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DSchenk

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Everything posted by DSchenk

  1. Appreciate the discussion. Some good points being made. My last statement for tonight, but strongly disagree with this. It makes all the difference. Measuring in £ doesn't make much sense at all Ross Cameron account size is always the same. He starts each month with about $100k, hence he has the same targets for each month. If he would leave all the profits in his account, his targets would grow each month. Although the % profits would still be the same each month. % counts, not £.
  2. I think I got your point now. You are confusing £ profits with % profits. When you say something like What you mean are probably massive £ profits. Whereas in fact you would only make tiny profits, % wise. Therefore I don't understand why you think, that with a larger account you would go long, whereas with a smaller account you would go short. The goal is not to make £100k in profits with a £10m account, that's only a 1% profit. Far from massive. The goal is to make £100k in profits starting with a £2k account. That's the same £ value, but here we're talking massive profits. Doesn't make sense to me, because if you had £250k in your account, then your stop would cost you £87k. It's the same %. If you don't want to risk £87 of £250, then you also probably don't want to risk £87k out of £250k, right? Which means your strategy doesn't fit you. If you want to risk less, just trade less size. (I mentioned earlier, IG puts a minimum size in place, so we have to have a minimum account size. above that size won't matter anymore)
  3. Makes sense what you say, @nit2wynit, but where's the correlation to the account size? With a bigger account you could've risked £55 and made £40 and with an even bigger account you could've risked £5500 and made £4000. % stay the same, just the pound value changes. But pound value is irrelevant for any strategy. The more you put in, the more you get out, simple as that.
  4. Check this out: https://www.forbes.com/sites/stephenmcbride1/2019/10/21/aurora-cannabis-is-dumping-its-pot-which-may-be-a-sign-its-all-over/#5298dc955775 Seems like the end is nigh
  5. Good points as always @nit2wynit. You understand the game. In all the examples you give you have declared certain variables, like this quote: My answer is, if historic data suggests that it is more profitable to hold through 15 points pullbacks and then ride the next wave, then that is what should be done. If the data suggests, better to take profit after a 20 points run, then get back in on the bottom of the pullback, then this is what should be done. But possibly the optimum lies at only allowing 13 points pullbacks and then stop out or taking profit already at 17 points. Once you have simulated every possible outcome, there are no opinions left, no emotions, just simple, plain data driven trading. Difficulty is to build a trading framework where all possible variables can be simulated (and also having a powerful enough simulator - PRT seems to come quickly at its limits, both in terms of number of possibilities which can be simulated and processing time - simulating 200-400 different possibilities takes a matter of minutes, but possibly this exercise need to be done with millions of possibilities. That's essentially what the Quant Trading Funds do. That's another good quote. This comes down to time in market, which needs to be minimised. Better to take 10 points profit after 15 minutes, than 20 points after 3 hours. Cause you could've made another 10 points 4 times over somewhere else in that time frame. However, I slightly disagree with below statement. Account size only affects the size of your trades. All strategies should equally work across all account sizes, by just scaling the position sizes accordingly. (Obviously there's a minimum as you have minimum position sizes defined by the broker). But it shouldn't really matter if you have £1k, £10k or £100k in your account, this just means you have position sizes of let's say 5, 50 or 500.
  6. Trying to simplify the strategy proves to be a rather complex exercise. Not sure if on the right track here, or lost in the woods, trying to find a tree. It should be as simple as finding out the thresholds where an index becomes overbought, then entry short. Where it becomes oversold, entry long. Take profit and stop loss a function of historic data. Backtesting this is fascinating though . Only small deviations in parameters can lead to a huge difference in the end result. Like changing the entry level by a single point - couple of 100% gain lost. Maybe that's why 95% lose in trading, the margin of error is astonishing. Half a point entered too late or too early, profits halfed. Half a point exited too early or too late, profits gone. Stop loss set half a point too far or too tight, huge losses.
  7. So I was crunching the numbers on this yesterday for FTSE 100, DAX, NASDAQ, NG and CL. Table below shows how it looks. Definitions: TPL (Take Profit Long) TPS (Take Profit Short) X (Points above L0 - Low of previous Day for entry Long) Y (Points below L100 - High of previous Day for entry Short) Considerations: While the results do look promising, I'm having a few concerns, which I want to iron out. 1) I'd rather have all X and Ys in the positive area, so that the entry is always in between L0 and L100. That just sounds more intuitive, but the data obviously needs to tell what's better. DAX is currently set-up that way. 2) The algorithm currently increases the position size as a function of the account size. After reconsideration I think it would make more sense to calculate based on a flat size, so that all trades in the sample size of 100,000 units are weighed equal. With increasing position size, the more recent positions count way more than the positions in the beginning, which may skew the results. Obviously the % gains in the end will be less, but we know when actually trading it, it will be much higher. (Even more so if you take into account you trade multiple of these strategies the same time, this leads to a further multiplication effect of profits) 3) Currently there are no stop-losses applied in the strategy, which doesn't seem right. Looking to find a way to work stop losses in without sacrificing too much profitability 4) I took an actual live trade today on DAX with this strategy. Screenshot below. Entry at break of the red line at 7.55, which was bit of cheating as strategy only starts at 8.00. (Correct entry would've been the candle at 8.15 breaking through the red line again.) Profit target would've been about 18 points below the Pivot, unfortunately we saw a bounce off the pivot. So I'm asking myself would it not have been better to either take profits at the pivot or at my daily goal of 20 points (on the way back up). Need to see if I can work stuff like this into the strategy. Ticker TPL TPS X Y Result over 100,000 5min units % of winning trades Entry from Entry until Flat after Time in Market FTSE 100 34 48 -30 8 1466% 65% 08:00:00 16:00:00 21:55:00 19% DAX 30 55 14 22 1131% 71% 08:00:00 16:00:00 21:55:00 22% NASDAQ 85 99 -9 -37 2065% 59% 10:00:00 21:00:00 21:55:00 10% NG 45 41 -42 6 1864% 59% 13:00:00 20:00:00 21:55:00 11% CL 95 85 37 -15 1147% 59% 15:00:00 18:00:00 21:55:00 10%
  8. On blowing cash through - I'm just reading The Naked Trader's Guide to Spread Betting by Robbie Burns - there are some good stories in there how (not) to blow it all out Will give my 2 cents on here once finished the book - worth a read if you haven't yet
  9. The algorithm is I haven't tried on live yet, but hope to be ready to trial this from tomorrow. will obviously update how it goes
  10. Was able to optimise the strategy a little more for FTSE 100. Managed to work with smaller TP levels, which led to a reduction of time in market. Also % of winning trades went up. Optimised the entry condition a bit more as well, now working with stop orders not market orders. New stats: Gain: 1380% (+73% vs previous run) % of winning trades: 64% (+4% vs previous run) Time in market: 18% (-2% vs previous run) Would've turned out marvellously for today btw. Hit perfectly the high and low candle of this move.
  11. looks like your position sizing is way off in the first example you make way too much profit and in the second example your account blows up with the first trade
  12. you probably need to set your chart to display 100,000 units as well Also the code uses initial capital of 2000, not 10,000 you can change it in this line though
  13. Yeah, only tested on a 5min chart so far. It does about 177 trades in 1 year and a quarter, so less than 1 trade per day on average
  14. Alright. Got you. Code is below. Variables need to be set for FTSE to X = -23 y = 7 TPL = 84 TPS = 70
  15. FTSE 100 today. (I didn't trade it btw, cause all my margin was tied up in Prudential) Black line is the previous high of day (I call that L100, for Lvl 100%). Red line would be the entry level of L100 - 7 points. According to the strategy, take profit level would be 70 points below the entry level, which is too far away for my taste. Time in market needs to be reduced as much as possible. I'm looking to optimise the strategy for a smaller take profit level. Looking at the chart today, something like 40 points would've been ideal for a 20min trade.
  16. Hi @EugeneB, shoot me your questions. This strategy would only work for indices (I believe at this moment - cause stocks move to irregular) and the 4 parameters (TPL, TPS, Entry L, Entry S) need to be assessed for each index individually. I'm going to model this for NASDAQ and DAX next and also gonna look at commodities like NG and CL.
  17. "Eventually, Alan Andrew began selling The Action-Reaction Course, a 60-page course available for $1,500 in the 1960s and 1970s." Holy sh!t. $1,500 for a trading course in the 1960s. And in 2019 courses are sometimes only $977. Equivalent of $1,500 in 1960, would be $13k in 2019.
  18. Nice gap-reversal opportunity today with Prudential after they split off M&G as a separate company. Chart in PRT looks completely skewed, so screenshot from online platform below. Managed to capture 10 points. Although, could've been 30 points looking at it now
  19. Ok, so I took this approach to the next level. Rather than telling the algorithm enter long at 25% and enter short at 75% levels, I decided to let the algorithm decide itself at what levels its best to enter short or long. This simplifies the strategy and boosts its gains dramatically. Top level stats over 100,000 5min candles: Gain: +1,307% % of winning trades: 60% Starting with a £2000 account, after 1 year and 1 quarter that account would have grown to almost £30k (£28k). The equity curve looks also a lot more stable, too. I resolved the issue with the lot size, this is now a formula. Unfortunately we still have 3 negative months, but overall the max runup is a lot higher than the max drawdown. Overall time in market is only 20%, so there should be the opportunity to run multiple of this strategy on different assets simultaneously to further boost the return. If let's say 3 of these programs could run simultaneously and deliver similar results you could grow £2000 to £100k within about 18 months. Still not as good as the results of the few world-class top traders like Ross Cameron from Warrior Trading, etc but a start nonetheless. The variables which the program optimised are the following: Take Profit for Long Positions: 84 points Take Profit for Short Positions: 70 Points Entry LvL for Long Positions: 23 Points below the low of previous day Entry LvL for Short Positions: 7 Points below the high of previous day Interestingly, it turned out the strategy works best without a set stop-loss, but just to close out any open positions at 21.00 o'clock at night, if not already closed by the take profit rule. I'm gonna simulate this on NASDAQ next. Obviously will need to find out the 4 variables again, as these will be subject to the Index where this is traded. What do you guys think? Worth a shot this strategy?
  20. Warren Buffett says he would guarantee 50% return per annum if he managed a $1m portfolio. With $100b that kind of returns are simply not possible As the kind of Anton Kreil dudes portfolio size is surely not larger than $1m, $10m at the max, returns of 25% surely are possible. The bigger problem is, if you only have $500-$2000 to start with, how to grow that to $1m. That's they ultimate key question. Cause there your annual returns need to be somewhere in the thousands, if not tens of thousands. Think Ross Cameron started with $570 and grew that to $300k or so in the first year of his trading challenge. That's 525,000 % right there. Key is to get the initial $500 as quick as possible to like $100k and then reduce risk from there and aim for slower growth.
  21. Ah, sorry, I'm too German. We don't understand humour, certainly not English one
  22. Ok, I've got some initial results from backtesting this strategy on FTSE 100. I was backtesting over 100,000 5min untits, that's the maximum PRT can do. It's a timeframe of approx. 1 year and a quarter. High Level Results are: Gain: 130% Winning trades: 60% So, promising results at first glance, but obviously way below expectations. In order for this to be a successful strategy, we would need a gain of something more in the area of 1200% over that timeframe. Not saying this strategy can't achieve this though, if we find a way to tweak it accordingly. Couple of issues to iron out: 1) In the first 3 months it doesn't seem to make any profits at all. Need to find out why this is the case and how the strategy can be tweaked. 2) Then between Nov 18 and Sep 19 the strategy seems to be largely flat as well. Need to investigate this as well 3) Position sizing is currently set as a constant, this needs to be turned into a formula to make the strategy scalable, but couldn't figure out so far how it's best to approach this 4) There are entire months where this strategy produces a loss - need to figure out why and how to avoid Btw, there are two parameters which I did let PRT optimise: 1) Target Profit: Result was that the TP level is optimal if it is set 10 points behind the mid level (50% level). So e.g. when entered long at the 25% level, then the price moves up and crosses the mid level and then makes another 10 points before profits are taken 2) Stop Loss. This is interesting. The optimisation concluded that the TP level is 65 points below the 0% level (or 65 points above the 100% level when shorting). This seems to be a large divergence, which makes me think the strategy itself needs further tweaking. Maybe taking high and low of previous day is not the optimal, but we need to build a range of previous x days and draw the fork over that. Will keep looking at this and update the thread accordingly.
  23. Well the brokers obviously also have an interest to get as many noobs as possible to trade and lose all their money, so I get why they would facilitate such a move if you happen to be an influencer with a couple of thousand followers and promise to bring in hundreds of noobs per month, ready to lose it all. Next question would be: If someone plays this strategy, where do they get the knowledge to create a 30 hour trading course? Or is everything in that course simply also loads of ****? (I never purchased any of those courses, so can't tell)
  24. Be careful with only looking at fundamentals, is what the video wants to tell, I guess Someone else once said (can't quite remember who - think it was a quant fund manager): The market can behave longer irrational than you have equity to be in it. Meaning, all the fundamentals point towards this company is to go bust, you go short, but the share price keeps rising until you receive your margin call and get pulled out of the trade. Afterwards the company goes bust. Consequently this means, timing is more important than getting the overall direction right. And that in return means, technical analysis is more important than fundamentals.
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