Hello everyone! 👋

So, in the whitepaper, I broke down how the Trade Maven algorithm does its magic. It's all about grabbing real-time market data, cooking up signals from that data, filtering the ones that seem odd, and managing any trade risks that come its way. Now, let's take a deep dive into how it all happens 🕵️‍♂️

But first, I'll mention something fun: [trends](https://www.investopedia.com/terms/t/trend.asp) 📊. The market's like a rollercoaster, always going in one of three ways:

- Upwards (when prices keep climbing) 📈
- Downwards (when prices take a nosedive) 📉
- Sideways/Consolidation (when the price keeps bouncing within a specific range) ↔️

So, here's the exciting part: the algorithm's goal is to be your trend-riding buddy 🚀. It aims to spot those moments when the market is playing it cool (moving sideways) and then predict when an **upward** or **downward** trend is about to start and ride it to the finish line 🏁

But hey, nobody's perfect, right? If it makes a rare slip-up, it's got some cool tricks up its sleeve like [stop losses](https://www.investopedia.com/terms/s/stop-lossorder.asp) and [trailing the price](https://www.investopedia.com/terms/t/trailingstop.asp) to turn things around 💫

Now, let's talk results. After backtesting the algorithm with over a decade's data (2013 to 2023) ⚙️, the scorecard is pretty impressive. It could predict upcoming trends with a smashing accuracy of 65.92% 🤖. And here's the cherry on top: it boasts a [Risk to Reward ratio (RRR)](https://www.investopedia.com/terms/r/riskrewardratio.asp) of **1 to 4**.

> **RRR** is like your trade's guardian angel. A ratio of **1:4** means that just one good trade can make up for four not-so-great ones 😄

Why do bad trades happen about 34% of the time? The algorithm isn't perfect, and the market can be as unpredictable as the **Wild West**. But if you're curious about the whole story, I'm ready to spill the details 🚨

1. **Pattern Imperfections**: Trade Maven is like a pattern detective. It looks for clues in the market's behaviour to anticipate trends 🧩. However, unusual events or outlier data points can throw off the algorithm's predictions.
2. **Premature Predictions**: Sometimes, it jumps the gun. Being too early isn't wise because the market might pull back/retrace temporarily before heading the predicted way 🐦
3. **Consolidation Conundrum**: When the market's bouncing up and down (consolidation), it's a puzzle. The algorithm might think it's forming a trend and enter a trade, only for the bouncing to hit stop losses 🤦‍♂
4. **News and Manipulation**: Even with accurate predictions, news (thanks, Elon Musk) or manipulation can cause a rapid change in direction that the algorithm couldn't have foreseen 📰

Now, let's address the significant developments of the day, which unfortunately led to losses on October 16, 2023. The algorithm executed four [SHORT trades](https://www.investopedia.com/terms/s/shortselling.asp) anticipating a downtrend. However, all of these trades were stopped due to the impact of [false information released by Cointelegraph, a well-regarded cryptocurrency publication](https://news.bitcoin.com/bitcoin-surges-on-fake-blackrock-etf-approval-news-misinformation-ripples-through-crypto-markets/) 😔


Despite Cointelegraph issuing an [apology](https://x.com/Cointelegraph/status/1713925876969017792?s=20) for their actions and the SEC launching an investigation into potential insider trading, our incurred losses are regrettably irreversible. Our next step is to learn from this experience, adapt our strategy, and continue to move forward 🚀

But take heart! The algorithm is battle-tested and ready for the challenge. It's primed to handle losses even more substantial than this and make a triumphant comeback 🔥. Based on its backtest results, it anticipates an [average annual drawdown](https://www.investopedia.com/terms/m/maximum-drawdown-mdd.asp) of 25.90%, so we're in diamond hands 💎🦾

> Originally published: 17/10/2023