DSchenk

@nit2wynit and myself just playing with small capital right now, because we don't have a winning strategy yet. As soon as I'm having a winning strategy and what I mean by that is trading the strategy in live environment consistently over 3 months with real capital, although small amounts, I'm scaling the equity in my account up drastically.

You've got the wrong view on things again, I'm afraid. All you need is capital to trade. It doesn't need to be your own. Put £20k on a credit card, trade it and make £25k out of it and pay the £20k back within the same month. No credit charges and you just made £5k. Do that 4 times and you have your £20k starting capital If you had a winning strategy, you would find a way to raise that capital quicker than you think. In fact people would start throwing more money at you as you can manage

That's why I always saying don't focus on the £ values - they don't mean anything. If @nit2wynit would've said he earned 11 points or 1% or something, then this would be of much more relevance. Because the £11.18 are just a reflection of how much he puts in, in the first place. But the 11 points instead of £11.18 can also be £111.80 or £1180 or £11,800, depending how big his account size is. Try doing that in a job, where your £ per hour is fixed and not a function of your capital.

With £20k, you could do position sizes on the FTSE of 50. Means £50 per point. If you scoop 5 points of the FTSE every day, you make £250 per day, that's about £5k per month or £60k per year. You're math is correct. I think this is an understatement of what spread betting can do. Don't forget your purchasing power rises during the year as you make profits. From month 2 you can up your position size to 60, meaning you make now £300 per day, that's £6k that month. Month 3 you up size to 75. You make now £375 per day, £7.5k per month. And so on. Your account size reaches £1m in month 19. That largely matches with for example Ross Cameron's performance ($500 to $1m in 24 months, but taking profits out of the account above $100k) Additionally, I think it should be more than doable to scoop more than merely 5 points per day. 10-20 points seems to be a realistic target.

LOL The chance of winning the National Lottery jackpot is 1 in 45,057,474. The chance of winning in spreadbetting is (according to spreadbet providers) 1 in 20 (95% lose). Ok, not everyone makes huge wins. I assume the chance of becoming a spreadbet millionaire is somewhere between 1 in 10,000 to 1 in 100,000. Certainly not in the millions

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 £.

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)

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.

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

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.

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.

Long live the emperor!

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%

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

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

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.

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

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

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

Alright. Got you. Code is below. Variables need to be set for FTSE to X = -23 y = 7 TPL = 84 TPS = 70

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.

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.

"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.

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

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?