Dynamic Allocations on Sell

Dynamic Allocations on Sell is a feature that allows a market-making bot to adjust the amount of capital allocated for selling assets based on various market conditions, such as volatility, liquidity, and price trends. This approach helps the bot optimize its selling strategy by ensuring it can capitalize on favorable market conditions while minimizing risk during unfavorable conditions.

▎How It Works

1. Market Conditions Assessment: The bot continuously monitors market indicators (e.g., price trends, order book depth) to assess current market conditions.

2. Dynamic Allocation Logic: Based on the assessment, the bot determines how much capital to allocate for selling. This can involve:

   • Increasing allocations during high volatility or bullish market conditions.

   • Decreasing allocations during low volatility or bearish conditions.

3. Order Execution: The bot executes sell orders based on the dynamically calculated allocation.

▎Example Code

Below is a sample implementation of the "Dynamic Allocations on Sell" feature using Python. This code builds upon the previous example and focuses on the dynamic allocation logic for selling.

▎Sample Code

// import random
import time

class DynamicAllocationMarketMakingBot:
    def __init__(self, trading_pair, base_allocation, volatility_threshold):
        self.trading_pair = trading_pair
        self.base_allocation = base_allocation  # Base allocation amount
        self.volatility_threshold = volatility_threshold  # Threshold for adjusting allocation
        self.orders = {}  # Store active orders

    def get_market_volatility(self):
        """Simulate fetching market volatility (replace with actual logic)."""
        return random.uniform(0, 1)  # Simulated volatility between 0 and 1

    def calculate_dynamic_buy_allocation(self):
        """Calculate dynamic allocation for buying based on market volatility."""
        volatility = self.get_market_volatility()
        print(f"Current Market Volatility (Buy): {volatility}")

        if volatility > self.volatility_threshold:
            dynamic_allocation = self.base_allocation * (1 + volatility)
        else:
            dynamic_allocation = self.base_allocation * (1 - (self.volatility_threshold - volatility))

        return max(dynamic_allocation, 0)  # Ensure allocation is non-negative

    def calculate_dynamic_sell_allocation(self):
        """Calculate dynamic allocation for selling based on market volatility."""
        volatility = self.get_market_volatility()
        print(f"Current Market Volatility (Sell): {volatility}")

        if volatility > self.volatility_threshold:
            dynamic_allocation = self.base_allocation * (1 + volatility)
        else:
            dynamic_allocation = self.base_allocation * (1 - (self.volatility_threshold - volatility))

        return max(dynamic_allocation, 0)  # Ensure allocation is non-negative

    def place_buy_order(self):
        """Place a buy order with dynamically calculated allocation."""
        try:
            allocation = self.calculate_dynamic_buy_allocation()
            print(f"Placing Buy Order for {self.trading_pair} with Allocation: {allocation}")

            # Here you would add your logic to interact with the exchange API to place an order

            # Store the order (simulated)
            self.orders[self.trading_pair] = {'side': 'buy', 'amount': allocation}

        except Exception as e:
            print(f"Error placing buy order for {self.trading_pair}: {e}")

    def place_sell_order(self):
        """Place a sell order with dynamically calculated allocation."""
        try:
            allocation = self.calculate_dynamic_sell_allocation()
            print(f"Placing Sell Order for {self.trading_pair} with Allocation: {allocation}")

            # Here you would add your logic to interact with the exchange API to place an order

            # Store the order (simulated)
             self.orders[self.trading_pair] = {'side': 'sell', 'amount': allocation}

        except Exception as e:
            print(f"Error placing sell order for {self.trading_pair}: {e}")

    def run(self):
        while True:
            self.place_buy_order()
            self.place_sell_order()
            time.sleep(10)  # Check every 10 seconds

if __name__ == "__main__":
    trading_pair = 'ETH/USDT'
    base_allocation = 1.0  # Base allocation amount (in ETH, for example)
    volatility_threshold = 0.5  # Threshold for adjusting allocation

    bot = DynamicAllocationMarketMakingBot(trading_pair, base_allocation, volatility_threshold)
    bot.run()

▎Explanation of the Code

1. Initialization:

   • Similar to the previous example, the bot initializes with a trading pair, a base allocation amount, and a volatility threshold.

2. Fetching Market Volatility:

   • The get_market_volatility method simulates fetching market volatility.

3. Calculating Dynamic Allocations:

   • The calculate_dynamic_buy_allocation method computes the dynamic allocation for buying.

   • The calculate_dynamic_sell_allocation method computes the dynamic allocation for selling using similar logic.

4. Placing Orders:

   • The place_buy_order method places a buy order with the dynamically calculated allocation.

   • The place_sell_order method places a sell order with the dynamically calculated allocation.

5. Running the Bot:

   • The run method continuously places both buy and sell orders in an infinite loop, checking every 10 seconds.