Mark Holstius Elite    Posts: 744 Joined: 10/11/2012 Location: Sleepy Hollow, IL  User Profile | My original thread on RTM Entry Allocations is here; https://www.omnitrader.com/currentclients/omnivestforum/thread-view.asp?threadid=7843&posts=7 Goals of this tesing; Improve PPT by lowering the avg entry price. Improve CAR by allocating more equity to the trades with a higher PPT. These tests use the existing data for my FTM portfolio trades over 15 years to determine if using Limit Orders would’ve helped. I acknowledge that the data reflects the results of those particular trades, and is therefore a curve fit to the data… but I’ll also include additional results that may add support to the robustness of the proposal. There’s no way at the moment to submit a limit order in OV - but I’ve shared this “proof of concept” data with Nirvana and I’m hopeful that it will be implemented in some form.(?) To keep things simple the process uses two types of entry orders; 1) A MOO order that fills each day using a low allocation % 2) A Limit order with price equal to the previous day’s Close - 2% that uses a higher allocation % The Limit Order is filled on 2 events using historical OHLC data in my spreadsheet; A) Filled at the Open if the Open is <= the Limit. (Entry $ can be < the Limit $) B) When the Open is above the Limit, filled during the day if the Low for that day goes below the limit. (entry $ is then calculated using the weighted allocation of the MOO & Limit prices) If the Limit Order isn’t filled by the end of the entry day, the trade proceeds using only the MOO fill at its low allocation. Results; Blue statistics and Equity; Normal MOO Entry & MOO Exit using 1% Allocation … And When Triggered … Limit Entries (Prev Close - 2%) & MOO Exit using 10% Allocation Red statistics and Equity; Normal MOO Entry & MOO Exit using 4% Allocation **Note the improvement in all statistics when adding Limit Entries & adjusted allocations. I’ve used allocations that keep the Avg % Inv similar for both, and added a measure of efficiency in the last column. The ratio of CAR / Avg % Inv is a measure of ROI not affected by differences in Avg % Inv between portfolios. The data is as accurate as I can make it using Excel. The spreadsheet determines the equity available at the time of each trade, calculates the # of shares for each trade based on the allocation used, and subtracts commissions. Even so, the results are constrained to one set of trades. There’s a very legitimate objection that the results are positive only because those particular trades worked well and are a curve fit. I’ll try to address that problem as follows… Think of these results as a back test using “in sample” data. I ran identical tests with a set of trades that are completely “out of sample” in an attempt to validate the results. I used Nirvana’s excellent ARM4 portfolio at a low allocation to obtain another large set of historical RTM trades. Since ARM4 uses 12 RTMs and only 3 of those overlap with the 9 my FTM portfolio uses, that adds variety to the population of RTMs used. In addition, I cross-referenced all the trades produced by ARM4 and deleted the trades that were mirrored in my FTM portfolio. 15,800 trades remained that were unique & different from those in my FTM data - and I used those as an “out of sample” test of the theory. Results using the 15,800 unique / ARM4 “out of sample” trades; Blue statistics and Equity; Normal MOO Entry & MOO Exit using 1% Allocation … And When Triggered … Limit Entries (Prev Close - 2%) & MOO Exit using 10% Allocation Red statistics and Equity; Normal MOO Entry & MOO Exit using 4% Allocation **Also shows improvement in all statistics when adding Limit Entries & adjusted allocations. The results are consistent with those obtained using my FTM trades. I decided to press the limits of Excel and combined the 2 sets of trade data (~3.5 Million cells); Blue statistics and Equity; Normal MOO Entry & MOO Exit using 1% Allocation … And When Triggered … Limit Entries (Prev Close - 2%) & MOO Exit using 10% Allocation Red statistics and Equity; Normal MOO Entry & MOO Exit using 4% Allocation It’s rather obvious that using the same allocation levels with 25,164 trades produces results that are unrealistic as far as Avg % Invested and Equity. To make things more reasonable, I reduced all the allocations by half; Blue statistics and Equity; Normal MOO Entry & MOO Exit using 0.5% Allocation … And When Triggered … Limit Entries (Prev Close - 2%) & MOO Exit using 5% Allocation Red statistics and Equity; Normal MOO Entry & MOO Exit using 2% Allocation Again, the results are consistent with those obtained using my FTM trades. Below is a table showing the number and % of Limit trades taken at the Open and during the day; Every trade is taken MOO at a low 1% allocation. About 25% of those trades are then supplemented with Limit orders using a higher 10 % allocation. The % of trades filled as Limit Orders is comparable using either my “in sample” or “out of sample” set of trades. That uniformity is an indication that the results might be replicated using different portfolios. The consistent results with the “out of sample” trades also appear to validate that using this rather simple Day Limit Entry may be robust, and that adding a Limit Order capability to OV could potentially increase the profitability of an already great product. If implemented in OV with the ability to simulate historic results, we could probably find better settings for both the Limits and the Allocations. I suspect that using limits based on ATR may enhance it even more, but I don’t have that capability with Excel. Please share your experiences / thoughts on various types of Orders and how we might improve this “proof of concept” proposal. Thanks. And as always, good luck in your trading… Mark [Edited by Mark Holstius on 8/13/2017 7:41 PM]  Attached file : 01 FTM Results.png (68KB - 2459 downloads) Attached file : 02 ARM4 Results.png (70KB - 1173 downloads) Attached file : 03 ARM4 And FTM Results.png (91KB - 1176 downloads) Attached file : 04 ARM4 And FTM Results.png (86KB - 1144 downloads) Attached file : 05 Trade Totals.png (22KB - 1112 downloads) |
