From Robinhood to Polymarket: Is the Era of Integrating All Assets on a Single Platform Coming?

marsbitОпубліковано о 2026-04-24Востаннє оновлено о 2026-04-24

Анотація

From Robinhood to Polymarket: The Era of All-in-One Asset Platforms Is Coming Asset classes are rapidly converging. Platforms that once specialized in single categories—such as stocks, cryptocurrencies, or prediction markets—are now moving toward offering all three. Robinhood pioneered this model, starting with equities, adding crypto in 2018, and prediction markets in 2025. This strategy has proven resilient: when crypto revenues fell, other segments like options and stocks filled the gap. Now, prediction market leaders Polymarket and Kalshi are moving in the same direction, both announcing perpetual futures trading on April 21, 2026, pending regulatory approval. These futures will cover assets like Bitcoin, gold, and stocks such as Nvidia. This trend mirrors the consolidation seen in consumer tech, like smartphones replacing dedicated cameras and MP3 players. Younger users, accustomed to interacting with multiple asset types from an early age, will increasingly demand unified platforms. A key competitive advantage in prediction markets is collateral utilization—idle assets locked during betting periods. Polymarket’s move into perpetuals may be a strategy to generate yield from that capital, similar to earlier DeFi integrations like PolyAave. As the regulatory landscape evolves, traditional finance is also likely to incorporate crypto and prediction markets, further accelerating this convergence.

Written by: Tiger Research

Compiled by: AididiaoJP, Foresight News

Key Points

Different asset classes are accelerating their integration: Stocks, cryptocurrencies, and prediction markets were once independent. Today, the trend of integrating all assets on a single platform is accelerating. Robinhood has proven this model with data; Polymarket and Kalshi are moving in the same direction.

In prediction markets, collateral utilization will become a core competitive advantage: In prediction markets, collateral is locked until the outcome is determined. Polymarket's launch of perpetual futures trading is likely an effort to generate returns from idle assets.

Traditional finance is also moving toward the same integration: The new generation of users has grown up accustomed to interacting with multiple asset classes simultaneously. As generations shift, the demand for integrated platforms will only grow, and large financial institutions will gradually incorporate crypto spot trading and prediction markets as the environment opens up to regulation.

On April 21, 2026, the two leading prediction market platforms, @Polymarket and @Kalshi, announced the launch of perpetual futures trading on the same day. The trading targets are expected to include cryptocurrencies like Bitcoin, commodities like gold, and stocks like Nvidia. Both platforms stated that they will officially launch after receiving regulatory approval.

Why Now

This can be understood through the "Robinhood model." The trend of integrating previously independent asset classes into a single platform has long been underway; the announcements from Polymarket and Kalshi are merely a continuation of this trend.

Robinhood started as a stock trading app, added cryptocurrency trading in 2018, and incorporated prediction markets in 2025, pioneering the model of consolidating fragmented trading markets under one platform.

This model has been validated by data. After expanding its crypto business, crypto trading revenue became Robinhood's largest single revenue source in Q4 2024. Although crypto revenue fell 38% year-over-year in Q4 2025, total revenue remained stable, with options, stocks, and prediction markets filling the gap. A structure of resilience through diversification has taken shape.

Polymarket and Kalshi are starting from the opposite direction but heading toward the same endpoint. They originated in prediction markets and are now adding futures trading. The starting points differ, but the destination is the same. As the Robinhood model proves successful, traditional finance is likely exploring the same path.

A Simple Analogy

Smartphones integrated cameras, MP3 players, and navigation into a single device; the era of carrying separate devices for each function is over. The same transformation is happening in finance.

Brokerage accounts, crypto exchanges, and prediction markets are merging into a single platform. Robinhood started as a stock app and gradually added cryptocurrencies and prediction markets; Polymarket started with prediction markets and is now adding crypto perpetual contracts. The starting points differ, but the direction is the same.

The Generalization of the Robinhood Model

As generations shift, this trend will accelerate further. The new generation of users has grown up simultaneously exposed to stocks, cryptocurrencies, and prediction markets. Just as smartphone users would not accept separate devices for a camera, MP3 player, and map, this generation finds the idea of using separate apps for each asset class unfamiliar from the start. The demand for an integrated platform that handles all assets within a familiar interface will grow naturally with each generation.

This is the generalization of the Robinhood model.

Polymarket and Kalshi have a particular advantage in this model. Because collateral in prediction markets is locked until the outcome is determined, how to utilize these idle assets will become a key competitive differentiator.

On December 3, 2025, a developer proposed the concept of PolyAave: depositing Polymarket's outcome tokens into an Aave liquidity pool to earn interest. This was an early attempt to convert prediction market collateral into DeFi yields. Polymarket's launch of perpetual futures is likely an extension of this logic. The strategy of not letting locked capital sit idle is sound.

Polymarket and Kalshi are moving first, but traditional finance faces the same pressure. As the regulatory environment gradually opens up, large financial institutions will directly support crypto spot trading and gradually incorporate new asset classes, including prediction markets.

Пов'язані питання

QWhat is the main trend discussed in the article regarding asset trading platforms?

AThe main trend is the convergence of different asset classes—such as stocks, cryptocurrencies, and prediction markets—into single, integrated platforms, as exemplified by Robinhood, Polymarket, and Kalshi.

QHow did Robinhood validate the integrated platform model according to the article?

ARobinhood validated the model by expanding from stocks to cryptocurrencies in 2018 and prediction markets in 2025, with crypto trading becoming its largest revenue source in Q4 2024. Despite a crypto revenue drop in Q4 2025, total revenue remained stable due to diversification into options, stocks, and prediction markets.

QWhy are Polymarket and Kalshi adding perpetual futures trading?

AThey are adding perpetual futures trading to utilize idle collateral locked in prediction markets, turning it into yield and enhancing their competitive advantage by not letting capital remain idle.

QWhat generational shift is driving the demand for integrated financial platforms?

AYounger generations, who have grown up simultaneously exposed to stocks, cryptocurrencies, and prediction markets, naturally prefer a single platform for all assets, similar to how smartphones integrate multiple devices into one.

QHow might traditional financial institutions respond to this trend?

AAs regulatory environments open up, large financial institutions are likely to gradually adopt crypto spot trading and incorporate new asset classes like prediction markets, following the same convergence path.

Пов'язані матеріали

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The Value Distribution of Stablecoins The article argues that stablecoins are evolving from a mere trading tool into a broad "dollar channel." It analyzes the industry's value chain through four layers: 1. **Issuance Layer (e.g., Tether, Circle):** The top layer that mints stablecoins, holds reserve assets, and captures the thickest interest rate spread. 2. **Infrastructure Layer (e.g., Bridge, BVNK):** Connects stablecoins to the traditional financial system, handling critical but complex "dirty work" like fiat on/off-ramps, banking integration, compliance (KYC/AML), and cross-border settlement. 3. **Acquiring/Distribution Layer (e.g., Stripe, Coinbase):** Embeds stablecoins into merchant systems, manages payment flows, and integrates with enterprise software. 4. **Application Layer:** End-users and businesses that ultimately use stablecoins for payments, settlement, or storing value. The author posits that while the issuance layer currently captures the most profit, the most overlooked and potentially critical layer is infrastructure. The core challenge for stablecoin adoption isn't the on-chain transfer (which is simple), but bridging the gap between blockchain and the real-world financial system. This involves solving practical problems for businesses: fiat conversion, reconciliation, tax handling, and user onboarding. Infrastructure companies are currently in a difficult "land-grab" phase—building networks, securing banking relationships, and achieving compliance country-by-country. They face pressure from both the profitable issuance layer above and distribution platforms below. However, the author suggests this layer is building a crucial moat. Once stablecoins become a default business rail, the infrastructure players who have done the hard work of integration may gain significant, durable value and pricing power.

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No one truly teaches you how to do research. You're often given a desk, a pre-selected problem, and vague instructions to "create something new." Consequently, many people reverse-engineer the job based on visible outputs—papers, posts, announcements—learning only how to *appear* like a researcher rather than how to *become* one. True research capability is built from stacking small, trainable skills, nearly all of which can be developed through deliberate practice. **Pick Your Own Problem:** Most researchers absorb problems from advisors or trends, lacking the underlying reasoning. Choosing a problem you genuinely care about, as John Schulman advises, leads to original work. Develop "taste" like a muscle: predict experiment outcomes, guess paper results from methods, and track which findings remain important over time. **Upgrade Your Inputs:** Relying on shared reading lists (arXiv hot lists, filtered group chats) leads to unoriginal conclusions. Undervalued old literature often holds crucial insights (e.g., MoE, LSTM, backpropagation). Richard Sutton's "The Bitter Lesson" or Claude Shannon's 1952 talk on creative thinking are more predictive than lengthy modern surveys. Breadth matters as much as depth: draw from neuroscience, mechanism design, hardware knowledge, and honest statistics. Read papers directly, especially appendices and limitations sections. **Write Everything Down:** As Paul Graham noted, writing exposes flaws in seemingly mature ideas. Writing is the cheapest defense against self-deception. Following Feynman's principle, Darwin programmatically wrote down facts contradicting his theory to combat memory bias. Maintain a detailed log of hypotheses, setups, predictions, results, and updated understandings. Reviewing past logs fosters essential humility.

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