The "Hello World" sample algorithm on Quantopian gets a 4000% return if it operates on AAPL for a year. It makes trades each minute using a "3 day volume-weighted-average-price." I find it hard to believe this algorithm would perform so well in the real world.
How much of an impact would factors like latency in a real world environment have on this algorithm?
If you are trading in small lots, not very much. For the example of AAPL which has a daily volume of 20mil shares, at the current price of $450, a $450 million buy or sell order on AAPL will only be 1% of the daily trading volume.
Problem is that the bigger the ticker, the more crowded and optimized your competitors already are. The spread on AAPL options/stock is razor-thin, so using IB to do any kind of arbing/volatility/market-making trades is probably not going to be idea.
The trade-off with smaller ticker is you might have less competitors and even if it's a good opportunity, hedge funds aren't interested because potential profit is less than $1mil but for a retail guy, it's a lot. But the catch is the market is thinner, so in a volatile event, you might not be able to trade out of a very bad situation quickly. So your risk is higher.
Basically anything involving HFT where you are trading for liquidity rebates or sub-penny profits doing market-making or arbitrage, latency is critical; but 1sec tick data is an eternity already, for those operations, you need co-location to the exchanges for quotes and execution, not to mention 1mil+ trading capital for sub-penny profits/share to make sense.
1 second tick data would be more useful in swing trading situations where your profit target is 5-10% in a span of a few days to a week - it matters less if your order gets executed $0.01 less or more. So latency shouldn't be an issue.
> second tick data would be more useful in swing trading situations where your profit target is 5-10% in a span of a few days to a week - it matters less if your order gets executed $0.01 less or more. So latency shouldn't be an issue.
How stiff is the competition in that kind of trading?
The unrealistic aspect of that backtest is the total leverage - the algorithm ends up borrowing something like $700k on an initial balance of $10k.
Why not prevent this borrowing in the backtest? Quantopian's philosophy is to report the results, rather than block you from trying outrageous scenarios.
Backtests are not predictive; they are a tool to investigate the behavior of your algorithm.
How much of an impact would factors like latency in a real world environment have on this algorithm?
https://www.quantopian.com/posts/the-hello-world-algorithm-m...