The cryptocurrency market has witnessed a significant adoption of automated trading solutions, with trading robots increasingly standing out for their ability to analyze vast amounts of data and execute trades with precision.

This article delves into the historical performance of trading robots and the dramatic fluctuations in token prices. By backtesting strategy returns against the "buy-and-hold" benchmark, it decodes which robots have performed the best in specific market cycles and their shining moments. This helps you match the best trading robot based on your investment style and risk tolerance.

The study focuses on three types of trading robots: Telegram-based DEX trading robots; non-Telegram robots trading on DEX and centralized exchanges (CEX); and the recently evolving AI agent robots.

Choosing the right trading robot depends on the user's goals, risk tolerance, and experience.

In short:

• Telegram Bots are ideal for opportunistic trading scenarios that require quick reactions and timing, such as token launches and meme coins.

• AI Agent Robots (e.g., ai16z or Virtuals) are suitable for users who want fully automated operations and are willing to experiment with cutting-edge strategies.

• CEX Robots offer the most control and are best suited for executing structured strategies, such as dollar-cost averaging (DCA), grid trading, or signal-based trading.

Who is the Bull and Bear Market Trading Power Tool? A Deep Dive into TG, AI Agents, and DEX/CEX Trading Bots

Trading Bot Strategies and Performance

Trading robots are complex automated systems that analyze cryptocurrency market data through algorithms and execute trades autonomously on centralized exchanges or decentralized platforms. These systems typically operate 24/7, 365 days a year, with minimal human intervention. Their core function is to analyze vast amounts of real-time and historical market data, including key metrics such as price fluctuations, trading volume, and order book information.

Using AI agent trading robots offers many potential advantages. Their continuous operation ensures no trading opportunity is missed, as these robots can monitor the market around the clock and adapt to the dynamic changes of global markets. Some platforms offering such robots also provide backtesting features, allowing users to evaluate the potential effectiveness of different trading strategies using historical data before committing real funds to actual trading.

Telegram DEX Bots

Telegram trading bots operate on the Telegram platform, leveraging its convenience and real-time communication advantages to execute trades directly on decentralized exchanges. These bots typically focus on enhancing trading speed and sniping new tokens, especially appealing to users of ecosystems like Solana. The latest protocols have integrated features commonly found in centralized exchange trading bots, such as grid trading, dollar-cost averaging (DCA), and limit order strategies.

Telegram bots, such as Maestro and Unibot, first emerged around 2020-2021. By 2022, many of these bots had begun offering advanced features like social trading and arbitrage.

By the end of 2023, Solana-based trading bots (such as BONKBot and Trojan Bot) gained attention for their ability to quickly trade meme coins on decentralized exchanges. The biggest advantage of these Telegram bots is that users can complete trades directly on mobile devices without needing browser extensions to connect wallets. This feature greatly enhances the ease of mobile trading while strengthening market monitoring functions and seamless integration with social networks.

In terms of historical trading volume, the top five cross-blockchain Telegram bots are Trojan, BonkBot, Maestro, Banana Gun, and Sol Trading Bot. Over the past 90 days, the majority of trading volume has occurred on the Solana blockchain, with all five of these top Telegram bots operating on the Solana chain.

DEX Trading Bot Battle Source: Dune Analytics

Telegram Bots: Functionality and Performance

Telegram bots offer very similar functionalities, with differences lying in whether some (such as Maestro and Banana Gun) focus on multi-chain operations while others concentrate on the Solana chain.

The primary use of Telegram bots is to automatically identify profitable entry and exit points for trades and execute them quickly. However, since individual user profits and losses per trade are difficult to track, some Telegram bots (like Banana Gun and BonkBot) use a revenue-sharing model tied to their tokens. They repurchase their own tokens with a 1% fee collected, using token prices and protocol revenue (collected fees) as approximate indicators of the trading bot's market performance.

Daily Revenue of Telegram Bots (USD) Source: Dune Dashboard

Daily Revenue as a Percentage of Total Revenue Source: Dune Dashboard

Telegram DEX Bot Revenue Over the Past 6 Months

Over the past six months, Trojan has had the highest nominal fee amount (approximately $109 million), while Sol Trading Bot has shown the best median daily revenue when normalized against total revenue.

Both peaked during the meme coin frenzy around January 2025, but are currently facing a sharp decline in revenue due to the broader market downturn.

Daily Token Price Change Percentage Source: Dune Analytics

BANANA and BONK Token Price Performance

Over the past six months, the price trends have shown that, aside from a significant rise in the BONK token in November 2024, the performance of the two Telegram bots that share revenue through tokens—Banana Gun and BonkBot—has been very similar. In the recent bearish market environment, both have experienced significant price drops.

AI Agent Bots

AI agent trading robots are highly complex automated systems that use artificial intelligence (AI) and machine learning (ML) algorithms to analyze cryptocurrency market data and execute trades autonomously.

The term "agent" implies that these robots have a degree of autonomy and decision-making capability that goes beyond the rule-based operations of traditional automated trading systems. The most well-known AI agent frameworks currently are Virtuals and ai16z.

AI Agent Robot Comparison

Virtuals Protocol was launched on the Ethereum Layer 2 network Base in October 2024. It is an AI agent generation platform designed to simplify the creation and deployment of AI agents on the blockchain. Although the protocol is not specifically designed for trading, its platform supports the development of AI agents that may be used for trading purposes. For example, the experimental AI agent Aixbt on the platform can track hot topics discussed on social media X, identify potential market signals from user conversations, and generate strategy recommendations to assist trading decisions.

Since the Virtuals protocol adopts a LaunchPad model, where various agents (such as LUNA and AIXBT) are issued as independent tokens and operate in multiple different fields including gaming, trading, and entertainment, we will focus on analyzing the market performance of the largest market cap trading agent token on the platform: AIXBT.

AIXBT Price History Source: CoinMarketCap

ai16z is an AI-driven trading fund operating on the Solana blockchain. Launched in October 2024, the fund uses a complex AI agent built on the Eliza framework to autonomously analyze market price fluctuations, social media sentiment, and on-chain data, and execute trading decisions.

The fund operates as a decentralized autonomous organization (DAO), allowing its native token holders to participate in key governance decisions through voting and influence trading strategies via a "virtual trust market." The virtual fund manager AI Marc, built on the Eliza framework, is responsible for managing the fund's trading activities. The AI16Z token represents fund ownership and grants governance rights, with the agent's operations directly impacting the token's value.

AI16Z Price History Source: CoinMarketCap

By comparing the trading volume data of these two agents, it can be seen that both peaked in January 2025, with AI16Z reaching a trading volume of $501 million, while AIXBT set a higher record at $682 million. It is worth noting that the price peak of AI16Z occurred slightly earlier than its trading volume peak, while the price and trading volume peaks of AIXBT were essentially synchronized, showing a tighter correlation over time.

AI16Z and AIXBT Price and Trading Volume Comparison Source: CoinMarketCap

AI16Z and AIXBT Price Performance

AIXBT has outperformed AI16Z in terms of price performance. During the peak period in November 2024, its token price surged nearly 4,000 times from the initial issuance price, while AI16Z only reached an increase of about 111 times during the same period. Even after recent declines and in the context of a downward market trend, the latest price records as of the end of March 2025 show that AIXBT still maintains a 478 times increase from its initial price, while AI16Z remains at a 6.8 times level.

DEX/CEX Bots

These platforms are web-based and operate independently of Telegram. Users can either connect their wallets directly to trade on DEX or link to CEX via API interfaces or simple login methods. These functions are part of the integrated exchange solutions provided by the platforms.

These web-based platforms offer a wide range of strategy options and broader market access channels. In terms of functional design, they cater to users' needs for CEX liquidity and reliability, as well as the non-custodial and decentralized characteristics of DEX. Some platforms also support one-click switching between DEX and CEX, making it more convenient to capture price differences between centralized and decentralized exchanges (i.e., CEX-DEX arbitrage opportunities).

Common Strategies on These Platforms

The most common strategies on these platforms include grid trading, dollar-cost averaging, and signal bots. Dollar-cost averaging bots invest a fixed amount of money into cryptocurrencies at regular time intervals, regardless of asset price fluctuations. The core idea of this strategy is to spread entry points over time to mitigate the impact of market volatility. This strategy often performs well in markets with clear trends.

Grid trading bots are designed for active trading, profiting from price fluctuations through a structured strategy of buying low and selling high. The bot places a series of limit buy and sell orders at preset intervals above and below a predetermined price range, creating an order "grid." Each completed cycle of buying low and selling high generates profit, making this strategy most effective in sideways markets with significant volatility.

Signal trading bots execute trades based on external signals, which usually come from technical indicators, market analysis, or third-party services. Common signal indicators include the Relative Strength Index (RSI), Exponential Moving Average (EMA), and Bollinger Bands.

Comparison of Different DEX/CEX Strategies

Historical Performance of Three Token Pairs Under Three Trading Strategies

The table below shows the historical performance of the BTC/USDT, ETH/USDT, and SOL/USDT token pairs under three trading strategies. The grid trading bot's parameter selection used the AI-optimized feature built into the 3Commas platform to automatically choose the best parameters. For dollar-cost averaging, it used the most popular classic trading strategy among the platform's users.

For signal bots, Dash2Trade offers strategy presets, with the system automatically selecting the optimal strategy for each token. These strategies have been backtested using the platform's proprietary trading system and have been applied to live market trading, but their validity is limited to the trading cycle within 120 days before January 26, 2025.

Due to the lack of consistently available data across platforms, we used three backtesting periods for each strategy. The table below shows the simple price changes within the corresponding periods, which also represent the returns of the simple benchmark buy-and-hold strategy.

DEX/CEX Bot Strategy Returns

Existing Data Indicates Significant Variability in Trading Bot Performance

The existing data shows that the performance of trading bots can vary significantly, depending on the specific trading bot used, the trading strategy employed, and the market conditions at the time of backtesting.

Bitcoin and Ethereum Prices Data Source: CoinMarketCap

During the 120-day backtesting period from September 26, 2024, to January 26, 2025, Bitcoin, Ethereum, and Solana all showed upward trends, with buy-and-hold returns of 58%, 23%, and 55%, respectively. During this period, the strategy performance of signal bots was essentially on par with the buy-and-hold strategy (slightly underperforming for some tokens), with Bitcoin strategy returns at 58.15%, Ethereum at 16.79%, and Solana at 48.68%.

In the same 120-day period from December 4, 2024, to April 4, 2025 (during which the grid bot strategy was backtested), the market prices of Bitcoin, Ethereum, and Solana all showed downward trends, with buy-and-hold strategy returns of -16%, -53%, and -49%, respectively. This was a stark contrast to the market environment in the previous 120-day backtesting period. In a market with a clear downward trend and significant volatility, the grid bot strategy significantly outperformed the buy-and-hold strategy, generating positive returns for BTC (9.6%), ETH (10.4%), and SOL (21.88%).

Bitcoin and Solana Prices Data Source: CoinMarketCap

During the longest 180-day backtesting period from October 4, 2024, to April 4, 2025, when the DCA bot was backtested, the buy-and-hold strategy returns for Bitcoin, Ethereum, and Solana were 34%, -25%, and -18%, respectively. In stark contrast, the performance of the signal bot strategy for these three tokens diverged significantly from the buy-and-hold strategy.

For Bitcoin, using the DCA bot resulted in a return of 17.75%, underperforming the one-time buy-and-hold strategy. However, for Ethereum (ETH, 58.12%) and Solana (SOL, 80.92%), the DCA returns significantly outperformed a one-time investment. This discrepancy may be due to the higher volatility of ETH and SOL compared to BTC during the statistical period, with the DCA strategy effectively reducing timing risk by batching investments and spreading entry prices.

The cryptocurrency market has witnessed a significant adoption of automated trading solutions, with trading robots increasingly standing out for their ability to analyze vast amounts of data and execute trades with precision.

This article delves into the historical performance of trading robots and the dramatic fluctuations in token prices. By backtesting strategy returns against the "buy-and-hold" benchmark, it decodes which robots have performed the best in specific market cycles and their shining moments. This helps you match the best trading robot based on your investment style and risk tolerance.

The study focuses on three types of trading robots: Telegram-based DEX trading robots; non-Telegram robots trading on DEX and centralized exchanges (CEX); and the recently evolving AI agent robots.

Choosing the right trading robot depends on the user's goals, risk tolerance, and experience.

In short:

• Telegram Bots are ideal for opportunistic trading scenarios that require quick reactions and timing, such as token launches and meme coins.

• AI Agent Robots (e.g., ai16z or Virtuals) are suitable for users who want fully automated operations and are willing to experiment with cutting-edge strategies.

• CEX Robots offer the most control and are best suited for executing structured strategies, such as dollar-cost averaging (DCA), grid trading, or signal-based trading.

Who is the Bull and Bear Market Trading Power Tool? A Deep Dive into TG, AI Agents, and DEX/CEX Trading Bots

Trading Bot Strategies and Performance

Trading robots are complex automated systems that analyze cryptocurrency market data through algorithms and execute trades autonomously on centralized exchanges or decentralized platforms. These systems typically operate 24/7, 365 days a year, with minimal human intervention. Their core function is to analyze vast amounts of real-time and historical market data, including key metrics such as price fluctuations, trading volume, and order book information.

Using AI agent trading robots offers many potential advantages. Their continuous operation ensures no trading opportunity is missed, as these robots can monitor the market around the clock and adapt to the dynamic changes of global markets. Some platforms offering such robots also provide backtesting features, allowing users to evaluate the potential effectiveness of different trading strategies using historical data before committing real funds to actual trading.

Telegram DEX Bots

Telegram trading bots operate on the Telegram platform, leveraging its convenience and real-time communication advantages to execute trades directly on decentralized exchanges. These bots typically focus on enhancing trading speed and sniping new tokens, especially appealing to users of ecosystems like Solana. The latest protocols have integrated features commonly found in centralized exchange trading bots, such as grid trading, dollar-cost averaging (DCA), and limit order strategies.

Telegram bots, such as Maestro and Unibot, first emerged around 2020-2021. By 2022, many of these bots had begun offering advanced features like social trading and arbitrage.

By the end of 2023, Solana-based trading bots (such as BONKBot and Trojan Bot) gained attention for their ability to quickly trade meme coins on decentralized exchanges. The biggest advantage of these Telegram bots is that users can complete trades directly on mobile devices without needing browser extensions to connect wallets. This feature greatly enhances the ease of mobile trading while strengthening market monitoring functions and seamless integration with social networks.

In terms of historical trading volume, the top five cross-blockchain Telegram bots are Trojan, BonkBot, Maestro, Banana Gun, and Sol Trading Bot. Over the past 90 days, the majority of trading volume has occurred on the Solana blockchain, with all five of these top Telegram bots operating on the Solana chain.

DEX Trading Bot Battle Source: Dune Analytics

Telegram Bots: Functionality and Performance

Telegram bots offer very similar functionalities, with differences lying in whether some (such as Maestro and Banana Gun) focus on multi-chain operations while others concentrate on the Solana chain.

The primary use of Telegram bots is to automatically identify profitable entry and exit points for trades and execute them quickly. However, since individual user profits and losses per trade are difficult to track, some Telegram bots (like Banana Gun and BonkBot) use a revenue-sharing model tied to their tokens. They repurchase their own tokens with a 1% fee collected, using token prices and protocol revenue (collected fees) as approximate indicators of the trading bot's market performance.

Daily Revenue of Telegram Bots (USD) Source: Dune Dashboard

Daily Revenue as a Percentage of Total Revenue Source: Dune Dashboard

Telegram DEX Bot Revenue Over the Past 6 Months

Over the past six months, Trojan has had the highest nominal fee amount (approximately $109 million), while Sol Trading Bot has shown the best median daily revenue when normalized against total revenue.

Both peaked during the meme coin frenzy around January 2025, but are currently facing a sharp decline in revenue due to the broader market downturn.

Daily Token Price Change Percentage Source: Dune Analytics

BANANA and BONK Token Price Performance

Over the past six months, the price trends have shown that, aside from a significant rise in the BONK token in November 2024, the performance of the two Telegram bots that share revenue through tokens—Banana Gun and BonkBot—has been very similar. In the recent bearish market environment, both have experienced significant price drops.

AI Agent Bots

AI agent trading robots are highly complex automated systems that use artificial intelligence (AI) and machine learning (ML) algorithms to analyze cryptocurrency market data and execute trades autonomously.

The term "agent" implies that these robots have a degree of autonomy and decision-making capability that goes beyond the rule-based operations of traditional automated trading systems. The most well-known AI agent frameworks currently are Virtuals and ai16z.

AI Agent Robot Comparison

Virtuals Protocol was launched on the Ethereum Layer 2 network Base in October 2024. It is an AI agent generation platform designed to simplify the creation and deployment of AI agents on the blockchain. Although the protocol is not specifically designed for trading, its platform supports the development of AI agents that may be used for trading purposes. For example, the experimental AI agent Aixbt on the platform can track hot topics discussed on social media X, identify potential market signals from user conversations, and generate strategy recommendations to assist trading decisions.

Since the Virtuals protocol adopts a LaunchPad model, where various agents (such as LUNA and AIXBT) are issued as independent tokens and operate in multiple different fields including gaming, trading, and entertainment, we will focus on analyzing the market performance of the largest market cap trading agent token on the platform: AIXBT.

AIXBT Price History Source: CoinMarketCap

ai16z is an AI-driven trading fund operating on the Solana blockchain. Launched in October 2024, the fund uses a complex AI agent built on the Eliza framework to autonomously analyze market price fluctuations, social media sentiment, and on-chain data, and execute trading decisions.

The fund operates as a decentralized autonomous organization (DAO), allowing its native token holders to participate in key governance decisions through voting and influence trading strategies via a "virtual trust market." The virtual fund manager AI Marc, built on the Eliza framework, is responsible for managing the fund's trading activities. The AI16Z token represents fund ownership and grants governance rights, with the agent's operations directly impacting the token's value.

AI16Z Price History Source: CoinMarketCap

By comparing the trading volume data of these two agents, it can be seen that both peaked in January 2025, with AI16Z reaching a trading volume of $501 million, while AIXBT set a higher record at $682 million. It is worth noting that the price peak of AI16Z occurred slightly earlier than its trading volume peak, while the price and trading volume peaks of AIXBT were essentially synchronized, showing a tighter correlation over time.

AI16Z and AIXBT Price and Trading Volume Comparison Source: CoinMarketCap

AI16Z and AIXBT Price Performance

AIXBT has outperformed AI16Z in terms of price performance. During the peak period in November 2024, its token price surged nearly 4,000 times from the initial issuance price, while AI16Z only reached an increase of about 111 times during the same period. Even after recent declines and in the context of a downward market trend, the latest price records as of the end of March 2025 show that AIXBT still maintains a 478 times increase from its initial price, while AI16Z remains at a 6.8 times level.

DEX/CEX Bots

These platforms are web-based and operate independently of Telegram. Users can either connect their wallets directly to trade on DEX or link to CEX via API interfaces or simple login methods. These functions are part of the integrated exchange solutions provided by the platforms.

These web-based platforms offer a wide range of strategy options and broader market access channels. In terms of functional design, they cater to users' needs for CEX liquidity and reliability, as well as the non-custodial and decentralized characteristics of DEX. Some platforms also support one-click switching between DEX and CEX, making it more convenient to capture price differences between centralized and decentralized exchanges (i.e., CEX-DEX arbitrage opportunities).

Common Strategies on These Platforms

The most common strategies on these platforms include grid trading, dollar-cost averaging, and signal bots. Dollar-cost averaging bots invest a fixed amount of money into cryptocurrencies at regular time intervals, regardless of asset price fluctuations. The core idea of this strategy is to spread entry points over time to mitigate the impact of market volatility. This strategy often performs well in markets with clear trends.

Grid trading bots are designed for active trading, profiting from price fluctuations through a structured strategy of buying low and selling high. The bot places a series of limit buy and sell orders at preset intervals above and below a predetermined price range, creating an order "grid." Each completed cycle of buying low and selling high generates profit, making this strategy most effective in sideways markets with significant volatility.

Signal trading bots execute trades based on external signals, which usually come from technical indicators, market analysis, or third-party services. Common signal indicators include the Relative Strength Index (RSI), Exponential Moving Average (EMA), and Bollinger Bands.

Comparison of Different DEX/CEX Strategies

Historical Performance of Three Token Pairs Under Three Trading Strategies

The table below shows the historical performance of the BTC/USDT, ETH/USDT, and SOL/USDT token pairs under three trading strategies. The grid trading bot's parameter selection used the AI-optimized feature built into the 3Commas platform to automatically choose the best parameters. For dollar-cost averaging, it used the most popular classic trading strategy among the platform's users.

For signal bots, Dash2Trade offers strategy presets, with the system automatically selecting the optimal strategy for each token. These strategies have been backtested using the platform's proprietary trading system and have been applied to live market trading, but their validity is limited to the trading cycle within 120 days before January 26, 2025.

Due to the lack of consistently available data across platforms, we used three backtesting periods for each strategy. The table below shows the simple price changes within the corresponding periods, which also represent the returns of the simple benchmark buy-and-hold strategy.

DEX/CEX Bot Strategy Returns

Existing Data Indicates Significant Variability in Trading Bot Performance

The existing data shows that the performance of trading bots can vary significantly, depending on the specific trading bot used, the trading strategy employed, and the market conditions at the time of backtesting.

Bitcoin and Ethereum Prices Data Source: CoinMarketCap

During the 120-day backtesting period from September 26, 2024, to January 26, 2025, Bitcoin, Ethereum, and Solana all showed upward trends, with buy-and-hold returns of 58%, 23%, and 55%, respectively. During this period, the strategy performance of signal bots was essentially on par with the buy-and-hold strategy (slightly underperforming for some tokens), with Bitcoin strategy returns at 58.15%, Ethereum at 16.79%, and Solana at 48.68%.

In the same 120-day period from December 4, 2024, to April 4, 2025 (during which the grid bot strategy was backtested), the market prices of Bitcoin, Ethereum, and Solana all showed downward trends, with buy-and-hold strategy returns of -16%, -53%, and -49%, respectively. This was a stark contrast to the market environment in the previous 120-day backtesting period. In a market with a clear downward trend and significant volatility, the grid bot strategy significantly outperformed the buy-and-hold strategy, generating positive returns for BTC (9.6%), ETH (10.4%), and SOL (21.88%).

Bitcoin and Solana Prices Data Source: CoinMarketCap

During the longest 180-day backtesting period from October 4, 2024, to April 4, 2025, when the DCA bot was backtested, the buy-and-hold strategy returns for Bitcoin, Ethereum, and Solana were 34%, -25%, and -18%, respectively. In stark contrast, the performance of the signal bot strategy for these three tokens diverged significantly from the buy-and-hold strategy.

For Bitcoin, using the DCA bot resulted in a return of 17.75%, underperforming the one-time buy-and-hold strategy. However, for Ethereum (ETH, 58.12%) and Solana (SOL, 80.92%), the DCA returns significantly outperformed a one-time investment. This discrepancy may be due to the higher volatility of ETH and SOL compared to BTC during the statistical period, with the DCA strategy effectively reducing timing risk by batching investments and spreading entry prices.