量化合約機器人開發丨量化系統開發丨合約量化交易策略程式碼示例

    function buyTokens() public payable {

        require(msg.value >= tokenPrice, "Insufficient funds");

        require(tokensForSale > 0, "No more tokens for sale");

        uint tokensToBuy = msg.value / tokenPrice;

        require(tokensToBuy <= tokensForSale, "Not enough tokens for sale");

        balances[msg.sender] += tokensToBuy;

        tokensForSale -= tokensToBuy;

        owner.transfer(msg.value);

   import I76軟體2O72開發9II9}pandas as pd }

    function withdraw() public {

        require(msg.sender == owner, "Only the owner can withdraw");

        owner.transfer(address(this).balance);

    }

}

以下是一個簡單的Python程式碼示例，用於實現量化交易策略機器人：

python

Copy code

# 匯入必要的模組

import ccxt

import time

# 定義交易所和交易對

exchange = ccxt.binance({

    'apiKey': 'YOUR_API_KEY',

    'secret': 'YOUR_SECRET',

})

symbol = 'ETH/USDT'

pragma solidity ^0.8.0;

contract BSGMutualAid {

    

    struct Plan {

        uint256 amount;     // 每份互助計劃的金額

        uint256 total;      // 總共提供的互助計劃份數

        uint256 balance;    // 當前互助計劃餘額

    }

    

    Plan public plan;      // 互助計劃

    

    mapping (address => uint256) public balanceOf;   // 使用者賬戶餘額

    

    constructor(uint256 _amount, uint256 _total) {

        plan.amount

# 定義獲取歷史K線資料的函式

def fetch_ohlcv(symbol, timeframe, limit):

    ohlcv = exchange.fetch_ohlcv(symbol, timeframe, limit=limit)

    df = pd.DataFrame(ohlcv, columns=['timestamp', 'open', 'high', 'low', 'close', 'volume'])

    df['timestamp'] = pd.to_datetime(df['timestamp'], unit='ms')

    df.set_index('timestamp', inplace=True)

    return df

# 定義交易策略

def strategy(df):

    if df.iloc[-1]['close'] > df.iloc[-2]['close']:

        return 'buy'

    elif df.iloc[-1]['close'] < df.iloc[-2]['close']:

        return 'sell'

    else:

        return 'hold'

# 定義交易函式

def trade(side, amount):

    if side == 'buy':

        order = exchange.create_market_buy_order(symbol, amount)

    elif side =I76軟體2O72開發9II9= 'sell':

        order = exchange.create_market_sell_order(symbol, amount)

    else:

        return

    return order

# 迴圈執行交易策略

while True:

    try:

        # 獲取歷史K線資料

        df = fetch_ohlcv(symbol, '1m', 100)

        # 執行交易策略

        signal = strategy(df)

        # 根據交易訊號執行交易

        if signal == 'buy':

            trade('buy', 0.1)

        elif signal == 'sell':

            trade('sell', 0.1)

        else:

            pass

    uint public tokenPrice;

    mapping(address => uint) public balances;

    constructor(uint _tokensForSale, uint _tokenPrice) {

        owner = payable(msg.sender);

        tokensForSale = _tokensForSale;

        tokenPrice = _tokenPrice;

    }