grid
Python strategy by CYZWX.
PythonGrid
The original spec has no written description. Read the source below.
Source Python
last_tick = []
line = []
grid_buy_list = []
def net(now_price):
global line
print(now_price)
line = [now_price*(1+0.003*i) for i in range(-1000,1000)]
Log(line)
def ontick():
global last_tick
global line
global grid_buy_list
account = exchange.GetAccount()
ticker = exchange.GetTicker()
last_tick.append(ticker['Last'])
if len(last_tick) == 1:return
elif len(last_tick) == 100:del last_tick[0]
for i in range(len(line)):
if last_tick[-1] > line[i] and last_tick[-2] < line[i] and len(grid_buy_list)!= 0 and i > min(grid_buy_list) and account['Stocks'] >= 0.001:
exchange.Sell(last_tick[-1],0.01)
del grid_buy_list[grid_buy_list.index(min(grid_buy_list))]
Log(exchange.GetAccount())
elif last_tick[-1] < line[i] and last_tick[-2] > line[i] and i not in grid_buy_list:
exchange.Buy(last_tick[-1],0.01)
grid_buy_list.append(i)
Log(exchange.GetAccount())
def main():
net(exchange.GetTicker()['Last'])
Log(exchange.GetAccount())
while(True):
ontick()
Sleep(1000)
Published by CYZWX on the FMZ strategy square · last modified 2021-06-17. Collected in the Quant Trading Vault. Unvalidated research: re-test with your own data and costs before trusting it.
Build this with AgenKit
A spec is not a trading system. Paste this into your coding agent and AgenKit runs a specialist team — architecture, test-first build, risk gates, review — with paper trading on by default.
/agenkit build a grid bot with inventory caps and order deduplication from strategies/grid.md- npx agenkit install engineering-kit in your project
- Paste the command into your agent and approve each phase
- Get tests, backtest, risk controls and a paper-trading switch
Understand it first
Before you run this, read the lesson behind the idea and how to backtest it honestly. Specs like this one are the survivors of an unknown number of trials; deflate their results accordingly.