How about this? from peregrinearb import get_opportunity_for_market
import asyncio
collections_dir = '/Users/wardbradt/cs/peregrine/'
opportunity = asyncio.get_event_loop().run_until_complete(get_opportunity_for_market("BTC/USD", collections_dir, exchanges=["anxpro", "bitbay", "coinfloor", "gemini", "livecoin"]))
print(opportunity)
This code snippet is similar to the previous one, but with an additional argument `exchanges` passed to the `get_opportunity_for_market` function. The `exchanges` argument specifies a list of exchanges to include in the analysis for finding arbitrage opportunities.
In this case, the function is analyzing the order books of five exchanges: ANXPRO, BitBay, Coinfloor, Gemini, and Livecoin. By specifying a subset of exchanges to analyze, the function can potentially find more profitable arbitrage opportunities that are specific to those exchanges.
It's worth noting that the exchanges included in the analysis can affect the results of the arbitrage opportunity search. Different exchanges may have different trading fees, liquidity, and order book depth, which can affect the potential profitability of an arbitrage trade. Additionally, some exchanges may have restrictions or limitations on trading that can affect the ability to execute profitable trades.
And how about this one? import asyncio
from peregrinearb import load_exchange_graph, print_profit_opportunity_for_path, bellman_ford
graph = asyncio.get_event_loop().run_until_complete(load_exchange_graph('binance'))
paths = bellman_ford(graph, depth=True)
for path, starting_amount in paths:
# Note that depth=True and starting_amount are set in this example
print_profit_opportunity_for_path(graph, path, depth=True, starting_amount=starting_amount)
This code snippet is also related to arbitrage trading, but it's using a different approach to find profitable opportunities.
The code is using the `peregrinearb` module to load an exchange graph for the Binance exchange, which represents the trading pairs and exchange rates for different cryptocurrencies on the exchange. The `load_exchange_graph` function is an asynchronous function that loads the exchange graph for a specified exchange.
The `bellman_ford` function is then used to find the most profitable paths through the exchange graph, based on the current exchange rates and trading fees. The `depth` and `starting_amount` arguments are used to specify the maximum depth of the search and the starting amount of the cryptocurrency being traded.
Finally, the `print_profit_opportunity_for_path` function is used to print out the details of each profitable path, including the exchanges involved, the currencies being traded, and the potential profit that could be made.
Overall, this code is using a different approach to find arbitrage opportunities by analyzing the exchange graph and finding the most profitable paths through it. This approach can potentially find more complex and profitable opportunities than the previous code snippets.
So what is the reality of arbitrage trading. Any good examples of success stories?
Arbitrage trading can be a profitable strategy for experienced traders who are able to identify and execute profitable trades. However, it's important to note that arbitrage opportunities can be rare and may require significant capital and expertise to take advantage of.
There have been some successful examples of arbitrage trading in the cryptocurrency market. For example, in 2017, a South Korean cryptocurrency trader named Kim Hyon-jeong reportedly made over $1 million in profit by buying Bitcoin on overseas exchanges where the price was lower and selling it on local exchanges where the price was higher.
Another example is the case of the "Kimchi Premium," which was a phenomenon in 2017 where the price of Bitcoin on South Korean exchanges was significantly higher than the price on other exchanges due to high demand and limited supply. Traders were able to take advantage of this price difference by buying Bitcoin on overseas exchanges and selling it on South Korean exchanges, earning a profit in the process.
However, it's worth noting that arbitrage trading can be risky and requires careful analysis of market conditions and trading fees. Additionally, some exchanges have restrictions or fees that can make it difficult to execute profitable arbitrage trades. As with any trading strategy, it's important to do your own research and understand the risks involved before investing your money.
I remember that now. That’s what Sam Bankman-fried was known for.
Yes, you're right! Sam Bankman-Fried is a well-known cryptocurrency trader and entrepreneur who has been successful in using arbitrage trading strategies. He is the founder of FTX, a cryptocurrency derivatives exchange, and Alameda Research, a quantitative trading firm that uses algorithmic trading strategies to trade cryptocurrencies.
Bankman-Fried has been vocal about his use of arbitrage trading to generate profits for his trading firm. In an interview with Forbes, he explained that his firm uses a variety of strategies, including arbitrage trading, to generate profits in the cryptocurrency market.
Bankman-Fried has also been involved in various philanthropic efforts, including donating millions of dollars to charities focused on global poverty and animal welfare.
