Ethereum: “Precision is above the maximum defined for this asset” – Binance
As cryptocurrency developers and developers continue to deal with the complexities of the construction of robust commercial systems, a frequently forgotten aspect stands out as particularly challenging: accuracy.
In the native cryptocurrency of Blockchain Ethereum, ether (ETH), the concept of accuracy becomes increasingly relevant when it comes to determining input and output points for negotiations. In this article, we will deepen the details of how to configure a price -sensitive negotiation strategy using code, specifically regarding binance as our reference platform.
Understanding the precision in negotiation
Precision refers to the degree to which the parameters of a negotiation are finely adjusted to minimize sliding and maximize profits. This is particularly crucial in performing negotiations through various exchanges, such as Binance, due to its high liquidity and rapid execution speed.
However, defining perfect accuracy can be scary, especially for traders without extensive experience in algorithmic negotiation or development of intelligent contracts. The goal here is to achieve an ideal level of precision that balances risk management with market volatility.
Configuring a price sensitive negotiation strategy
To implement price -sensitive strategies on binance, you will need to enjoy the platform API and use libraries designed for this purpose. Here is a step -by -step guide to configure a simple stop order system using Python:
Step 1: Install the necessary libraries
First, make sure you have the required libraries installed. You can install them via pip:
`Bash
PIP Install Python-Ctypes
Pip Install Pycrypto
`
In addition, you will need to install Binance-Meth-Trader, which provides a Python enclosure to interact with the Binance API.
Step 2: Configure API credentials and binance connection
Create a new file called config.py to store your API credentials:
`Python
config.py
Binance_api_key = ‘your_api_key’
Binance_api_secret = ‘your_api_secret’
`
Then initialize the necessary libraries in your main script:
`Python
import requests
Import binance
Api_key = binance_api_key
Api_secret = binance_api_secret
Beginning the binance connection
Customer = binance.client (api_key = api_key, api_secret = api_secret)
`
Step 3: Implement Price Sensitive Negotiation Logic
Create a function that will deal with the entry and exit points of trade based on price sensitivity:
`Python
DEF set_precision_order (par, stop_loss_percentage):
Calculate the desired stop loss position
stop_loss = pair [‘price’] (1 – stop_loss_percentage / 100)
Configure the order parameters
Order = client.createorder (
symbol = pair [‘symbol’],
Type = ‘Stop’,
Side = ‘Sell’,
value = 0.01,
timeinforce = ‘gtc’,
good cancellation
STOPPRICE = STOP_LOSS,
LIMITPRICE = None,
)
return order
Usage Example:
Par = {
‘symbol’: ‘eth/usdt’,
eth/usd
‘Price’: 3500.00,
Current ETH price in exchange
}
`
In this example, we define a `set_precision_order ‘function that calculates the desired stop loss position based on a specified percentage (for example, 10%). Then we use to set up a order with the Binance API.
Step 4: Monitor and adjust the accuracy
By adjusting your strategy, adjusting parameters such as stops of stop losses or commercial sizes, monitor your bot performance using metrics such as:
- Commercial execution time
- Order filling rates
- Profit/loss calculations
Make adjustments to your code and test them in a risk free environment before integrating them with your live trading configuration.
