By RoyQuant – Statistician & Crypto Assets Analyst.


In a market like cryptocurrencies, where the price of an asset can change drastically in minutes, intuition is not enough. We need tools. And that's where applied statistics comes in.

As a statistician specialized in the behavior of digital assets, I want to show you how you can use stochastic models to make more informed decisions when trading Bitcoin (BTC), Binance Coin (BNB), or other cryptos.

🔍 What are stochastic processes and why are they useful?

A stochastic process is a mathematical model that describes how something changes over time under a certain degree of randomness. In crypto, we use it to model price behavior.

The most well-known in finance is the Geometric Brownian Motion (GBM), which simulates how prices move over time:

dS = μSdt + σSdz

  • S: asset price

  • μ: expected average return

  • σ: volatility

  • dz: random noise (market randomness)

This model allows simulating thousands of future scenarios based on the current price, to estimate possible ranges of movement and associated probabilities.

📈 Example with $BTC : What could happen this week?

Using data from the last 30 days:

  • Current BTC price: $105,934

  • Average daily return (μ): 2.5%

  • Daily volatility (σ): 4.3%

Simulating 10,000 trajectories:

Percentile Estimated price (30 days)

25% $101,200

50% $107,800

75% $115,600

📌 This is not an exact prediction. It is measuring possibilities based on real data, to help you plan your entry or exit more objectively.

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🔁 And what about $BNB ?

With $BNB , the analysis is similar but with lower volatility. Assume:

• Current price: $725

• μ ≈ 1.8%

• σ ≈ 3.1%

Estimated range this week:

• Between $700 and $770, with a 70% confidence

BNB responds to internal factors of the Binance ecosystem (staking, fees, volume), so its movements tend to be more predictable than BTC in the short term.

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🧠 How to apply this in your real trading?

1. Study the probable price range before trading

2. Define entry/exit zones within those ranges

3. Do not confuse probability with certainty: this is for managing risks, not guessing the market

4. Complement with technical and fundamental analysis.

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📌 Final reflection

Markets are not completely rational, but they are not absolute chaos either.

Between randomness and strategy, statistics helps you see more clearly.

You don't need to be a mathematician to use these models, just have judgment, a desire to learn… and an active account on #Binance 😉

🔗 Follow me for more technical-humanist analysis of the crypto market.

Applied statistics + real market vision = smarter decisions.

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