Why Faster Code Does Not Fix Slow Triangular Arbitrage Data

# Would C++'s speed over Python make it a more applicable language for scalping arbitrage opportunities?


# Would C++'s speed over Python make it a more applicable language for scalping arbitrage opportunities?












I am using the Bittrex exchange API to ping markets to poll whether there are triangular arbitrage opportunities available for USD/BTC/LTC/USD. Note that I am not trading but rather synthesising them by using the API to collect bid and ask data for each of the 3 markets. My test polls also account for fees too. My current code base that uses the API is as follows

```
import requests as rq 
import json 
from CONSTANTS import API_PUBLIC, API_SECRET
import time
import hmac 
import hashlib 

def arbitrage():

    nonce = time.time()

    #Defines the API call that gets the price data
    usd_btc_market = 'https://api.bittrex.com/api/v1.1/public/getticker?market=USD-BTC&apikey={0}&nonce={1}'.format(API_PUBLIC, nonce)
    btc_ltc_market = 'https://api.bittrex.com/api/v1.1/public/getticker?market=BTC-LTC&apikey={0}&nonce={1}'.format(API_PUBLIC, nonce)
    usd_ltc_market = 'https://api.bittrex.com/api/v1.1/public/getticker?market=USD-LTC&apikey={0}&nonce={1}'.format(API_PUBLIC, nonce)

    #Ensures connections are secured through hashing
    usd_btc_signature = hmac.new(API_SECRET.encode(), usd_btc_market.encode(), hashlib.sha512).hexdigest()
    btc_ltc_signature = hmac.new(API_SECRET.encode(), btc_ltc_market.encode(), hashlib.sha512).hexdigest()
    usd_ltc_signature = hmac.new(API_SECRET.encode(), usd_ltc_market.encode(), hashlib.sha512).hexdigest()

    #Conducts the hypothetical trades using the API bid/ask prices from each market. 
    #Assumes a starting capital value of $1
    btc_balance = (1 / json.loads(rq.get(usd_btc_market, headers = {'apisign': usd_btc_signature}).content.decode('utf-8'))['result']['Ask']) * 0.998
    ltc_balance = (btc_balance / json.loads(rq.get(btc_ltc_market, headers = {'apisign': btc_ltc_signature}).content.decode('utf-8'))['result']['Ask']) * 0.998
    usd_balance = (ltc_balance * json.loads(rq.get(usd_ltc_market, headers = {'apisign': usd_ltc_signature}).content.decode('utf-8'))['result']['Bid'])* 0.998

    print(usd_balance) 

while True:
    arbitrage()
    time.sleep(3) #Limited to 60 API calls per minute, ensures not too many calls are made
```

The hypothetical trade results appear nearly profitable. Note that if we started with $1, then the final balance at the end of the arbitrage loop are as follows (code ran every 3 seconds):

```
#Time span of over a 5 minute period
#Each arbitrage loop takes on average 0.48 seconds to run
0.9915490241394859
0.9915511459969782
0.9915511459969782
...
0.9901270999326443
0.9901250816417339
0.9901269101525229
```

I am using Python to run this bot, however I am wondering if the 'so close yet so far' conundrum could be rectified by switching to a faster language such as c++? According to this post, c++ is atleast 10 times faster than python. My thinking is, could this language, with its faster runtime, overcome the minutely small time increments between each API market call? Could this be the reason why such opportunities aren't being found, that Python is simply to slow to take advantage of fleeting arbitrage opportunities? Or, is it just the case that the Cryptocurrency market is more efficient than I thought and arbitrage opportunities don't persist. Looking forward to hearing back what you think.

## Answer by chrisaycock (score 1, accepted)

https://quant.stackexchange.com/a/54522

To expand on what others have said, C++ is only faster on your machine; it's not going to help your counterparty.

Polling over HTTP is the slowest imaginable way to get data, but if that's all Bittrex provides, then perhaps an alternative venue is needed. You are literally waiting three seconds to sample the data; by that point, the market has likely moved to a more efficient price.

Ideally you'd have an open socket with a callback mechanism. The venue should alert you in realtime whenever a new quote appears. Then, at least, the performance of your machine becomes a factor because you'll have to consume the data fast enough to keep up.

Beyond that, there is another issue: the speed of light. I assume you are not colocated with the venue. And in fact, if you're running over the Internet, then your latency is completely at the whim of your connection. If it takes you 40 ms to get the data and your competitors only 20 ms, then no amount of code will make-up for that. It is extremely difficult to comparatively measure this, and almost impossible to control.

## Answer by C8H10N4O2 (score 3)

https://quant.stackexchange.com/a/53996

It’s likely the gets and decoding are where the time is spent. If you want to speed this up, run the three gets in parallel instead of in serial, then make that calculation.

C or C++ can be faster, but here it’s more about the code than the language.