Ethereum: “Precision is over the maximum defined for this asset” – Binance

As cryptocurrency traders and developers continue to grapple with the complexities of building robust trading systems, one often-overlooked aspect stands out as particularly challenging: precision.

In the Ethereum blockchain’s native cryptocurrency, Ether (ETH), the concept of precision becomes increasingly relevant when it comes to determining entry and exit points for trades. In this article, we’ll delve into the details on how to set up a price-sensitive trading strategy using code, specifically with regards to Binance as our reference platform.

Understanding Precision in Trading

Precision refers to the degree to which a trade’s parameters are finely tuned to minimize slippage and maximize profits. This is particularly crucial when executing trades through various exchanges, such as Binance, due to their high liquidity and fast execution speeds.

However, setting the perfect precision can be daunting, especially for traders without extensive experience in algorithmic trading or smart contract development. The goal here is to achieve an optimal level of precision that balances risk management with market volatility.

Setting up a Price-Sensitive Trading Strategy

To implement price-sensitive strategies on Binance, you’ll need to leverage the platform’s API and utilize libraries designed for this purpose. Here’s a step-by-step guide to setting up a simple stop-loss order system using Python:

Step 1: Install Required Libraries

First, ensure that you have the necessary libraries installed. You can install them via pip:

pip install python-ctypes

pip install pycrypto

Additionally, you’ll need to install binance-eth-trader, which provides a Python wrapper for interacting with Binance’s API.

Step 2: Set up API Credentials and Binance Connection

Create a new file called config.py to store your API credentials:

config.py

Binance_API_KEY = 'YOUR_API_KEY'

Binance_API_SECRET = 'YOUR_API_SECRET'

Then, initialize the necessary libraries in your main script:

import requests

import binance


API_KEY = Binance_API_KEY

API_SECRET = Binance_API_SECRET



Initialize Binance connection

client = binance.Client(api_key=API_KEY, api_secret=API_SECRET)

Step 3: Implement Price-Sensitive Trading Logic

Create a function that will handle trade entry and exit points based on price sensitivity:

def set_precision_order(pair, stop_loss_percentage):

    
Calculate the desired stop loss position

    stop_loss = pair['price'] * (1 - stop_loss_percentage / 100)


    
Set up the order parameters

    order = client.createOrder(

        symbol=pair['symbol'],

        type='stop',

        side='sell',

        amount=0.01,

        timeInForce='GTC',  
Good Till Cancel

        stopPrice=stop_loss,

        limitPrice=None,

    )


    return order



Example usage:

pair = {

    'symbol': 'ETH/USDT',  
ETH/USD

    'price': 3500.00,   
Current price of ETH on the exchange

}

In this example, we’ve defined a function set_precision_order that calculates the desired stop loss position based on a specified percentage (e.g., 10%). We then use it to set up an order with Binance’s API.

Step 4: Monitor and Adjust Precision

As you fine-tune your strategy by adjusting parameters like stop loss percentages or trade sizes, monitor the performance of your bot using metrics such as:

• Trade execution time

• Order fill rates

• Profit/loss calculations

Make adjustments to your code and test them in a risk-free environment before integrating them into your live trading setup.