Bitcoin Dominance (BTC.d or BTCDOM) is Bitcoin's market share relative to the whole crypto market share. It’s calculated by dividing Bitcoin's market capitalization by the total market capitalization of all crypto currencies and multiplying it by 100.

For example: If Bitcoin's market capitalization is 2 Trillion and the market capitalization of all crypto currencies is 3.4 Trillion, BTC dominance would be: (2 / 3.4) * 100 = 58.8

In other words, Bitcoin makes up 58.8% of all crypto currencies.

Why is this interesting?

Bitcoin dominance gives you an idea where we could be in the market cycle.

If it rises it could either mean that Bitcoin price is going up and altcoins are staying flat or even declining.

If it goes down that either means Bitcoin price is going down or altcoins are growing in value.

Changes in the BTC.d could either mean that money is flowing from BTC to alts or vice versa or that new money is coming in for one of these sectors.

Historically, at the start of a bull market cycle, money flows into Bitcoin and Bitcoin dominance rises. At some point it tops and through a wealth effect it flows into alt coins, which leads to a further decline in BTC.d

Trading BTC.d index

What if there was a way to put money on BTC.d going up or down? This index is traded on Binance and Bitfinex and is also available as a long or short leg on the INTENT engine on Pear Protocol:

https://intent.pear.garden/trade/BTCDOM-USDC

How to use it for trading?

A) Long BTCDOM

Longing BTCDOM vs. USDC results in a straight long position

B) Short BTCDOM

Shorting BTCDOM vs. USDC results in a short position and is betting on altcoins to rise

C) As a short leg: Betting on the beginning of an altcoin season AND ethereum profiting

For example: Long ETH / Short BTCDOM 

D) As a long leg: Betting on the decline of altcoins and BTCs growth.

For example: When Bitcoin is showing strength and a small correction in Bitcoin lets altcoins correct 20-30%, Long BTCDOM / Short Meme coins

Recent BTCDOM trades and ideas

• BTC / BTCDOM

• SOL / BTCDOM

• BTCDOM / USDC

• USDC / BTCDOM

• DOGE / BTCDOM

• ETH / BTCDOM

• BTCDOM / XLM

by Yuvi (@crypto_yuvi), Conclave Head of DeFi

I recently started placing trades on Pear Protocol because I believe that pair trading is a fantastic way to bet on relative outperformance while mitigating the influence of extraneous variables. You can long one asset and short another, and if the market is influenced by something you had not considered, they are more likely to move together and allow you to focus on relative outperformance of the specific pair.

In doing so, I found myself swamped with tickers and ideas, and decision paralysis meant that I could never settle on a pair. So I set out to build a process that could help me synthesize the volumes of data that are available and find indicators for pair trading ideas that I could consider.

I shared some outputs with a few friends (s/o HanSolar) who helped me come up with ideas and indicators, so in this article I would like to share one particular tool that I have been using, and how my use developed in response to some losing trades.

The hypothesis is simple; tokens with large upcoming unlocks will not see commensurate demand to absorb supply.

To begin, I looked at the DefiLlama Unlocks dashboard (s/o DefiLlama). By downloading the same data that informs the unlock dashboard, I built a python script to parse it for my own dashboard.

Unlocks dashboard as at 07 Oct 24


Since this was a problem of supply and demand, I thought a good way to present the data would be an ‘average return over 14 days’ relative to the ‘next 30 day inflation rate’ per any unlocks occurring in the next 30 days, compared to the ‘expected analytical price action’.

The expected analytical price action is simply an inflation curve whereby no unlocks means no price movement, and 100% supply inflation corresponds with -50% price movement (if you double the supply, you half the value).

Output at 07 Oct 24


This simply provides another view of the unlock data, however an edge may lie in assessing market activity. In order to see if unlocks were priced in, I used the Binance public API to fetch the last two weeks of price action for each asset, and compare the average daily price movement to the expected price movement caused by upcoming inflation events. For any inflation rate caused by unlocks, the average price movement of the asset should correspond with the analytical expected price action curve, if the unlock is being priced in.

Lesson 1: Timeline. Unlocks will occur in the future, whereas the data I am looking at occurred in the past. Since the supply hasn’t hit the market yet, there is no material impetus for the price action of the asset to align with the expected curve. However, the opportunity here is to find the relative outperformers and look for likely cases of reversion.

It is critical to understand the context of these assets, what ‘unlock’ means, and what kind of liquidity they have. Having narrowed down opportunities to a few, I could go back to the unlock dashboard and take a look at the purpose of the unlock and what that supply was doing. Unlocking treasury assets? Less likely to get sold off. Early investor or advisor unlocks? More likely to get sold off. Similarly, a 2% depth calculation from the Binance API data could reveal illiquid assets. The context of an unlock is important to understand the effect it has on supply.

Output at 07 Oct 24



So now I had narrowed down my picks to a few assets whose unlocks I thought would hit the market, and whose price action I thought was not reflecting the upcoming influx.

Lesson 2:
Thematic pairs. Initially I was only looking for shorts and ignored the long side. I paired with majors because I assumed they would be less volatile, allowing me to focus on the inflating assets. I realized that this introduced more variables into the question of relative outperformance, because now network effects came into play. There is definitely a time and place for this, but I decided that I wanted even fewer variables influencing my trades, and I think this is where Pear protocol really sets itself apart. If the short token was an AI token, and the long was BTC, there were cases where the AI narrative saw a tailwind in the order books and even the lowest tier assets caught huge bids. Now, when I select a short leg based on this approach, I look for a theme-aligned long pair. If the short asset is a gaming token, I look for a relatively stronger looking gaming token. If the short asset is an AI token, I look for a relatively stronger looking AI token.

Narratives catching a bid was one hurdle to navigate, but has been easy enough to mitigate. Other hurdles have presented themselves with root causes that were much harder to identify. I recently opened a pair trade shorting $BIGTIME, before it launched up over 50% in a matter of days. I could not work out why. No other gaming tokens caught a bid, no other network tokens were up, and volume on Binance had barely moved.

Lesson 3:
Geography. Binance may have the deepest liquidity and typically the most volume, but it is not the only exchange. In the case of $BIGTIME, trading volume on Bithumb and Upbit, largely driven by Korean traders, had elevated to beyond BTC volumes. After losing a few trades to the Korean markets, I integrated Bithumb and Upbit volume data into my dashboard to help me identify cases where Korean market momentum might catch me off guard. Fool me twice, shame on me.

Output at 07 Oct 24


It’s not all pair trading, and I have other tools and indicators that I am using to inform my trades and help me generate ideas. My trading accounts are still small and I have gone from losing money to losing less money, which means I am trending towards not losing money, and perhaps will go as far as making money. One thing that is certain is that I will lose more trades. I know that and I am okay with it. My goal is to develop a process by which I win more trades than I lose, and hopefully in larger sizes. My pair trading process has evolved from ‘short token unlocks’, to quantitatively analyzing data and identifying relative outperformance to trade against.

by Chris Newhouse of Cumberland Labs (@CumberlandLabs)

Advisor to Pear Protocol

Pair trading has become a staple strategy for navigating volatile crypto markets. While it may sound simple—long one asset, short another—the success of this approach often hinges on selecting the correct leg to short. The goal of the short leg is to hedge the market risk while amplifying the relative outperformance of the long leg. In this article, we explore how to select the short leg, why it matters, and how to utilize a data-driven approach for success.

Why Choosing the Short Leg Matters

At the core of pair trading is the desire to exploit the relative movement between two assets. Ideally, the long asset should outperform, while the short asset either declines or remains neutral. This creates profit on both sides: gains on the long leg and losses (or minimal gains) on the short leg. The wrong short leg can negate the gains of the long leg, which is why careful selection is crucial.

For instance, in a typical Bitcoin (BTC) and Worldcoin (WLD) pair, if BTC rallies significantly while WLD stays flat or falls, the trader can capitalize on the BTC outperformance while minimizing overall market risk. However, if WLD suddenly outperforms BTC due to unforeseen events, the trade may underperform or even result in losses.

Data-Driven Criteria for Selecting the Short Leg

The choice of the short leg involves balancing several factors, all of which can be informed by data:

1. Correlation and Volatility

Pair trading relies on a certain level of correlation between the two assets. Highly correlated pairs tend to move together, which minimizes the risk of one leg significantly diverging from the other. For example, in high-frequency data, correlations between major blue-chip cryptos like BTC and ETH can exceed 90%. Ideally, the short leg should have a high correlation but exhibit greater downside volatility.

Data Tip: Look at historical correlation and volatility metrics over different time frames (e.g., daily, weekly, and monthly). This can be easily observed using pair charts, like ETH/BTC, to visualize how one asset performs relative to the other during different market conditions, as well as more sophisticated tools like Crypto Wizards.

2. Liquidity Considerations

The short leg should be liquid enough to handle large trades without significant slippage. Illiquid assets can be risky to short as sudden spikes in trading volume or market-moving news can drive sharp upward price movements.

Data Tip: Use liquidity metrics, such as order book depth and average daily trading volume, across popular exchanges like Binance (which supports over 250 trading pairs). Filtering the least liquid tokens out of your shortlist for the short leg will reduce the risk of price manipulation or large price movements due to thin order books.




3. Idiosyncratic Risks: Avoid Event-Driven Moves

Before choosing the short leg, it is critical to assess whether there are any upcoming events that could disproportionately affect its price. Regulatory changes, network upgrades, or high-profile partnerships can drive unpredictable volatility.

Data Tip: Keep a close eye on news feeds and calendar events. For example, if there’s a significant development like a protocol upgrade or token burn event, it may not be suitable for a short position. Using platforms that aggregate news and on-chain analytics will help traders avoid getting caught by surprise(Pear Things to Consider).

4. Relative Strength

An asset that shows signs of persistent weakness compared to its pair is often a good candidate for the short leg. This weakness can be gauged through technical indicators such as Relative Strength Index (RSI) or Moving Averages. If the asset is underperforming over multiple time frames, it signals a potential decline.

Data Tip: RSI and moving average crossovers (e.g., 50-day vs. 200-day) provide clear signals of relative weakness. Traders should also monitor whether the short leg has repeatedly failed to break through key resistance levels.

5. Funding Costs and Arbitrage Considerations

In perpetual futures markets, the funding rate is a critical consideration. A positive funding rate (where shorts receive funding and longs pay) can offer an additional layer of profitability. For example, if you are short ETH and the funding rate is positive, you receive a payment for holding the short position, which enhances your return.

Data Tip: Calculate net funding across the selected pair and include this in your decision-making process. Using funding heatmaps available on Binance and other exchanges can help identify pairs where shorting is more cost-effective, especially when the funding rate is positive.

Future Features for Data-Driven Trading on Pear Protocol

As pair trading evolves, so must the tools that support it. Pear Protocol has already established itself as a streamlined platform for executing pair trades, but there are several key features that could further enhance the trading experience and provide users with a more data-driven edge. Here are three features that I, as a trader, would like to see integrated into Pear Protocol in the future:

1. Screener for Long/Short Pair Selection

A robust screener that automatically suggests long and short pairs based on the criteria we've discussed—correlation, volatility, liquidity, and funding rates—would be a game-changer for traders. By integrating data analytics directly into the platform, Pear Protocol can offer traders the ability to quickly identify ideal pairs, removing much of the manual analysis required today. A screener could:

• Provide a ranked list of potential pairs based on customizable filters.

• Display real-time metrics such as correlation and historical volatility.

• Highlight optimal short-leg candidates with favorable funding rates or weaker relative strength.

This feature would empower traders to make quicker, more informed decisions and seamlessly find pairs that fit their trading strategy.

2. Market Overview Page with Emissions and Funding Data

Understanding tokenomics and funding rates is crucial for successful pair trading. A market page that provides real-time data on token emissions, alongside funding rates across popular exchanges, would offer valuable insights to traders looking to short tokens with high emissions or negative funding rates. Such a page could:

• Track tokens with low vs. high emissions, helping traders gauge potential supply pressure.

• Show funding rates in real-time, allowing traders to capitalize on favorable conditions for short positions.

• Include customizable alerts for funding rate changes or emissions announcements.

This would make Pear Protocol a one-stop hub for tokenomics and funding data, increasing its appeal to traders seeking data-driven advantages.

3. Unified Platform for Data and Analytics

The ultimate goal for Pear Protocol should be to become a fully integrated platform that seamlessly blends trading execution with powerful analytics. By consolidating all relevant data—correlations, volatility, liquidity, news events, and funding rates—Pear can become a go-to destination for traders who want not only to execute trades but also to analyze market conditions in real-time. Imagine having a dashboard that:

• Displays all the key data points needed for pair trading in one place.

• Provides predictive analytics based on past market behavior, helping traders anticipate trends.

• Allows for in-depth back-testing of pair trading strategies using historical data.

  
  

By evolving into a unified platform for trading and analytics, Pear Protocol can set itself apart from other platforms and attract a broader base of sophisticated traders.

In the previous article we discussed the different things to consider whilst pair trading. In this one we will look into one of it’s most popular use cases i.e. Narrative Trading.

In the fast-paced crypto world, narrative trading has emerged as a compelling strategy recently, driven by ever-changing paradigms, VC investments, and of course X influencers. Narrative trading revolves around the idea that market movements are often influenced not just by fundamentals but also word of mouth from Investors and market participants.

In this article, we'll explore the various facets of narrative trading and how pair trading can be leveraged in each instance to gain the most returns.

1) The News-based Beta

One of the critical drivers of narrative trading is news. News-based narratives can swiftly capture the attention of market participants and influence their decisions. Often, Insiders can pick to frontrun the news, and market participants react to it when it’s in the public domain.  Whether it's a technology development, a geopolitical event, a project rebranding, news triggers can set off a chain reaction of buying or selling as traders interpret and react to the latest information.

For example, Hong Kong 🇭🇰 #Bitcoin ETFs were launched on 30th April, which was bullish news for $BTC.There were also rumours of Etherium Foundation selling their $ETH, simultaneously, which was a catalyst to the bearish PA. Going Long on $BTC and short on $ETH was the favorable trade.

2) Hot Ball of Money on Crypto Twitter

Crypto Twitter (CT) is the biggest crypto marketplace.There are new metas, projects, themes, insider info to trade & speculate for traders every day. 

Here, the "hot ball of money" refers to the asset which is the flavor of the day/week/month and can be a potential blackhole, sucking all the liquidity.

For example-

A single tweet on $SOL from a prominent CT figure, let’s say Hsaka can spark a frenzy of buying from manlets, creating short-term price spikes or dips for an asset. Some Traders and bots who are quick to pick up on these tweets can profit handsomely. Next Day the playbook remains the same, but the asset is now changed to $AVAX to play a catchup play in the L1 sector.

In this situation, having $AVAX on the long leg, and $SOL for the short leg, can be a good plan to bet for the outperformance and rotation.

3) The Sector-based Meta

Another common narrative trading strategy revolves around sector-based narratives. This approach involves identifying broader trends or sectors of the cycle, picking up traction, and positioning yourself accordingly.

For instance, this cycle has been about AI coins due to advancements of the same and expanding use case in many industries including. Whereas, DeFi has been lacking behind in 2024, vastly due to lackluster performance of $ETH compared to $BTC. 

Here a long on $NEAR and a short on $ARB may be a good way to bet on the comparative performance of both the sectors. 

4) Fees Wars

In rare cases(especially on CT), narrative trading can be driven by more practical considerations such as fees of transactions. For example, in the world of DeFi, narratives around high gas fees on the Ethereum network during an activity spike have led to increased interest in alternative blockchains like L1’s.

This fees-driven narrative can influence trading patterns and contribute to shifts in market sentiment within the industry.For instance, during high activity on $ETH, it can observe a high transaction fee, and bearish price action due to competitive pressure. Going long on $SOL, and short on $ETH with a lower leverage can be a good bet in this case.

Conclusion

Narrative trading is a tricky approach for even highly sophisticated market participants(cough). By understanding and harnessing the power of narratives, traders can uncover unique opportunities and gain a dynamic edge above others. On Pear Protocol you can pick between at least 37 assets (with more being constantly added) to short/long based on the narrative you pick to play from the above.

Traders get access to digital asset prices either via:

1) Spot (no leverage)

2) Perpetuals (w/ leverage) 

Perps have been the preferred vehicle to amplify or fully implement your conviction.

However, with wild daily swings in asset prices, traders are limited to either: 

a) spot trading and capping their upside 

b) running a high risk of liquidation

What’s happening in practice is that up to 98% of traders using leverage get liquidated when trading perps.

Source

But what if you could shield yourself from this liquidation risk? Whilst maximising the potential upside for your view?

Example of Liquidations

Consider the SOL rally over the past 1 year (365 days).

The price has appreciated +611%, despite the recent correction.

Holding $1000 of spot to today would have returned you $6110. But not everyone has the cahones to hold, so lets say average return is $3000 for most who entered and exited spot at some point during the rally.

Clearly, if you were bullish $SOL, it would have made sense for you to use leverage to amplify your views. Let’s say with 10x leverage, and 600% return on SOL, the investor with $1000 stands to make $60,000. Now that’s more like it!

However, the problem here is that you can have the right view, but get rekt. This is depicted in the SOL Liquidation history below.

As per the data, there was >$500 million of long liquidations over the past year, which means lost capital for those who should have been right, and $billions of foregone profit. 

For example, on the week of March 11th, just before SOL broke out above $200 in price, these leveraged longs on Binance lost $30.35m of collateral due to some intraday moves to the downside.

Instead of doubling their $30.35m of collateral when the market moved another 10% (with 10x leverage), they lost ALL their margin due to liquidations.

There is nothing more frustrating than having the right view that SOL will outperform, but missing out.

Pairs-trading is a way of hedging your market risk (beta), and shielding yourself from liquidation risk, whilst still holding leveraged upside exposure to SOL.

Liquidations More Generally

We decided to zoom out and look more closely at Hyperliquid traders.

https://stats.hyperliquid.xyz/

Of the $2.4bn of total user deposits over the past 1 year, guess how much of that was liquidated? 

They are transparent about this - $3.2bn! 

That means >100% of deposits was eventually liquidated. How? Traders win on the way up, they have unrealised gains, and then lose their gains and their collateral in short term wicks during market turmoil.

If we extrapolate out to other CEXes like Binance, Bybit and OKX those numbers run >$100bn. 

How can we keep our gains when you have the right view?

Let’s take a deeper look.

Pair Trading

Pair trading is a new financial primitive conceived to enable investors to leverage their views while minimizing the risk of short-term liquidation due to systematic market movements. 

These short-lived but impactful blips frequently trigger waves of liquidation that further snowball across the crypto market.

The short-term protection arises because of the greater short-term correlation between crypto-assets: over short horizons, most risk assets move in tandem (aggresively down), while over the long-term, one asset tends to outperform the other - leading to opportunities to capture the relative value. One way to achieve this is to simultaneously short a correlated asset like $ETH, which is a good proxy for market risk. This is denoted as being long SOL / ETH.

On one of these down days, if SOL is -5%, and ETH is -10%, then you’ve made a net return of +5%. With 10x leverage thats a +50% move in a single day. Your collateral is cross-margined, meaning that the positive PnL on the short eth leg is used to offset the negative PnL on the long sol eth. This way we get to stay long SOL even during the downturns, whilst still maintaining 10x leverage.

Understanding What the Short-and-Long-Term Dynamics of Asset Prices

The price of cryptocurrencies can be dissected into two main components:

- Systematic Component: Market-wide influences affecting all coins.

- Idiosyncratic Component: Specific factors affecting individual coins.

Over the long term, idiosyncratic factors dominate — companies outperform because of their “fundamentals”.

Conversely, in the short term, systematic factors prevail, with markets seemingly overreacting to news. This apparent overreaction is not due to irrational investor radically altering their assessment of fundamental value, but to changing risk aversion, and to the impact of flows (which can snowball into liquidations)

The Time Structure of Correlations

Empirical data shows that correlations between coin prices vary with time frames:

- At lower frequencies, correlations are typically weak (less than 40%).

- At higher frequencies, correlations surge (often exceeding 90% for 1-minute ticks).

Systematic jumps, particularly those impacting Ethereum (the crypto benchmark), propagate quickly across the market. However, the reverse is less true: there is a greater probability that a shock affecting a single 

As is well known (see e.g. Pindyck, 1984), correlations increase with volatility. This also explains why over the recent highly volatile period, high-frequency correlations have been particularly high.

Graphs

Image 1: one thousand weekly returns

At low frequency, correlations between blue-chip crypto assets are typically less than 50%; they are close to zero between blue-chips and meme coins

Image 2: one thousand daily returns

At medium frequency, correlations between blue-chip crypto assets are typically around 70%; they are close to 50% between blue-chips and meme coins

Image 3: 90 days of 1 minute returns

At higher frequency, correlations become quite high across the board between similar assets

Image 4: 30 days of 1 minute returns

Overly volatile periods such as the last 30 days (June 2024), one-minute correlations are very high across all assets. It is during these volatile periods that the most dramatic liquidations occur, and that pair trading offer the greatest protection.

Image 5: 30 days of conditional jump corelations (over 1 minute returns)

One can also measure correlations conditional to a jump happening on any given asset — this table measures correlation only when a jump ( one minute return greater than 3 standard deviations of returns ) occurs for the asset the row index.

During volatile periods, these correlations are extreme too. This is called scam-wick protection.

Conclusion: Scam-Wick Protection from Pair Trading

Pair trading mainly enables investors to shed themselves from short-term liquidation risk that arises from the frequent extreme downside movements in crypto-assets.

During times of volatility, correlation typically goes to 1:1, allowing gains on the short leg to offset losses on the long leg. Whilst in the good times, your long leg outperforms the other asset because they are sufficiently de-correlated on longer time horizons. Pair trading leads to a more controlled trading environment, providing some degree of liquidation protection. We call this scam-wick protection, and it’s something that is available through our dynamic cross-margin pair trading engine powered by SYMM.

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Article written by mazett and huf

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Academic References

Andersen, T.G., Bollerslev, T., Diebold, F.X., & Ebens, H. (2001). Journal of Financial Economics, 61(1). The Distribution of Realized Stock Return Volatility. 

Andersen, T.G., Bollerslev, T., Diebold, F.X., & Wu, J. (2005). American Economic Review, 95(2). A Framework for Exploring the Macroeconomic Determinants of Systematic Risk. 

Barndorff-Nielsen, E., and ,Shephard N., (2006). Journal of Financial Econometrics 4(1). 

Econometrics of Testing for Jumps in Financial Economics Using Bipower Variation

Bollerslev, T., Tauchen, G., & Zhou, H. (2009). Review of Financial Studies, 22(11). Expected Stock Returns and Variance Risk Premia

Bandi, F.M., & Perron, B. (2006). Journal of Financial Econometrics, 4(1). Long Memory and the Term Structure of Volatility: New Evidence from the French Stock Market.

Pindyck, R.S. (1984). National Bureau of Economic Research. Risk Aversion and Determinants of Stock Price Volatility. 

Schwert, G.W. (1989). Journal of Finance, 44. Why Does Stock Market Volatility Change Over Time?

Hey Anon,

Have you ever sat and watched as other tokens in your sector (AI, gaming, memes) rally, but you seem to be holding the wrong ones. We have all been there!

Token Baskets or Indices (e.g. GMCI30, GMMEME), contains a collection of specific tokens, and have been a preferred way for many traders to diversify their bets for decades now. It can also come in handy with pair trading to further decrease risk and maximize returns.

So, let us dig deeper into the world of crypto indices, and how to use them in your trading!

1) What Are Indices?

Indices track the performance of a group (or basket) of assets, providing a benchmark for evaluating market trends. They aggregate price data from multiple assets to represent the sectors' overall movement and health. For example, a memecoin basket tracks the performance of a number of different meme tokens, whereas a gaming basket tracks the performance of a number of….you guessed it, different gaming tokens.

Within crypto, GMCI leads the way with a diverse suite of indices.

Their indices deliver the transparency and robustness expected from traditional financial markets while leveraging the ever-changing narratives in the crypto space. Understanding their methodology is essential to recognizing the value of their indices.

2) How Are They Constructed?

The selection of assets for inclusion in the indices follows a rigorous process, some include: Security Designation, Asset Universe Eligibility, Asset Exclusion Criteria, Pricing Input Source, Circulating Market Capitalization Input Source, Blended Circulating Market Capitalization,and others. These steps ensure that only assets meeting their stringent criteria are included, thus maintaining the indices' accuracy and use case. 

Let us look at two GMCI token indices launched on Pear Protocol.

1) GMCI 30 (BTC, ETH, BNB, etc)

“GMCI 30” represents a selection of the top 30 cryptocurrencies, highlighting the leading players in the market. It is a way for participants to bet on the market's core strength and primary drivers. The index provides a solid way to determine the risk appetite in the market by featuring stalwarts like Bitcoin and Ethereum.

2) GMMeme (SHIB, DOGE, PEPE, etc)

The "GMMeme" index comprises the leading meme coins by market capitalization, capturing the unique autism intrinsic to crypto communities. It highlights meme coins that have captured the most attention and engagement from degens on Crypto Twitter.

3) How to Pair Trade with GMCI Indices?

Here are three ways to combine the GMCI Indices at Pear protocol with your Pair Trading.

a) To Mitigate Risk- There are many cases of crypto tradoors blowing accounts due to major exploits in a particular coin in an otherwise booming sector. For instance, FUD around $WIF can cause liquidation cascade while other meme coins keep outperforming boomer coins.

To reduce this risk, one can long GMMeme Index (SHIB, DOGE, PEPE), short $ETH to bet the out-performance of memes against majors.

b) On the Short Leg- Shorting a particular Meme coin is a tricky task. They can pump or dump by double digit numbers out of nowhere with little narrative behind them. Hence, To select one meme for the short leg in a pair trade can be risky. It is where GMCI Meme Index comes handy, which can be used for the short leg and depends on the average movement in all the three assets it contains.

c) Gauge the Market Sentiment- The performance of GMCI 30 which includes BTC, ETH, BNB, and many other assets can also serve as a gauge for the risk appetite of traders.

If the performance is starting to trend up, it is a sign to bet more. On the other hand, if you see exhaustion in the average price of the index, it is a sign to take foot off the pedal from trading and prepare yourself for the chop which comes next. Our Top movers in Indices Tab can provide a general view of market referring to performances of both index against individual tokens.

Stemming from observations in previous articles, traders face issues such as operational complexity, capital inefficiency, and custody concerns when executing pair trades on CEXs and DEXs alike.

Pear Protocol aims to solve these challenges by offering a streamlined and decentralized platform for pair trading. To get more context, one can read the previous articles present in the education hub on our platform.

Introduction

Pair trading has gained traction in the crypto market as traders seek different strategies to navigate the ongoing trends and narratives. However, this approach demands a comprehensive understanding of market dynamics and risk management principles.

With Pear Protocol in mind, we delve into essential considerations for tradoors looking to optimize their pair trading strategies

1) Choose Which Asset to Long/Short

The success of pair trading hinges on selecting the right assets/pair to trade. D’uh!

You can utilize market trends, fundamental analysis, and technical indicators in determining which assets to long and short simultaneously. The asset picked for the long leg, must show comparative strength against the asset picked for the short leg.

For instance, The golden trick on Crypto Twitter back in the day used to be long whatever Hsaka has tweeted about, and short whatever Bitboy shills after the first pump.

2) Which Asset Moves Faster?

Understanding the correlation between paired assets is paramount. High correlation indicates a strong relationship between assets (good for pair trading), while low correlation suggests muted movement with respect to each other (bad for pair trading). 

One way to find an outperformer is also to go through a spaghetti chart, it helps to find the faster horse.

With time more and more traders have started using Pair Charts, which signify strength against the denomination. For instance, here is an ETH/BTC chart which comes in handy when making a correlation between the two assets. The previous PA shows it to be an excellent region to bounce. Hence, initiating a long position on Ethereum (ETH) while concurrently shorting Bitcoin (BTC) may be deemed judicious for capturing the anticipated upward movement in the market.

Pairing assets with a balanced correlation can enhance your trading risk/reward, while mitigating risk.

3) Deciding The Degree Of Leverage

Leverage amplifies trading positions' exposure to market fluctuations, increasing both profits and losses. Always consider the downside risk. A rule of thumb is to push the leverage button to the west while entering a position before confirmation of your levels. Bet more, and push the leverage button to the east once you have had confirmation/reclaim aligning with your trade direction.

Opting for conservative leverage can safeguard against excessive risk exposure, promotes long-term growth, and can be perfect for your PNL curve.

4) Net Funding

If you are active on Crypto Twitter, you must have seen many refer to these funding heatmaps to figure out the signs of froth in the market.

Funding is simply the cost of you holding a long/short position. In pair trading, you pay funding on one leg and receive on the other. Net Funding is the cumulative of funding for both the legs involved in pear trading, it makes it a necessary factor to consider when pair trading. We can calculate the same as follows-

you pay the funding rate to be long (A)

you receive the funding rate to be short (B)

net funding = A+B

e.g. ETH above

-0.038% (pay) + 0.006% (receive) = -0.032% on the notional every 8h

These can be indicative/expected levels.

5) Market & News Induced Volatility

In the trenches of the bear market, we all saw Gary Gensler coming for the crypto industry, and at times coming for particular projects as well. These types of events can induce market volatility and can affect your pair trading as well. For instance, you being a sophisticated trader have sniped what you believe to be the pico bottom of ETH/BTC, and have longed it. Next day, Gary Gensler is on CNBC talking about how he plans to launch a campaign to classify Ethereum, the second-most popular cryptocurrency, as a security. Not only, the market will react to the news, but also affect your current running pair trade. Therefore, it is necessary to keep a track of news around the coins you trade in a pair, and lookout for the events which can cause extreme market volatility. 

Above are the most essential things to consider before entering your pair trade on Pear Protocol.

Hop on to the Pear Train now!

Pairs trading has become a popular trading strategy especially on Crypto Twitter, where users long one asset (say ETH) and short another against it (SOL). This is expressed as ETH/SOL.

This idea of being long one asset, and short another can be applied to any two assets in the market e.g. LINK/PYTH, OP/ARB, WIF/BONK, where you believe the first one will outperform the other asset.

1) Pair Trading in A Rising Market

One common mid-curve take is that pair trading is more risky since you’re shorting something.

Anons, you cannot be more wrong, because even if SOL goes up (and you are short), you hope you make more on the long ETH leg as Ethereum eventually outperforms Solana on the leg up.

i.e. you make the ‘spread’ between the two. This is where leverage goes into play. Say ETH/SOL moves 5% in your favor (as per the image). With 10x, you’ve made 50%, all with much less risk than if you were outright long or short. Why is it less risky? Because it doesn’t matter if the market goes up, down or sideways. The real power in pair trading is that it can work in different market scenarios.

2) Pair Trading in A Falling Market

The US Government has just sold more Silk Road Bitcoins, the market is red, wyd? As we’ve seen, pair trading can work well in up-trending markets. But what if the trend is downwards?

Well, in this scenario you hope to make an offsetting amount of PnL (and more) from your SOL short leg. Let’s say ETH is -5%, and SOL is -8%. In this example you’ve made +3%

Again, let’s say with 10x leverage that would have gained a profit of 30%. So as you can see, you can make money pair trading regardless of if the broader market is green or red. 

But how about in sideways/choppy markets?

3) Pair Trading in A Ranging Market

Lastly, using the same logic, pair trading can work in choppy aka crab markets. Let’s take the example where markets have not really moved much and ETH is +2%, whilst SOL is +1%.

In the example above, the spread is positive and with x10 leverage you would have gained +10% in otherwise benign and boring market conditions.

When you’re wrong

The time when you’re wrong will be when you chose an asset that doesn’t outperform the other for whatever reason. This is why we consider this type of trading to be narrative trading - you want to long the things that are attracting volume and attention, and short the unloved ones that can’t keep pace.

Like all trading, you have to be conscious of taking profits when moves seem over-extended. Thankfully on Pear Protocol you can chart these different pair trades automatically simply by choosing a long and a short and see how it evolves over time.

Why Pair Trade?

To summarize, pair trading is a strategy that works in all market conditions and allows you to generate returns in a risk-optimized manner.

Compared to outright longing and shorting stuff, here are some other reasons to pair trade:

• Less risk of liquidation

• Somewhat market neutral

• Less volatility, yes you can sleep better with positions open

• Can amplify returns via leverage for real this time

• Narrative based trading

It’s a powerful tool in a trader’s arsenal, and now with Pear Protocol you can easily create your own pair trades with 1 click.

Try it now.

If you have followed our previous articles, you’ll understand the premise and use case behind pairs trading. Basically, you can make money in almost all market scenarios. But how can a sophisticated connoisseur like yourself decide which pairs to trade?

1) Narrative Driven 

Pair trading is all about finding assets that may become outliers. This is often narrative-driven. For instance, with increasingly centralized exchanges shutting down in many countries, decentralized exchanges like DYDX and Vertex will continue to grow and take market share from their CEX counterparts like Binance and OKX.

How could you capture this narrative? One idea might be to long $DYDX and short $BNB.

Another Narrative To Trade for this Cycle. 

Another trending narrative is AI and Decentralized Science, with tokens like $FET, $RNDR, $TAO all catching a strong bid and outperforming the market. Yes, you could outright just long these, but if the market drops you’ll be sitting on a big loss. Here you could pair trade it with some boomer tech like $ETC for a short & manage your risk.

long $RNDR/ short $ETC

2) Technical Analysis Driven

You could also take a more technical/charting approach. For instance, sitting at your desk, you find that one chart you have been looking for while $BTC sucks liquidity from every alt. 

Looking at $MATIC, it appears to have bottomed against $BTC, and other assets like $ETH as well. The way to express this as a pair trade would be to long MATIC / BTC, again all possible through Pair Trading via Pear Protocol.

3) Environment & News Driven

Even if you have been living in your Mom’s basement like most Crypto participants, you must know the news around $BTC’s approved ETFs. The demand for Bitcoin has increased ever since with the price, before and even after the approval announcements. Amidst, ETH has underperformed vastly going into the approval, and even after it. So much so that it has almost become a meme for this cycle till now.

The word is $ETH will have an ETF of its own around this May. A bet for ETH’s outperformance has favorable odds and can be possible by longing $ETH and shorting $BTC simultaneously. All Possible on Pear Protocol, with a single click.

4) Musical Chairs

If you have spent enough time on Crypto Twitter, you must have laid eyes on this picture. The typical money flow in the past goes- Bitcoin > Ethereum > Large Caps > Smaller market cap altcoins. One can leverage the transition of phases by shorting the prior one and longing the latter one using Pear Protocol. For instance, at the start of big buy-ups in large caps, one can short $ETH and long the likes of $AVAX simultaneously.

The key benefits of pair trading are:

• Less likely to get liquidated

• Somewhat market-neutral 

• Less volatility

• Can amplify returns via leverage

• Narrative-based trading

• Can capture value in varying market phases

Hop on to the Pear Train now!