By blowing up my account, I meant lose around 20-22 percent of my capital if I were to have 12 consecutive losses. I am looking for a filter such that even if I have fewer trades, losses don't come in clusters.
If you can only trade on the long side where you live - I'm going to second the vote for using a long term moving average as a filter. There are other ways to do it but that's a good starting point. I'm not saying that you can't ever go long in a correction or bear market. Short covering rallies / squeezes are often breathtaking. It's just that you can't apply the same logic that works in a bull market. As others have mentioned, using a measure of recent volatility, an ATR function or Std Dev to adjust your position size is also a good idea to help smooth things out if that is your goal.
I’ll offer some ideas in an attempt to answer your question and then expand into a broader discussion of RTM trading for the possible benefit of other readers. My philosophy on RTM trading, in all timeframes, is I’m trading against an established trend. Therefore, time is not on my side. As such, I use time stops that trigger either at the end of the second price bar or briefly into the third bar, win, lose, or draw. For overnight trades, I exclusively use very short term, defined risk option strategies. My stop loss is the same as my profit objective, usually a full retracement of either a wide range bar or a reversion to the mean, typically based upon a simple moving average. My RTM considerations are: 1. Extent of reversion using x-ATR from mean or Keltner Channels using x-SD. 2. Nature of the underlying to gauge likelihood of extended adverse moves. 3. Age of current trend, with greater confidence on a RTM trade idea on well established trends. 4. Order execution can be at the close of a wide range bar, a change of momentum, such as a bar break on a shorter term time frame, signs of distribution or accumulation contrary to trend, such as extended period of narrow range bars on a shorter time frame along with confirming tick action. Note: Price consolidation that often precedes trend continuations can look like accumulation or distribution, with subtle differences seen in relative volume and in level 2. In general, I will not fight VWAP on a overnight trade idea without taking protective action in some form, such as waiting for a better entry, hedging, or closing out the position. The exception to my VWAP rule is x-ATR from WVAP after a specific time of day. However, intraday reversals of strong trends are rare, making entering near end of day often less stressful, if one is willing to accept a adverse gap move next day. After a losing trade, I have rules that allow reentry after a timeout period and or if price reaches another statistical “Cluster” related to x-ATR from mean for that particular underlying. As a recent example of a trade that initially went wrong, but ultimately led to profitable trades, was with AMD. I see AMD as an established company and expect price reversions to be reliably turned back. Further, there were a couple of news events that had negative long term implications for the current trend, as institutions care about such things in order to avoid getting trapped with their often huge positions. I bought a .35/.05 delta call credit spread for a swing trade that I closed out at a loss of 130% of my initial credit. However, I felt AMD was definitely in play. I traded the underlying intraday as well as its puts for a nicely profitable result. As it turned out, AMD topped that day. This trade reaffirmed my idea to not allocate full risk to a particular trade and to be willing to shorten one’s time frame when conditions warrant. For more consistent returns and more confident higher utilization of capital, multiple RTM trades using different asset classes may be optimal. Sometimes there are RTM opportunities on both sides, but in different industries, potentially creating a more market insulated portfolio. Defined risk and convexity can be a beautiful thing. Costs and management requirements will be higher for multiple RTM trades, but for me, it’s worth it. I believe RTM strategies lend itself well to automation, but an experienced, well disciplined trader with a broad view will outperform a computer.
Conventional wisdom suggests 1-2% per trade. However, given you have back-tested across an extensive dataset, you should be able to derive a sensible risk per trade from the observed drawdown across the test. TDUK
This shows probably of the string of losses given a certain win %. https://www.newtraderu.com/2020/07/22/risk-of-ruin-calculator/
The issue is that there are 131 stocks with enough volume to trade here (And even out of those 131 stocks the major buying/selling is in 30-40 stocks!). Even if I am taking bets in 15 of those stocks on average, to employ 100 percent of the capital on average, I would need to risk 6-7 percent per trade. Any suggestions? This is why most of the people do fundamental analysis here. They are engaged in not more than 4-5 stocks at a time. By these standards, me trading 10-15 stocks at a time, is much more.
%% 7-8% average loss,can work well, Oadi,that 's what CAN SLIM averages. 555 page book system. 100% percent capital sounds a bit aggressive, except even that can work well adding to it monthly or quarterly . Me, i can watch 7 or 8 ETFs better than 20 , but i do both, so i have an order in my notebook, last one one on page s least profitable. I dont know of any fund that uses 100%[no cash @ all cushion even if using leverage] MSFT for example/ is a bit unusual, most dont grow that well, that long. Good question
Now here is the issue. I just checked my notes, I have a system, with a win percentage of 61.79 with Average Gain/Average Loss ratio of 1.5. The winning percentage is lower, whereas the reward/risk is higher. However, I don't know how much to risk per trade, given the constraints that I would probably have 15-17 trades at a time on average (this number also includes trades from a trend-following system that I would be employing at the same time as the mean-reverting one). They can go upto 20 in periods and be as low as 7-8 in periods. This system has 18 consecutive losses when covid hit the markets. How do I filter out some of those trades? These 18 consecutive losses have an average loss which is more than the average loss of the system. It means that I could lose around 20-25 percent of my capital because of one bad period.