All statistics can be found using the categories page, but the following list (though not always guaranteed to be 100% up to date) offers some quick descriptions of the statistics performed, and my arbitrary ranking on difficulty to achieve (either in depth of theory required or mechanical/technological ability)
1-10, 1 being the most simple, 10 being the most complex. Rough estimations: 1-3 easy, 4-7 intermediate, 8-9 complex, 10 extremely complex
In chronological order:
1. Some data(1)- Tracks frequency of highs within a 24 hour period. This is not rolling time, and 00:00 represents midnight EST. Also a few statistics grouping these within the framework of Asian, London, and New York Sessions.
2. Wick Statistic(1)- Looks at the average length of the upper and lower wick of the daily candle.
3. Movement statistic(1)- A quick check on the average range for various time periods, now redone with an efficiency statistic to study which time frame offers the best pip/minute ratio.
4. Exploration of SB Pt 1(2)- Looks into blending price bars together, in effect creating metadata and studying that instead. Attempt to visually see if these bars produce any forecasting ability in relation to real price.
5. Candle Prediction (2)- On a rolling basis, is there any predictability to bars, or does it seem more “coin flippy” in nature? Using 1 Hour data
6. Week Min-Max Statistic (2)- Similar to the first statistic, now looking at what day of the week contains the high/low of the week. Do markets top/bottom out consistently on a certain day?
7. Basic session Waves statistic (2)- Coding each session into a net up or down move, and comparing these to the other sessions
8. Times for extremes in session Waves (2)- Similar to a combination of Numbers 1 and 7; Now looking at what time each price extreme occurs within each session
9. Time for Daily Extremes (1)- Statistic Number 1 redone with more data and a different definition of the bounds of a day-updated 12/14/13
10. Basic Movements into extremes (2!)- Basic statistic to see if there is any relation between which extreme is greater and which extreme occurs first (Updated 10-2-2013, redid statistic with accuracy)
11. Basic Retracement and MMLC statistics (3)-Statistic to convert prices into either new highs, lows, both, or some form of retracement as a percentage. (VBA, no actual statistic)
12. Intraday Wave statistics by bar type (1)- Basic count statistics of the above. Frequency of HH, LL, and binned percentages for inside bars.
13. Intraday Wave statistics by time (2)- A look into what is occurring most frequently with each hour of the market
14. First hour close forecasting ability (1)- What does the first hour’s close have to do with the movement for the rest of the day?
15. Wave modeling 1.0 (2)- Condensing waves by getting rid of consecutive movements to better see “pure” HH and LL movement.
16. Wave modeling 1.1 (2!)- A fully condensed version of the previous statistic to only show unique HHs and LLs as they pertain to the daily structure.
17. Basic counts on Individual waves (2)- Basically #s 12 and 13 done with each individual wave type.
18. Wave Continuity check (1)- Checking to see which waves appear before or after other waves
19. Time Length of Waves (2)- Breaks down waves into individual components, and studies how long each portion of the wave takes to complete on it’s own.
20. Time Length of Waves Pt. 2 (2)- Same as above, but studying the major/real/final move of the wave.
21. Pip Ranges (1)- How big is the range of each hour bar?
22. Statistic by request (1): Looking at the continuity of bars and bar colors. A roulette study
23. Statistic by request 2: rejection bars (1): A quick study of what color a bar is after it “rejects” a whole number support/resistance line
24. Wave Modeling 1.3 (2): A simple and incomplete study of the retracement numbers in between waves
25. Wave Modeling 1.4 (2): Additional filter on wave definitions. Powerful and much more condensed results
26. Wave Modeling 1.5 (3!): A more in depth study of wave modeling 1.3. Expansions on frequencies of any type of wave forming
27. Substring Sequencing (2): A starting look into rouletting with multiple variations in an attempt to find an edge
28. Substring squencing pt 2 (2): Recoded to fit the waves. Minor successful, contains some useful not-edges.
29. Wave Modeling 1.6 (Time) (3): What time does the Real Major Move of the day begin? Split between the waves, disregarding A waves.
30. A Study of “Both” (1): How often do “Both” bars appear as a function of time?
31. Starting studies of Weekly (2): Another look at which day of the week the weekly extremes are created
32. Another Glimpse at a weeks Movement (2): Which days of the week are most likely to create the extreme on both ends? Aka, if a weekly extreme is created on Monday, what day is likely to be the other extreme? I don’t think I quite have enough data to rely on this data, though I like it.
33. Ranges and Averages (1): Average range of TFs with standard deviations. Clear conclusion from this one.
34. More weekly averages (1): Tracking what happens at the end of the week based on the close of various days
35. Wave statistics yet again (3): Currently the most accurate code wise (4/11/2014)
36. Thinking Edison (1): Mostly a journal entry, but contains average ranges by hour.
37. Basic Ratios (3): Averages of pip ratios of wave to wave based on wave type. Powerful idea, but currently not executed properly.
38. Wick lengths by day (1): Seeing if wick lengths vary by day of the week.
39. Pip lengths of H1 bars based on D1 ranges (2): If a day has a 50 pip range, what are the typical bar ranges (1hr) that ultimately make up that 50 pips? How is this different than a 80 pip day? In other words, are the extra 30 pips made from 1 abnormally large bar or multiple bars that are only slightly larger than normal?
40. Fill % basic (1): As stated. A first look at Fill %s.
41. Pre/post bar Fill % (2): Studying Typical bars, fill %s, and what follows.
42. Post move bars (2): A follow up on post statistic #41.
43. Projection Levels 1.0 (3): First attempt at turning magnitude into H-L projections. Not aiming to hit the top bottom, but rather very safe projection that offers some good pips
44. More projection Data (2): A follow up on Statistic #43, looking at what’s happening after projection levels are hit.
45. Projection Levels 1.1 (4!): Second attempt with better results. This was ultimately superseded by a third version with slightly better results (trade off) that is frozen for the time being
46. Projection levels 1.1 Extra data (2): Quick follow up to statistic # 45.
47. Direction Pt. 1 (2): The beginning to another go at Fills and OHLC breakdown.
48. Movement imbalance (3): Looking at ratios of 2 H-O vs O-L. Hidden implication that I didn’t consider at the time I made this.
49. Initial movement compared to daily MM (3!): How does the first “move” of the day (in pips) affect the major move.
50. Direction Trajectories (3): Quick pictures of graphed trajectories. Might be worth returning to at some point. (Hurray for number 50!)