Without automated trading, liquidity would dry up, spreads would widen, and markets would become inefficient and expensive for everyone.

3. Since When Has Automated Trading Been a "Thing"?

While often associated with the crypto boom of 2017, algorithmic trading has been the standard in traditional finance (TradFi) for decades.

• 1976 (The Birth of Efficiency): The NYSE introduced the Designated Order Turnaround (DOT) system. This early automation allowed small orders to be routed electronically to the specialist post, bypassing the manual floor brokerage process.
• 1980s (Program Trading): Institutional traders began using computers to trade entire baskets of stocks (like the S&P 500) simultaneously. This allowed them to exploit arbitrage opportunities between futures and spot markets instantaneously.
• 2000s (The HFT Era): As infrastructure improved, High-Frequency Trading (HFT) emerged. Firms invested in microwave towers and fiber optics to execute trades in microseconds, cementing automation as the dominant force in global equities.

Today, it is estimated that over 70% of all US stock market volume is driven by algorithmic trading. Crypto is simply the latest asset class to adopt this mature technology.

4. The Current Landscape: Native Bots, SaaS, and the "Edge"

As the technology moved from Wall Street to the crypto markets, the ecosystem fragmented into several distinct categories. Understanding the difference between these tools is vital for any trader.

1. Exchange-Native Bots (Binance, OKX, Pionex) Major exchanges now offer built-in trading bots, such as Grid Trading or DCA.

• The Utility: These are excellent entry points because they are free and integrated directly into the exchange interface.
• The Limitation: You are "locked" into a single exchange. These bots generally cannot perform arbitrage (buying on Exchange A and selling on Exchange B) because they lack visibility outside their own platform.

2. SaaS & Management Software (3Commas, Cryptohopper) These are third-party platforms that connect to multiple exchanges via API.

• The Utility: They provide a unified dashboard to manage positions across Binance, Coinbase, and Kraken simultaneously.
• The Limitation: They are primarily execution tools. They provide the car, but you must provide the map (the strategy).

3. Open Source & Local Execution (Hummingbot) Advanced quantitative traders often prefer running open-source software like Hummingbot locally or on their own servers.

• The Utility: This offers the highest security for Intellectual Property (IP). The "Edge" (the strategy logic) runs on your own machine, meaning no one—not even the software provider—can see your trade logic.
• The Limitation: High technical barrier. It requires coding knowledge, server management, and continuous maintenance.

4. The Buddytrading Solution Buddytrading was built to bridge the gap between these worlds. We recognized that while platforms like Hummingbot allow professionals to secure their edge, there was no easy way for them to monetize that skill without revealing their code.

Buddytrading acts as a social trading marketplace. We allow advanced traders to host their strategies securely, while allowing retail users to copy the execution of those trades. This protects the quant's IP while giving the user access to institutional-grade logic.

For more details on the tools available to traders, read our deep dives on:

• The Pros and Cons of Exchange-Native Bots
• SaaS vs. Self-Hosted: Choosing Your Bot Infrastructure
• Optimizing Latency: A Guide to Bot VPS Providers

5. Why is that $50 Telegram Bot a Scam?

If automated trading is a legitimate industry, why are there so many scams? The issue lies in the promise of guaranteed returns versus market reality. You will often encounter two types of fraudulent offers in Telegram groups or social media ads:

Scenario A: The "Black Box" Deposit

• The Pitch: "Deposit money into our bot, and it will trade for you, generating 100% profit daily."
• The Reality: This is mathematically impossible. If a strategy compounded at 100% daily, it would absorb all global liquidity within weeks. These are almost exclusively Ponzi schemes where early payouts are funded by new deposits, not trading profits.

Scenario B: The "Code for Sale"

• The Pitch: "Buy this software script for $50. Run it on your computer and it will print money."
• The Reality: This fails due to the economic principle of Alpha Decay. In trading, a profitable strategy (Alpha) only works as long as it is unique. If thousands of people buy the same code and run the same strategy, the market inefficiency disappears immediately.
  • The Logic Test: If a developer truly had a code that guaranteed profit, they would not sell it for a fixed fee. They would run it themselves to compound their own capital.

Ending words Real automated trading is about probability, risk management, and speed—not guaranteed wins. At Buddytrading, we believe in transparent performance history rather than impossible promises. By aligning the incentives of strategy creators and followers, we aim to build a sustainable ecosystem for algorithmic execution.

Sources

1. History of Automation: The Rise of Computerized High Frequency Trading (Duke Law Scholarship Repository).
2. Market Structure: Market Makers vs Market Takers (CME Group Education).
3. Strategy Decay: Alpha Decay: What does it look like? (Maven Securities).