Funding Rate Arbitrage Decoded: How to Achieve Stable Annualized Returns through Spot and Perpetual Hedging?
Original Title: Funding - earning 25-50% passive income per year with the cash/carry strategy?
Original Author: The Black Swan
Original Translation: Deep Tide TechFlow
In the cryptocurrency perpetual contract market, the phenomenon of price deviation often occurs, and traders can take advantage of these price errors.
“Cash and Carry Trade” is a classic profit strategy that allows traders to profit from the price difference between the perpetual contract price and the spot price.
Funding Rate Arbitrage – Earning 25-50% Passive Income Per Year with the Cash and Carry Strategy?

In the cryptocurrency perpetual contract market, the phenomenon of price deviation often occurs, and traders can take advantage of these price errors. "Cash and Carry Trade" is a classic strategy specifically targeting the price difference between perpetual contracts and spot prices, allowing traders to easily profit.
Through this strategy, traders can engage in arbitrage on centralized exchanges (CEX) and decentralized exchanges (DEX) without incurring high fees. Specifically, you can establish a spot long position on an asset while simultaneously selling the corresponding futures derivative. When the market overall tends towards a long position (i.e., the price premium is high), you can earn additional income through the funding rate. If this sounds a bit complex to you, don't worry, I will explain it to you in an ELI5 (Explain Like I'm 5) manner.
What is the Funding Rate?
The funding rate is a periodic fee that traders need to pay or receive based on the difference between the perpetual contract price and the spot market price. The size of this rate depends on the skew of the perpetual contract market and the extent to which the perpetual contract price deviates from the spot market price.
In simple terms, when the trading price of a perpetual swap contract is higher than the spot price (i.e., a premium), the skew on platforms such as Binance, Bybit, dYdX, or Hyperliquid becomes positive, and long traders need to pay the funding rate to short traders. Conversely, when the trading price of the perpetual swap contract is lower than the spot price (i.e., a discount), the skew becomes negative, and short traders need to pay the funding rate to long traders.
What we essentially want to do is mimic the operation of Ethena Labs: take a long position on ETH spot, while simultaneously shorting ETH perpetual contracts. However, the difference is that we will be operating on our own and choosing assets that interest us (hint: it doesn't necessarily have to be ETH).
If you don't want to read the previous content, I will try to explain it to you in a simple way.
Let's say we take Ethereum as an example, and we want to go long on ETH (preferably staked ETH).
We can take stETH (with an annualized yield of 3.6%), for example, and at the same time short $ETH in the perpetual contract market (for example, on Binance or Bybit).
When we simultaneously take equal amounts of long and short positions on ETH, our portfolio is in a state of "Delta Neutral." This means that no matter how much the price of ETH fluctuates, we will not incur losses or gains due to price changes.
The "Delta Neutral Strategy" is an investment method that mitigates market price fluctuation risks by balancing long and short positions. For example, if I simultaneously open a 1 ETH long position and a 1 ETH short position at the same price, then regardless of how the market price changes, the total value of my portfolio will not be affected (ignoring fees).
In this strategy, our income comes from two parts: ETH staking rewards and funding rate income.
The funding rate is a mechanism used to adjust the price difference between the perpetual contract and the spot market price. Its function is similar to the interest cost in spot margin trading, ensuring that the perpetual contract price does not deviate from the spot market price by adjusting the flow of funds between long and short parties.
The settlement of the funding rate is as follows:
· The funding fee is the fee settled directly between the buy and sell sides, usually at the end of each funding interval. For example, in an 8-hour funding interval, the funding fee is settled at midnight, 8:00 AM, and 4:00 PM UTC.
· On decentralized exchanges like dYdX and Hyperliquid, the funding rate is settled hourly, while on Binance and Bybit, it is settled every 8 hours.
· When the funding rate is positive, long position holders pay the funding fee to short position holders; when the funding rate is negative, short position holders pay the funding fee to long position holders (this usually occurs in a bull market, as I will explain later).
· Only traders who still hold positions at the time of funding settlement will pay or receive funding fees. If the position is closed before funding settlement, no funding fee will be incurred.
· If a trader's account balance is insufficient to cover the funding fee, the system will deduct it from the position margin, causing the liquidation price to be closer to the mark price, thereby increasing the risk of liquidation.

Let's analyze the funding rate displayed in the image. Perpetual contract exchanges on different chains may have slightly different funding rate calculation mechanisms, but as a trader, you need to understand the timing of funding fee payments/receipts and how the funding rate fluctuates over time. Here is how you can calculate the Annual Percentage Rate (APR) based on the funding rate in the image:
For Hyperliquid:
0.0540% * 3 = 0.162% (1-day APR)
0.162% * 365 = 59.3% (1-year APR)
As you can see, Binance has a lower funding rate, with an annualized return of 31.2% (calculated in the same way). Additionally, there is an arbitrage opportunity between Hyperliquid and Binance. You can long ETH perpetual contracts on Binance and short ETH perpetual contracts on Hyperliquid, thereby capturing the the 59.3% and 31.2% annualized returns, the difference being 28.1%. However, this strategy also comes with some risks:
1. Funding rate fluctuations may cause the funding rate for long positions on Binance to be higher than the funding rate for short positions on Hyperliquid, resulting in losses.
2. Because long positions are not spot positions, you will not receive staking rewards, which will reduce overall returns.
But the advantage of this method is that when using perpetual contracts for long and short positions, leverage can be utilized to increase capital efficiency. It is recommended to create an Excel spreadsheet to compare the returns and risks of different strategies and find the one that best suits you.
When the funding rate is positive (as shown in our example), long traders need to pay the funding fee, while short traders will receive the funding fee. This is crucial because it forms the basis for designing Delta-neutral strategies to profit from funding rates.
Spot and Futures Arbitrage
One of the simplest and most common strategies is the "Cash and Carry Trade," which involves simultaneously buying the spot asset and selling the perpetual contract in equal quantities. Taking ETH as an example, the trading strategy is as follows:
· Buy 10 ETH/stETH spot (worth $37,000)
· Sell 10 ETH perpetual contract (worth $37,000, can be done on dYdX, Hyperliquid, Binance, or Bybit)
At the time of writing this article, the ETH trading price is around $3,700. To execute this strategy, traders need to try to simultaneously execute the buy and sell orders at the same price and quantity to avoid "basis risk" (where market fluctuations prevent complete hedging of both positions).
The goal of this strategy is to achieve a 59% annualized return through funding rates regardless of whether the market price goes up or down. However, while this return may seem very attractive, traders need to be aware that funding rates can vary between different exchanges and assets, affecting the final return.
Your daily funding rate income can be calculated using the following formula:
Funding Rate Income = Position Value x Funding Rate
Using the current ETH funding rate of 0.0321% as an example, let's calculate the daily income:
· Daily Funding Rate Income: 10 ETH x $3,700 = $37,000 x 0.0540% = $20, settled 3 times a day, totaling $60.
· Daily Staking Income: 10 ETH x 1.036 = 0.36 ETH per year / 365 = 0.001 ETH per day, equivalent to $3,700 x 0.001 ETH = $3.7.
Therefore, the total daily income is $60 + $3.7 = $63.7. For some, this may be a decent income, while for others, it may seem insignificant.
However, this strategy also faces some risks and challenges:
Difficulty of Opening Long/Short Positions Simultaneously: When looking at the spot price and perpetual contract price of ETH on Binance or Bybit, you will notice that there is usually a price difference between the two.
For example, as I write this article, the spot price is $3,852, while the perpetual contract price is $3,861, resulting in a $9 spread.
1. How should you proceed? Try experimenting with a small amount of funds, and you'll find it nearly impossible to perfectly match both long and short positions.
2. Should you go long first and wait for the price to rise before going short, or should you go short first and wait for the spot price to drop before buying? Or perhaps balance your long and short positions through Dollar-Cost Averaging (DCA), which involves gradually purchasing or selling assets in tranches?
Trading Fees: Both opening and closing positions will incur fees. If your holding period is less than 24 hours, fees could lead to losses.
Rebalancing Risk with Low Capital: If your long and short positions are equal but the market experiences significant volatility (e.g., ETH doubling to $7,600), your short position may suffer deep losses while your long position sees substantial gains. This imbalance could result in your account's net value being disrupted or even forced liquidation.
Liquidation Risk: Depending on the amount of available funds in your exchange account, extreme market movements (e.g., ETH's price skyrocketing) could trigger liquidation of your short position.
Funding Rate Fluctuations: Funding rates fluctuate with market conditions, directly impacting your returns.
Difficulty of Simultaneous Closing: Closing positions presents challenges similar to opening them, and you may struggle to perfectly match your long and short positions, incurring additional costs or risks.
Centralized Exchange Risk: If exchanges like Binance or Bybit encounter issues such as bankruptcy or withdrawal restrictions, your funds could be at risk. This risk is akin to smart contract vulnerabilities in DeFi.
Operational Mistakes Risk: If you're unfamiliar with perpetual contracts, exercise caution. Market order mistakes can lead to extreme price fluctuations, resulting in executions at unfavorable prices. Additionally, a single click to open or close a position means operational errors could significantly impact your trades.
On a side note, you might explore options trading. This method could be simpler and potentially save you some costs :)
I just wanted to showcase how you can experiment with Ethena Labs' trading strategy.
That's all for today's content.
See you in the order book, anonymous friend.
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Debunking the AI Doomsday Myth: Why Establishment Inertia and the Software Wasteland Will Save Us
Editor's Note: Citrini7's cyberpunk-themed AI doomsday prophecy has sparked widespread discussion across the internet. However, this article presents a more pragmatic counter perspective. If Citrini envisions a digital tsunami instantly engulfing civilization, this author sees the resilient resistance of the human bureaucratic system, the profoundly flawed existing software ecosystem, and the long-overlooked cornerstone of heavy industry. This is a frontal clash between Silicon Valley fantasy and the iron law of reality, reminding us that the singularity may come, but it will never happen overnight.
The following is the original content:
Renowned market commentator Citrini7 recently published a captivating and widely circulated AI doomsday novel. While he acknowledges that the probability of some scenes occurring is extremely low, as someone who has witnessed multiple economic collapse prophecies, I want to challenge his views and present a more deterministic and optimistic future.
In 2007, people thought that against the backdrop of "peak oil," the United States' geopolitical status had come to an end; in 2008, they believed the dollar system was on the brink of collapse; in 2014, everyone thought AMD and NVIDIA were done for. Then ChatGPT emerged, and people thought Google was toast... Yet every time, existing institutions with deep-rooted inertia have proven to be far more resilient than onlookers imagined.
When Citrini talks about the fear of institutional turnover and rapid workforce displacement, he writes, "Even in fields we think rely on interpersonal relationships, cracks are showing. Take the real estate industry, where buyers have tolerated 5%-6% commissions for decades due to the information asymmetry between brokers and consumers..."
Seeing this, I couldn't help but chuckle. People have been proclaiming the "death of real estate agents" for 20 years now! This hardly requires any superintelligence; with Zillow, Redfin, or Opendoor, it's enough. But this example precisely proves the opposite of Citrini's view: although this workforce has long been deemed obsolete in the eyes of most, due to market inertia and regulatory capture, real estate agents' vitality is more tenacious than anyone's expectations a decade ago.
A few months ago, I just bought a house. The transaction process mandated that we hire a real estate agent, with lofty justifications. My buyer's agent made about $50,000 in this transaction, while his actual work — filling out forms and coordinating between multiple parties — amounted to no more than 10 hours, something I could have easily handled myself. The market will eventually move towards efficiency, providing fair pricing for labor, but this will be a long process.
I deeply understand the ways of inertia and change management: I once founded and sold a company whose core business was driving insurance brokerages from "manual service" to "software-driven." The iron rule I learned is: human societies in the real world are extremely complex, and things always take longer than you imagine — even when you account for this rule. This doesn't mean that the world won't undergo drastic changes, but rather that change will be more gradual, allowing us time to respond and adapt.
Recently, the software sector has seen a downturn as investors worry about the lack of moats in the backend systems of companies like Monday, Salesforce, Asana, making them easily replicable. Citrini and others believe that AI programming heralds the end of SaaS companies: one, products become homogenized, with zero profits, and two, jobs disappear.
But everyone overlooks one thing: the current state of these software products is simply terrible.
I'm qualified to say this because I've spent hundreds of thousands of dollars on Salesforce and Monday. Indeed, AI can enable competitors to replicate these products, but more importantly, AI can enable competitors to build better products. Stock price declines are not surprising: an industry relying on long-term lock-ins, lacking competitiveness, and filled with low-quality legacy incumbents is finally facing competition again.
From a broader perspective, almost all existing software is garbage, which is an undeniable fact. Every tool I've paid for is riddled with bugs; some software is so bad that I can't even pay for it (I've been unable to use Citibank's online transfer for the past three years); most web apps can't even get mobile and desktop responsiveness right; not a single product can fully deliver what you want. Silicon Valley darlings like Stripe and Linear only garner massive followings because they are not as disgustingly unusable as their competitors. If you ask a seasoned engineer, "Show me a truly perfect piece of software," all you'll get is prolonged silence and blank stares.
Here lies a profound truth: even as we approach a "software singularity," the human demand for software labor is nearly infinite. It's well known that the final few percentage points of perfection often require the most work. By this standard, almost every software product has at least a 100x improvement in complexity and features before reaching demand saturation.
I believe that most commentators who claim that the software industry is on the brink of extinction lack an intuitive understanding of software development. The software industry has been around for 50 years, and despite tremendous progress, it is always in a state of "not enough." As a programmer in 2020, my productivity matches that of hundreds of people in 1970, which is incredibly impressive leverage. However, there is still significant room for improvement. People underestimate the "Jevons Paradox": Efficiency improvements often lead to explosive growth in overall demand.
This does not mean that software engineering is an invincible job, but the industry's ability to absorb labor and its inertia far exceed imagination. The saturation process will be very slow, giving us enough time to adapt.
Of course, labor reallocation is inevitable, such as in the driving sector. As Citrini pointed out, many white-collar jobs will experience disruptions. For positions like real estate brokers that have long lost tangible value and rely solely on momentum for income, AI may be the final straw.
But our lifesaver lies in the fact that the United States has almost infinite potential and demand for reindustrialization. You may have heard of "reshoring," but it goes far beyond that. We have essentially lost the ability to manufacture the core building blocks of modern life: batteries, motors, small-scale semiconductors—the entire electricity supply chain is almost entirely dependent on overseas sources. What if there is a military conflict? What's even worse, did you know that China produces 90% of the world's synthetic ammonia? Once the supply is cut off, we can't even produce fertilizer and will face famine.
As long as you look to the physical world, you will find endless job opportunities that will benefit the country, create employment, and build essential infrastructure, all of which can receive bipartisan political support.
We have seen the economic and political winds shifting in this direction—discussions on reshoring, deep tech, and "American vitality." My prediction is that when AI impacts the white-collar sector, the path of least political resistance will be to fund large-scale reindustrialization, absorbing labor through a "giant employment project." Fortunately, the physical world does not have a "singularity"; it is constrained by friction.
We will rebuild bridges and roads. People will find that seeing tangible labor results is more fulfilling than spinning in the digital abstract world. The Salesforce senior product manager who lost a $180,000 salary may find a new job at the "California Seawater Desalination Plant" to end the 25-year drought. These facilities not only need to be built but also pursued with excellence and require long-term maintenance. As long as we are willing, the "Jevons Paradox" also applies to the physical world.
The goal of large-scale industrial engineering is abundance. The United States will once again achieve self-sufficiency, enabling large-scale, low-cost production. Moving beyond material scarcity is crucial: in the long run, if we do indeed lose a significant portion of white-collar jobs to AI, we must be able to maintain a high quality of life for the public. And as AI drives profit margins to zero, consumer goods will become extremely affordable, automatically fulfilling this objective.
My view is that different sectors of the economy will "take off" at different speeds, and the transformation in almost all areas will be slower than Citrini anticipates. To be clear, I am extremely bullish on AI and foresee a day when my own labor will be obsolete. But this will take time, and time gives us the opportunity to devise sound strategies.
At this point, preventing the kind of market collapse Citrini imagines is actually not difficult. The U.S. government's performance during the pandemic has demonstrated its proactive and decisive crisis response. If necessary, massive stimulus policies will quickly intervene. Although I am somewhat displeased by its inefficiency, that is not the focus. The focus is on safeguarding material prosperity in people's lives—a universal well-being that gives legitimacy to a nation and upholds the social contract, rather than stubbornly adhering to past accounting metrics or economic dogma.
If we can maintain sharpness and responsiveness in this slow but sure technological transformation, we will eventually emerge unscathed.
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