I guess I'm being a bit too broad and subjective...
How about I start off with historical backtesting and/or data itself.
- Back in the internet bubble days, NatWest (now RBOS) made $100+ million loss, due to the options traders using the wrong data. Because they were using the wrong data, their options pricing model was giving the wrong figures, and ended up losing lotsa money.
- On a personal experience level, I use Forex as part of my portfolio of products. The problem with Forex is they don't have a centralized exchange, this causes each individual liquidity provider with their own set of data.
- Another experience is, around 4-5 years ago, a mainstream real-time data provider was filtering the data they stream to their customers due to bandwidth issues. Along with the data provider, depending on the hardware setup you have, there was a risk where your computer was not catching all of the data.
It's pretty obvious that inaccurate data is a big problem for us, traders. During live trading, you'll be entering trades where you shouldn't be. When you're researching or running tests on historical data, you're going to be getting inaccurate results.
Let's say you have a trading system that is working brilliantly, as it should. There can been times, where you would get outlyer trades just because the brokers are having a hardware problem. Which can then trigger your contingencies to cut your trading system.
Along with the above, you still have the risk of the market always changing and systems always fading. The historical data you use may not be representing the live market condition.
How do you all deal with the operating risks of market data? How you do you deal with the market risks of trading? How do you differentiate between the two?