CRYPTO
Bitcoin's Wild Ride: Making Sense of the Chaos
Fri May 30 2025
Bitcoin has become a hot topic in the world of finance. It is the most valuable cryptocurrency out there. The value of bitcoin has been all over the place in recent years. This makes predicting its future value a real challenge. But why is predicting bitcoin's value so important? Well, because it can help investors make smarter decisions. It can also help reduce the risks that come with investing in something so unpredictable.
One interesting approach to predicting bitcoin's value combines two powerful tools: Long Short-Term Memory (LSTM) and conformal prediction. LSTM is a type of artificial intelligence that's really good at spotting patterns in data. Conformal prediction, on the other hand, is a method that helps check how reliable these predictions are.
Here's how it works. First, the data is cleaned up. Any features that are too strongly or too weakly correlated with the bitcoin price are thrown out. This leaves a more manageable dataset. Next, an LSTM model is built and trained using this cleaned data. The model then generates predictions about future bitcoin prices.
But here's where it gets interesting. These predictions are then fed into a conformal prediction model. This model creates confidence intervals around the predictions. These intervals show how sure the model is about its predictions. The goal is to make the predictions as accurate as possible. To do this, the conformal prediction model uses a special loss function called quantile loss. It also designs something called an Average Coverage Interval (ACI) predictor. This helps improve the accuracy of the results even more.
So, does this method actually work? To find out, experiments were run using data from CoinGecko. This is a publicly available dataset. The results were promising. The combination of LSTM and conformal prediction did seem to improve the reliability of the predictions. This is a big deal because it means investors might have a better tool for navigating bitcoin's wild ride.
But here's a question to think about. While this method seems to work, is it really the best way to predict bitcoin's value? After all, bitcoin is known for its unpredictability. Maybe there's no perfect way to predict its value. Maybe the best we can do is make educated guesses. And maybe that's okay. Because at the end of the day, investing is always a bit of a gamble. It's about weighing the risks and making the best decisions we can.
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questions
If the LSTM model starts predicting Bitcoin prices based on the latest viral TikTok trends, how will the conformal prediction model handle the new 'data'?
What if the LSTM model decides to take a coffee break during a major market crash—will the conformal prediction model notice and sound the alarm?
If Bitcoin's value suddenly drops to zero, will the LSTM-CP model predict negative prices, or will it just laugh and say 'You should have invested in cat memes'?
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