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I would definitely say you are onto it! Knowing all of this and seeing all of the forces against you in the market are key.
Separating the various aspects of the house edge out like this really helped me be able to know what obstacles I needed to address. Some of these are easier to work around than others obviously.
I will throw out one helpful peace of advise that really made a huge difference for me in cracking this.
When looking at price (1 tick up, 1 tick down, etc.). It is very important to delineate the difference between flipping which side is currently getting served (The Bid Volumes or the Ask Volumes) this creates a tick up or a tick down and as the market is serving both sides I consider this to be largely arbitrary price movement that really doesn't matter. But when there is a level change in the books. I.E The entire Bid / Ask level moves up or down by one tick because a level cleared, this is a key event and very different than the former ticking between the two volumes.
Now keep in mind that you can pick your entry at a point in time so specific that you could enter when the last price = bid price, or the last price = ask price, you can find tune your entry to filter out the previous mentioned noise that I consider arbitrary. There are a number of ways of characterizing the play here, but I could write a whole book on the research I have done in cracking the ways levels are cleared and how volumes, and price and sequencing work. I would almost call this nano-structure because it is a field of study even more granular that most micro-structure studying.
But this field of research is where you can start to take back all of the house edge....
@wldman Thanks for sharing the excel sheet, Dan! I am looking forward to the explanations. So far, I can see HL, Range, Median, Open, and a 10-day average range.
"It does not matter how slowly you go, as long as you do not stop." Confucius
Alright, I've created my first backtest study in excel using daily RTH data on the NQ.
1. Study performed on RTH hours of the NQ. Data is from from Sierrachart, starting in 2012, with volume-based rollover
2. Looked for a Tuesday gap from Monday or Friday (if it was a 3-day weekend). Gap is defined as Tuesday low greater than Monday or Friday close.
3. If there was a tuesday RTH gap, buy Wednesday RTH open and exit Friday RTH close
4. Two control tests were performed. A daily RTH buy @open and sell @close, and a 3-Day buy@open and sell@ close (to simulate buying Wed open, and selling Fri close)
For the calculations, I used LOG[current price/previous price]. The reason I used this calculation is because I read in the Adam Grimes' book that log of returns simulates compounding returns. Additionally, log returns can be manipulated by simple math, and directly compared.
Here are the results:
Control study daily total returns: 18.76% from November 28, 2012 to present; 726 positive days, 5 neutral days, 583 negative days
Control study 3Day total returns: 99.69% from November 28, 2012 to present; 786 positive trades, 4 breakeven trades, 524 losing trades
GAP test returns: 0.04% from November 28, 2012 to present; 32 positive trades, 0 breakeven trades, 28 losing trades
It appears that buying after a Tuesday RTH gap and exiting Friday RTH close does not have a clear edge.
It appears that buying and holding for all 3 day groups does have an edge (not sure how you would do this in real-life other than having 3 separate accounts)
Attached spreadsheet.
Any feedback on calculations, further statistics to generate, or anything else, would be appreciated.
"It does not matter how slowly you go, as long as you do not stop." Confucius
Having a good reliable data source is very very important.
This may work for equities, but with futures it only works if your looking at NON-roll adjusted futures. How can that be the case? Well every time a contract expires/rolls to next expiry, the back adjusted prices all alter, and hence the return and log return all alter as well. Also back-adjusted contracts, can and do go negative if you go far enough back in history.
How does one know if a data source is reliable? I'm using Sierra Chart historical data (which I believe comes from barchart) and Gain top of the book data. Is there a "gold-standard" data set or data feed to compare?
"It does not matter how slowly you go, as long as you do not stop." Confucius
How roll adjusted contracts are calculated. Different systems & vendors do it in different ways. One of the data providers I use actually changed this for one contract at the end of 2016 but never told anybody. I only realized because I couldn't reconcile some roll costs. If your rolling on different days than your data - watch out.
using non-linear calculations on roll adjusted data (eg percent, log, ratios etc)
Deferred Contracts. I find that when using deferred contracts that many data vendors not only provide different results for the same product but also data that is sometimes plain wrong. In the last month I've discovered that two of the data providers I use currently return the wrong prices when you request deferred Eurodollar contracts. Admittedly Eurodollar has a weird contract structure but bad data is bad data.
Finally I've heard people claim that when testing automated strategies that use different data providers yield different results. If the data was the same that shouldn't be possible.