I really find it hard to believe that a an operation like OP is proposing would be run at IB like MrMuppet said. Just can't get over that really there are so many things wrong with this they are innumerable. Even if you had perfect code it would not run as expected because of snap shot data. It's ok for an investor but not this project at all.
40% of what? 1st that's way too much you must be crazy....
Here I have just saved you 40k probably in just getting started.
To create a C++ framework for the described project, we will design the structure to include classes and functions that cover the main tasks. This framework will be modular and scalable to handle multiple products, generate theoretical bid/ask values, send various types of orders, and handle hedging operations. Here’s how we can conceptualize this framework using pseudocode:
High-Level Framework Design in C++ Pseudocode
1. Core Components
- Product: Represents a tradeable product (futures, equity).
- Strategy: Represents different market-making strategies (quote, market take, etc.).
- Order: Represents buy/sell orders.
- Hedge: Represents hedging actions.
2. Key Classes and Structures
// Base class for any tradeable product
class Product {
public:
std::string symbol; // Symbol for the product (e.g., AAPL, S&P Futures)
double currentPrice; // Current market price
double theoreticalBid; // Theoretical bid price
double theoreticalAsk; // Theoretical ask price
Product(std::string symbol) : symbol(symbol), currentPrice(0), theoreticalBid(0), theoreticalAsk(0) {}
virtual void updatePrice(double newPrice) {
currentPrice = newPrice;
}
};
// Derived class for Futures products
class FuturesProduct : public Product {
public:
FuturesProduct(std::string symbol) : Product(symbol) {}
};
// Derived class for Equity products
class EquityProduct : public Product {
public:
EquityProduct(std::string symbol) : Product(symbol) {}
};
// Class representing trading strategy
class Strategy {
public:
virtual void calculateTheoreticalValues(Product& productA, Product& productB, double ratio, double offset) = 0;
virtual void executeOrder(Product& product) = 0;
};
// Market making strategy (MM), quote, etc.
class MarketMakingStrategy : public Strategy {
public:
void calculateTheoreticalValues(Product& productA, Product& productB, double ratio, double offset) override {
productA.theoreticalBid = productB.currentPrice * ratio - offset;
productA.theoreticalAsk = productB.currentPrice * ratio + offset;
}
void executeOrder(Product& product) override {
// Implement logic for sending orders
// Could be multiple types: quote, market take, etc.
}
};
// Class for hedging operations
class Hedging {
public:
void generateHedgeOrder(Product& hedgeProduct, double quantity) {
// Generate and execute hedging order based on the given quantity
}
};
// Order class
class Order {
public:
std::string productSymbol;
std::string orderType; // "Buy" or "Sell"
double price;
int quantity;
Order(std::string symbol, std::string type, double price, int qty)
: productSymbol(symbol), orderType(type), price(price), quantity(qty) {}
void execute() {
// Logic to execute order
}
};
// Main Trading Engine to manage multiple products and strategies
class TradingEngine {
public:
std::vector<Product*> products; // List of products to trade
Strategy* strategy; // Current strategy in use
void addProduct(Product* product) {
products.push_back(product);
}
void setStrategy(Strategy* strat) {
strategy = strat;
}
void run() {
for (auto product : products) {
// Example: Assuming the first product is 'product A' and the second is 'product B'
// In reality, you would have more robust logic to match products
if (products.size() > 1) {
strategy->calculateTheoreticalValues(*products[0], *products[1], 1.5, 0.5);
strategy->executeOrder(*products[0]);
}
}
}
};
Explanation of the Framework
- Product Class Hierarchy:
- The Product base class represents any tradeable item. Derived classes like FuturesProduct and EquityProduct can have specialized behavior.
- Each product has a symbol, current market price, and calculated theoretical bid/ask prices.
- Strategy Class:
- The Strategy base class defines a generic interface for different trading strategies. The MarketMakingStrategy class implements specific behavior for market-making.
- The calculateTheoreticalValues method sets the theoretical bid/ask prices based on a given ratio and offset.
- The executeOrder method simulates sending orders based on calculated values.
- Hedging Class:
- The Hedging class is responsible for generating hedge orders. This is essential in market-making to manage risk.
- Order Class:
- Represents a trade order with details such as product symbol, order type, price, and quantity. The execute method would handle the execution of orders.
- Trading Engine:
- The TradingEngine class manages the overall operation, holding a list of products and applying a selected strategy.
- The run method iterates over the products, applies the strategy to calculate theoretical prices, and sends orders.
Notes on Scalability and Robustness
- Multithreading/Concurrency: In a real-world implementation, you would need multithreading or asynchronous processing to handle the continuous update of market data and the sending of orders in real-time.
- Error Handling: Proper error handling mechanisms are required for robustness.
- Data Management: Efficient management of real-time data streams, possibly using message queues or databases for persistent storage and retrieval.
- Optimization: Techniques to minimize latency and maximize throughput, essential for handling millions of quotes and orders.
This pseudocode provides a framework that can be expanded upon with additional features, such as connecting to specific exchanges or trading platforms, handling more complex strategies, or implementing risk management protocols.
