Gains Eroded in the Past Few Weeks?

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Viewing 14 posts - 16 through 29 (of 29 total)
  • #240474

    What does that tell us? In turbulent times or over many years, trend strategies seem to be the safest. Then come mean reversions in terms of risk…
    Scalpers are definitely the most unstable. At least in my humble opinion.

    #240518

    phoentzs out of interest … what Chart Timeframe do your Strategies detect a downtrend, as an example on daily TF over 10k bars … where on attached for US100 do you / your code consider was a downtrend?

    Just the yellow area only or yellow plus all the 5 green areas or even all the other small downturns also?

    Or has US100 been in continuous uptrend on attached as far as your code / Strategy determines?

    #240520

    phoentzs easiest might be to post a screenshot of price curve below positions below equity curve and I imagine it will be obvious what your code considers is a downtrend as there would be very few Long entries during downtrends?

    If you are happy to do above, please show Chart TF, Units covered and axis values.

    #240521

    I’ll make it even easier and answer my own question 🙂 maybe … you posted just such a Chart as I mention above here …

    https://www.prorealcode.com/topic/algo-swap-anyone/#post-231193

    Judging from above on a ‘broad-brush’ basis, I would say your code considers any downturn longer than 1 day-ish as a downtrend and therefore Long entries are few in number during such downturns?

    Out of interest and as a comparison, here is mine from that same Topic

    https://www.prorealcode.com/topic/algo-swap-anyone/#post-231187

    #240522

    @Grahal
    I would do it like this. This is one of my simple systems. I don’t have any indicators and I see each day as a finished thing. That’s why there isn’t really a downtrend, because even in downtrends there are smaller upswings. The system is in the market for a maximum of 24 hours per position. Not the most lucrative, but… robust as hell. 😉
    Is it of any use to you?

    1 user thanked author for this post.
    #240525

    @Grahal
    I understand… here SP500 in M15. Same principle…

    #240531

    Not the most lucrative

    Looks good, average of 3K per year (21K Gain over 7 years) on US 100 at pos size = 1 … that is equivalent to 6k per year at pos size = 2 (to equate to DJI).

    Nice one! … that Algo could be left to your children in your will! 😉

    #240532

    @Grahal
    Unfortunately not quite so good. 😉
    It is 11,500 euros. The example is with 10,000 starting capital.

    1 user thanked author for this post.
    #240536

    May I ask you both wat your accounts % YTD are? I think it is very interesting to hear what other people achieve. Also I wonder, how was your September and October? Both of those were negative months for me.

    #240539

    I’ve had a ‘summer off’ for all comparison reasons as I have been building a house (still loads to do! 🙁  )

    My comments higher up this Topic are relating to Algos on Demo Live running.

    I still keep my hand in on manual trading if I am in the right mood … like today, but I am trading with minimum pos size, well 3 to 5 times over as I am, mmm whats the term … 1, 2, 3, 4 , 5 in then 1,2,3,4, 5 out.

    I’m sort of ‘kidding myself’ that I am starting over again from scratch / with only a few hundred pounds to start with!  Attached are today’s results so far.

    There is ‘method in my madness‘ … I am trying to cure myself of my one / main weakness when manual trading.

    Also I still have over 150 Algo’s running in Demo Live.

    #241599

    I have been in a drawdown since summer. It have been some tough months. ATH in summer my account was about 75% up YTD, now it is around 40% after a good start of November.

    Hello to the North!

    What is the max drawdown in % of equity behind your results YTD?

    I assume not so many will post here their results as you did, for various reasons. but I will – with my next post – so folks have something to laugh about my fabulous win-rate.

    cheers

    justisan

     

    #241602

    Hi,

    as we are approaching end of this year I will post some data from my „model account“ (trading DAX only): behind there is a portfolio of 11 algos, 6 long and 5 short, which I run with 10k EUR live on CFDs, almost no changes since more than 2 years on those algos,  all earnings when exceeding certain amount above 10k I am withdrawing from this account, so periodically bringing equity down to 10k and keeping position sizes for each algo stable (as % of those 10k). this account is a „model“ in these terms:

    1. it contains most robust of my systems with kind of optimal position sizing for each of algo as part of the portfolio, resulting in – for me – acceptable portfolio result in terms of risk/reward.
    2. Since the reference of all results are always those 10k, having almost no changes of systems, also not adding or removing systems, I have comparable numbers month over month, and year over year
    3. It’s not my main account 😀 since „main“ I am now running on futures, but „main“ contains currently 7 out of 11 algos from the „model“ (the reason I am not running all 11 on futures is because I would not be able currently to run all of them with intended/their unique position sizes within a portfolio)

    So, end of month results as % of equity on „model account“:

    SEP +3,7% OCT -6,2% NOV +1,2%

    So yep, OCT/NOV was not great but in fact nothing extraordinary – even if somewhere end of NOV this account was reaching drawdown of 13,7% of equity. Not funny for sure, yet 13,2% drawdawn it experienced in APR this year as well (when GraHal was opening this discussion), and SEP 2023 it had similar drawdown, too. So all fine – this matches my target: not to have drawdowns exceeding 15% of equity.

    What do I learn, from such months… and drawdown periods… they will come again and again! They have to come. And the worst is probably not in the past but in the future. So I have to expect such times – and that means I have to be prepared. And being prepared means first of all – don’t „overtrade“ (means – don’t trade too big positions compared to the equity available). And reduce risk (position size) if drawdowns approach levels which are not „comfortable“ any more for me personally. I was reading that I think some 15 years ago but I will never forget, what Larry Hite was telling in his interview: „Risk is a no-fooling-arround game. It does not allow for mistakes. If you do not manage the risk, eventually they will carry you out“. Furthermore, what I learnt during “bad times” is that there are times where kind of everything goes wrong, longs do not work, shorts fail, diversifications seems not to help, everything “goes to hell”. I think there are probably time periods where biggest market players withdraw from the market, not acting, not taking decisions, waiting, just waiting for some catalysts, and during such times there is quite a mess “everywhere”, in major indices, currencies, commodities… maybe at these times trading single stocks would work, but I don’t know and I don’t care these days. I have to take care I “survive” those messy periods until they are gone. one cannot predict when they will start, nor when they will be gone.

    I would never again accept drawdowns bigger than 20% of equity, but as mentioned above, I am targeting (since arround 4 years) to have not more than 15% as max drawdown. And I think if my main account will be growing further I will be probably reducing my expectations down to max 10% drawdown and possibly even further. I kind of do not have „target“ for earnings / no precise max profit expectations, but I definetely have a „target“ for max acceptable losses.

    And since SweTrade posted his YTD result and asking others, I am willing to post mine: the „model account“ earned so far 67,5% with above mentioned 13,7% max drawdown. In fact pure trading result was ~75% but lot of if was „eaten“ by overnight financing costs and some smaller part by guaranteed stop fees (using such stops for those few algos which are designed to carry positions over weekends and bank holidays).

    Even it’s not a 100% proof, I am attaching as „proof“ the printscreen from IG platform with real results of that „model account“, where you can detect equity curve and some more details as well. Maybe funny one – especially for those chasing win-rates of 70% 80% 90%: my „win-rate“ is only 18%, so only 117 out of total 660 trades this year were closed with profit.

    What’s possibly interesting but not showing up in IG’s statistics: until mid of NOV my shorts on DAX – which was making multiple all time highs whole year – all together were earning YTD slightly more than longs all together. Ok, it turned arround very end of NOV – when DAX kicked off that amazing rally, going up with no significant pullback for 7 days in row.

    Cheers

    justisan

    3 users thanked author for this post.
    #241639

    Based on the hit rate, I would assume that they are basically trend followers. Probably with a small stop loss and a large take profit. May I ask what time frame you use and how many trades are triggered per day? And why you don’t use mean reverse systems? Well, yesterday all of these systems probably had a bad hand.

    #241729

    Hi phoentzs

    the last bar in the trade statistics I attached in the previous post shows negative revenue for the day you mean, so yes, portfolio was down on that „yesterday“ (19th of DEC). but it was not like „all systems“ were down, only 3 out of 11 algos were triggering some trades that day – which all were losing. You see, with the hit-rate ~ 20% one could say 4 out of 5 days „on average“ are / will be losing money. On other hand longer term results are totally different: this year model account had 4 months with negative and 8  with positive revenue. Last year was the same. so quite consistently profitable months are outnumbering the losing months, and if one calculates the „hit-rate“ as number of winning months vs. losing – it’s like ~70%, so not exactly but close to opposite of the hit-rate on single trade level. Portfolio triggered around 670 trades last year, and almost same number I assume by end of this year, so arround 3 per day, but of course there are very different days, some triggering 0 trades, others more than 10.

    Regarding hit-rate and the type of systems behind. Not myself but somebody else would possibly classify some of those systems as „trend followers“ (entering trades in the direction of prevailing price move), some possibly as „mean reverse“ (entering trades in the opposite direction of prevailing price move), but for all of them is common that potential losses which I am ready to accept are relatively small compared to the potential gains which I am expecting, and on top I move stop loss relatively quickly (might take few minutes up to few hours) while I am exiting trades in profit relatively slowly (can take many hours up to many days). so even if few of those systems are entering trades in opposite direction of prevailing price move (kind of mean reverse-type) I do not bet prices will move just back to some „mean“/“fair value“ and there I will be exiting, no, I bet prices will move huge way into expected direction. Since those big moves are quite rare, I have quite miserable hit rate on single trade level, that’s all.

    Myself I would not classify my systems as „trend following“ or „mean reverse“ type. Behind those commonly known types there is certain basic concept which I am in the meanwhile massively doubting. I am doubting to the very roots that it makes sense to apply known statistical data analysis approaches to the price series of financial instruments – which then lead to the development of so called „indicators“ – which then are used to identify if instrument is „trending“, if instrument is „overbought“ etc. etc., and on top one can apply „optimization“ of all the indicators and their parameters – the ultimate tool for messing up everything. When one measures average weight of apples or calculates probabilities of casino games, puts in formulas cycles of natural phenomena  – all that makes sense, one can derive some knowledge from the results, they have also predictive value. When one the same or similar way measures price series of financial instruments traded at the exchanges – it absolutely does not make any sense to me. And it does not matter if one calculates simple moving average or any other of countless types of moving averages, it does not matter if one assumes „normal“ price distribution, or any type of other distribution models. With price series one has thousands, millions of data points and the „data sample“ is permanently expanding: what kind of average does the trader want/need to apply? And what period? One has billions of potential „average“ variants… do those averages then make any sense at all?

    This way of thinking was resulting in removing absolutely all „indicators“ from my systems, so now non of my systems „know“ if it is currently „up/down/sideways-trend“, nor does it know if instrument is now „overbought/oversold/at fair value“.

    wishing everybody nice end of the year, and happy trading in 2025!

    justisan

    1 user thanked author for this post.
Viewing 14 posts - 16 through 29 (of 29 total)

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