INTRODUCTION
An order matching engine operates on an Order Book (OB) to match buyers(bids) and sellers(asks), resulting in a series of trades. The most common matching algorithm is the Price-Time priority Algorithm. Orders in OB are filled primarily based on price; if multiple orders are present at the same price, then the oldest(first-placed) order will be filled first. This works on the principle of FIFO queue: first in, first out.
SETUP
- Clone the repo
- Activate virtual env:
python -m venv env - Install requirements:
pip install -r requirements.txt - Login using
/admin(Note - Login is mandatory to fetch user id) - Play!
LIBRARIES/FRAMEWORKS USED
Allowed Methods : GET | POST
URL Params : Optional: symbol=[string]
Access Level : AUTHORIZED
Additional:Return a json object of all/particular trade data
Allowed Methods : GET
URL Params : Required: id=[int], code=[int], direction=[string], limit_price=[string], type = [string], quantity=[int]
Access Level : AUTHORIZED
Additional: Return a confirmation if trade is successful, otherwise throw an error. limit_price should be 0 if type is "market" . If type is "limit", set the limit_price accordingly. direction is either "buy" or "sell". quantity is the number of stocks you want to buy if your current order is a limit order
NON-TECHNICAL EXPLANATION
An order is simply an offer (buy/sell) against a security which is not executed yet. An investor places an order which is executed by the matching engine using various algorithms (the best one being Price-Time). The execution of order is based on several (a lot) of factors such as - Market/Limit order, limit price if the order is a limit order, available quantity, an IOC/Day order, etc. Here, I have implemented a simple price time priority algorithm for both Market/Limit orders. The order will be partially filled, if the OB has no more units left to fill your desired amount. If an OB entry is consumed fully, it will be removed from the list. If some part of your order is unfulfilled, it will be recorded in the OB on a price-time basis.
TECHNICAL EXPLANATION
There are 2 endpoints - /v1/order_gateway and /v1/data_gateway.
Example Request-
http://127.0.0.1:8000/v1/order_gateway/?type=market&quantity=15&limit_price=0&code=bhel&id=1&direction=sell
Success Response
Code- 200
Content- This endpoint returns a json object of the trade (if fulfilled). [Note - only one last trade object returned] -
[
{
"id": 28,
"item_id": 1,
"seller_id": 1,
"buyer_id": 1,
"quantity": 15,
"quantity_fulfilled": 15,
"price": "46.76",
"offer_id": 52,
"created_on": "18:06:17",
"updated_at": "18:06:17"
}
]
Error Response
Code - 400
Content - { error : "Trade was not successful! Order added to Order Book." }
http://127.0.0.1:8000/v1/data_gateway/?symbol=bhel
Success Response -
Code- 200
Content- This endpoint returns a json object of the stock data(Truncated due to excess size) -
{
"data":
{
"symbol": "BHEL",
"totalSellQuantity": 7332.0,
"adhocMargin": 16.42,
"companyName": "Bharat Heavy Electricals Limited",
"marketType": "N",
"dayHigh": 47.15,
"basePrice": 46.55,
"sellQuantity5": null,
"sellQuantity4": null,
"sellQuantity3": null,
"sellQuantity2": null,
"dayLow": 45.0,
"sellQuantity1": 7332.0,
"pChange": "-1.07",
"buyPrice2": null,
"buyPrice1": null,
"previousClose": 46.55,
"buyPrice4": null,
"buyPrice3": null,
"buyPrice5": null,
"sellPrice1": 46.05,
"sellPrice2": null,
"sellPrice3": null,
"sellPrice4": null,
"sellPrice5": null,
"change": "-0.50",
"ndStartDate": null,
"buyQuantity4": null,
"buyQuantity3": null,
"buyQuantity2": null,
"buyQuantity1": null,
"buyQuantity5": null,
"closePrice": 46.05,
"open": 46.5,
"lastPrice": 46.05,
"timestamp": "18:41:40"
}
}Error Response
Code - 400
Content - { error : "No stock of this code found" }
The OB uses python sortedcontainers' sortedlist. Sortedlist is of the form: [ [quantity1, price1], [quantity2, price2], .... ]. Asks and bids are stored in this list. The benefit of using sortedcontainers is that the accessing of element becomes extremely time efficient. Adding/removal also performs well on sortedcontainers as compared to B-Tree (Reference - Link). Some time complexities are given below:
add(value) - Runtime complexity*: O(log(n)) – approximate.
bisect_right(value) - Runtime complexity*: O(log(n)) – approximate.
The full functioning of the app (excluding UI):
The flow of order processing is shown below in the flow-diagram:
Due to time constraint, many things are left in this app :(
-
Proper Integration Testing
-
Adding OB to db and updating it realtime. (Currently OB is manually set in views)
-
Make login and signup
-
Improve UI and add all stocks display