Quote from sbokov:
In regular backtesting there is an assumption that if open > close, then price first went Open -> High -> Low -> Close. When open < close, then price went Open -> Low -> High -> Close. But this is relevant to analysis that is not required to be that accurate.
Quote from intradaybill:
No, this is a bad assumption. Never use it.
Quote from sbokov:
Only the physical memory on your computer and the amount of tick data that you can obtain are limiting factors.
Quote from intradaybill:
Again no. The real issue here is cost of tick data. If I want to test an algorithm in all stocks in NASDAQ 100 I must spend a fortune in data.
Anyway, the issue with the TS2000i software AFAIK was that it did not execute stop-losses on entry bars. Also, it did not generate a valid entry at the open of a bar if a profitable trade was closed during the previous bar. Strange, but whoever wrote the backtesting algorithm had little relation to trading.
Two points.
Point 1 regarding âitâs a bad assumptionâ. Assumptions cannot be good or bad, as they are methods for estimating certain events with varying accuracy, and may be acceptable to some but not to others. You should
definitely be aware of what they are when using them, so you know the limitations of a particular method you are using.
Letâs say you are designing backtesting, and all the data feed gives you are OHLC values. How would you approximate the movements when there is no other data? Please suggest.
A possible answer is: âI wouldnât estimate at all since itâs too inaccurate â need to get more data to make it more accurateâ. Well, two things. First, sometimes there is just no other data, or the assumption may be suitable to some people â that doesnât make it bad. For example, some people use free daily data from FreeQuotes for longer-term analysis, which only gives OHLC? Our approximation in movements is better than no approximation at all.
Second, the option to use more data to make price movements more accurate. Itâs available as well with the Bar Magnifier, you can load historical tick and minute data, and use that to make backtesting very accurate.
Point 2 regarding âcost of tick dataâ. It all depends, how much data you need, what services you know about, and reliability of the tick data that you get. IQFeed, for example, provides 4 months of tick data with a standard subscription for stocks, futures, etc. That may be more than enough for some traders, but may be not enough for others. Our Forex feed provides 10 years of tick data for major Forex pairs.
As with any service there is a cost associated with it. Minute data granularity is sufficient for most traders under most conditions when they need a lot of history â itâs a compromise in terms of accuracy and price.
You mention that the assumption is bad, so donât use it, so we suggest you use tick data for maximum precision. But you say tick data is too expensive, so we are back to having to make assumptions. So, what do you propose?