq is directly integrating predictive structures into its existing product lineup. If approved, this would mark a significant step in bringing prediction-based trading into the regulated mainstream financial system, blending traditional derivatives with event-driven speculation.

Original | Odaily Planet Daily (@OdailyChina)

Author | Asher (@Asher_ 0210)

Last night, Nasdaq Inc. submitted a rule change proposal to the U.S. Securities and Exchange Commission (SEC), planning to introduce an options contract that allows investors to make "yes or no" judgments on major stock indices.

According to the document, Nasdaq intends to list "binary options," also known as "outcome-related options," on its flagship products—the Nasdaq 100 Index and the Nasdaq 100 Micro Index. If approved, this would mark Nasdaq's first official foray into products with prediction market attributes.

This move signifies that traditional stock exchange giants are actively entering the rapidly growing prediction market sector.

What Are Binary Options?

The proposed contracts have a pricing range of 1 cent to 1 dollar, with the price itself directly reflecting the market's judgment of the probability of a specific outcome.

For example, if a contract is based on whether "the Nasdaq 100 Index meets a certain condition at a specific time point," then:

  • If the market believes the probability of this outcome is 80%, the price might be close to $0.80;
  • If the condition is met at expiration, the contract settles at $1;
  • If the condition is not met, the contract value becomes zero.

If traditional options are about betting on "how much it will rise or fall," binary options are more concerned with "whether it will happen." There are no complex parameters, no interval calculations—only the outcome itself. This all-or-nothing settlement method makes trading more like making a clear judgment about the future.

Because of this, such products are closer in form to the logic of prediction markets.

Why Choose the Nasdaq 100?

Nasdaq's choice is not an ordinary index but one of the most sentiment-sensitive assets. The Nasdaq 100 has long been regarded as a core indicator of the U.S. technology sector, with concentrated holdings in heavyweight companies like Apple, NVIDIA, Microsoft, Amazon, and Meta. These companies almost always become market focal points each quarter. An earnings report, a regulatory update, or even a policy statement can quickly reflect in the index's movement.

The high concentration of components means that the Nasdaq 100's trends often revolve around a single focus. The market might bet on AI expectations for a period, then shift to interest rate paths or policy changes. During earnings or policy-intensive periods, the index typically reflects market judgments in a relatively short time rather than prolonged back-and-forth fluctuations.

Additionally, the Nasdaq 100 itself has a mature derivatives trading foundation, ample liquidity, and a well-established pricing system. Introducing new structured products on this underlying asset is risk-controllable and more likely to gain market acceptance.

Two Ways Traditional Exchanges Are Entering the Market

Nasdaq is not the first traditional exchange to show interest in prediction markets. In October 2025, Intercontinental Exchange, the parent company of the New York Stock Exchange, announced a strategic investment of approximately $2 billion in Polymarket, acquiring about a 20% stake, with the transaction valuation once reaching around $8 billion.

The NYSE's choice was not to launch its own prediction products but to enter the field through capital participation and data cooperation. Its core intention is to obtain real-time probability data formed by prediction markets and incorporate it into institutional service systems. For the NYSE, prediction markets are more like supplementary sentiment indicators and data assets.

In contrast, Nasdaq's approach is more direct. It chooses to embed binary structures into its core index product line, extending within the existing trading framework. Compared to investing in external prediction market platforms, this method means predictive trading is incorporated into the standardized securities product system, rather than being just an external data source.

The difference in strategies reflects the varying judgments of traditional exchanges when facing new trading structures.

Prediction Markets Are Being Integrated into Traditional Exchange Product Systems

Regardless of whether the SEC ultimately approves this proposal, Nasdaq's submission of the rule change application itself sends a clear signal—predictive trading is no longer just an experiment on crypto platforms or niche markets but is beginning to be integrated into traditional exchange product systems.

For a long time, mainstream derivatives have revolved around price fluctuations, with investors judging the magnitude and timing of rises and falls through different structures. Binary options simplify the question to whether the outcome will occur, shifting the trading focus from magnitude to the conclusion itself.

When the Nasdaq 100 Index is incorporated into such contract structures, the trading logic becomes more direct. The market's focus is no longer on the magnitude of fluctuations but on whether a specific outcome will materialize. The price reflects not just volatility but the consensus on the probability of the outcome.

For Nasdaq, this is an extension of its product line. For prediction market, it is the beginning of its structure being formally accepted by the mainstream system. If this product eventually launches, it could become a bridging attempt between traditional derivatives and event-based trading.

Пов'язані питання

QWhat is the new type of option contract that Nasdaq has proposed to the SEC?

ANasdaq has proposed a 'binary option' or 'outcome-related option' contract that allows investors to make 'yes or no' judgments on major stock indices.

QWhich specific indices will the new binary options be based on if approved?

AThe binary options will be based on the Nasdaq 100 Index and the Nasdaq 100 Micro Index.

QHow does the pricing of these binary options reflect market expectations?

AThe price, ranging from 1 cent to 1 dollar, directly reflects the market's judgment of the probability of a specific outcome. For example, a price of $0.80 indicates an 80% probability that the condition will be met.

QWhat is the key difference between traditional options and these new binary options?

ATraditional options focus on 'how much' the price will move, while binary options focus on 'whether' a specific outcome will happen, with a simple all-or-nothing settlement.

QHow does Nasdaq's approach to entering the prediction market differ from that of the New York Stock Exchange's parent company?

ANasdaq is directly integrating binary structures into its core index products, while NYSE's parent, Intercontinental Exchange, made a strategic investment in an external prediction market platform, Polymarket, to gain access to real-time probability data.

Пов'язані матеріали

Annual Salary of Millions Competing for Electricians, Meta Rushes to Open Its Own Technical School

The AI boom is facing an unexpected bottleneck: a severe shortage of skilled construction workers and electricians. As tech giants like Meta, OpenAI, and Alphabet race to build massive data centers—such as OpenAI's $16 billion "Stargate" project—they are hitting a critical labor wall. The U.S. needs an estimated 130,000 more electricians, 240,000 construction workers, and 150,000 supervisors by 2030 for AI infrastructure alone, but tens of thousands of electrician jobs go unfilled each year. While AI companies offer high premiums, with electricians earning up to $280,000 annually, worker scarcity still causes massive losses—delays on a single project can cost $14.2 million per month. The complexity of building AI data centers, which require immense power (equivalent to powering hundreds of thousands of homes), sophisticated electrical systems, and advanced liquid cooling solutions, demands highly skilled technicians who are in short supply. To combat this, companies are investing heavily in training. Meta has committed $115 million to a free training school offering tuition, housing, and stipends, targeting 5,000 new workers. OpenAI is partnering with unions to secure skilled labor. These efforts are paying off, with a significant rise in Gen Z interest in trade schools over college. However, the power demands are staggering. AI data centers are driving a rapid surge in electricity consumption, projected to account for up to 12% of U.S. power use by 2028 and raising costs for consumers. Furthermore, the construction boom is project-based, leading to a potential future glut of trained workers once building peaks, which could depress wages industry-wide. The race for AI supremacy now depends as much on skilled hands as on advanced chips.

marsbit1 год тому

Annual Salary of Millions Competing for Electricians, Meta Rushes to Open Its Own Technical School

marsbit1 год тому

OpenAI No Longer Sells Its Most Expensive Model for Profit

OpenAI is shifting its business strategy away from promoting its most expensive, flagship models for every task. Recent price cuts—80% for GPT-5.6 Luna and 20% for Terra—signal a deeper change: the company now actively advises users that many tasks don't require the most powerful model. Instead, OpenAI recommends a tiered approach: use the high-end GPT-5.6 Sol for complex planning and analysis, then delegate execution to cheaper models like Luna. This mirrors moves by Anthropic, which recently launched Claude Opus 5 at half the price of its top model, Fable 5. Both companies are de-emphasizing flagship models as primary revenue drivers, using them instead for brand prestige and technological showcases. The industry is entering a "mass-market" phase, similar to automotive, where high-volume, cost-effective models handle daily operations and drive scale. OpenAI's price reductions are partly enabled by AI models themselves optimizing underlying code and infrastructure, creating a self-reinforcing cycle of efficiency gains and cost reduction. Competition is shifting from "who is smartest" to "who offers the best value." The goal is no longer selling individual models but fostering widespread API adoption and ecosystem lock-in. By making AI calls cheap and ubiquitous, companies like OpenAI aim to become the indispensable, utility-like infrastructure powering automated workflows—the "water and electricity" of software, quietly embedded everywhere.

marsbit1 год тому

OpenAI No Longer Sells Its Most Expensive Model for Profit

marsbit1 год тому

Торгівля

Спот
活动图片