Jump to content

Welcome to the new Traders Laboratory! Please bear with us as we finish the migration over the next few days. If you find any issues, want to leave feedback, get in touch with us, or offer suggestions please post to the Support forum here.


  • Content Count

  • Joined

  • Last visited

Personal Information

  • First Name
  • Last Name
  • Country
    United Kingdom

Trading Information

  • Vendor
  1. I've been following this thread since April last year with keen interest and am curious as to how the system has worked for eveyone over the last year. Has anybody kept a profit/loss log of their trades to show how the system has performed for them and would care to share?
  2. Soybean Meal looks good for tomorrow's open on my charts
  3. Hi TN, I generated it in much the same way you did (you will see how in the spreadsheet attached). Basically, I generated a list of 144 rand ticks that went either up, down or no change and added the result to the previous result. After 144 ticks, i started a new "day" using previous days close as the starting point and ran another 144 ticks. I repeated this 200 times to get 200 "days". Then, for each day I took the start, finish, max and min to generate the candle stick chart.
  4. Guys. here is an example of random data over 200 days (144 ticks a day). I've attached the spreadsheet used to create the chart. Press F9 and you can refresh the chart to get a new random chart. RAND.xlsx
  5. Surely entry must have been the best possible moment
  6. PWP, looks like you are using the Williams indicator (myself and I think Ingot are using the sRSI indicator). This will lead to slightly different entries and might be the cause of the differences. The key here though is to stick to your indicators and follow them, I wouldn't chop and change.
  7. Got knocked out of Oats this morning
  8. Tom, I've been reading the link you posted and found it very interesting but I don't know what makes you think it relates to money management. GBM with mean reversion is a strategy for predicting the price movement of a stock. And if you used it to predict the evolution of your bank, I think you would be disappointed with the results! I started this thread hoping to see well laid out plans for money management, for instance a system with properties x, y & z has a Risk of Ruin, R based on M% of your bank risked per trade. Instead I got a little bit of insight overwhelmed with squabbling, waffling and bragging.
  9. Hi nvr735i, I agree with limiting losses to only a fraction of your bank. To do this, you don't need to tinker with the parameters of the system. But simply set set your bank to be 20% of your account. So you would still make your 50% a year, but it would be 50% against 20% of your account, not your full account. Could you expand your thoughts on why you would need a large account to trade futures?
  10. Thanks BlowFish, that is exactly what I am doing. The coin toss example helped me move from a "string of losses" based approach of risk management (which severely underestimates risk) to a "drunkards walk" based approach. I read your link and I believe (and have shown) that the series of losses argument is flawed. The article you posted suggest that with a bank of $100, and betting $10 on a coin flip, there is 1 in 1000 change of going broke due to 10 losses in a row. I have show that if you started with $100 and bet $10, the chances of you going broke after 100 bets is 1 in 44! Which is far more likely that 1 in 1000 (we can discuss this further if you wish). I have tried to move the discussion forward from the coin toss example to closer to reality here: http://www.traderslaboratory.com/forums/money-management/10553-risk-ruin-discussion-2.html#post125713 I asked for real world examples to run in monte carlo but I've so far not had any takers. I intend to add to the simulation the effect of a varying win value e.g. some systems have a tight grouping of your win amount whereas some systems have quite a wide spread e.g. many small wins and a few big wins. But before I did that, I wanted to start with a simple example before moving to the more complex stuff.
  11. Hi BlowFish, I demonstrated this effect on the chart I posted earlier. Over 100 trades, and a RoR of 1 in 10,000, a break even trader who's trades win only 1 time out of 5 would have to account for 89 losses. Whereas a break even trader who's trades win 4 times out of 5 would only need to account for 20 losses. This is wholly down to the variance a few wins have vs what lots of wins have.
  12. Cocoa and Oats (again) look tradable tomorrow:
  13. Hi rdhtci, what I am getting at is; it is not the long run of losers or long run of winners that affect the variance but the probability of winning that has the biggest impact. I tried to demonstrate this by graphing the variance of different winning probabilities with 0 EV. It show the variance of 1 in 10,000 events. For example, using a fair coin and flipping it 100 times, there is a 1 in 10,000 chance that at some point along the way you will be down 38 or more points. You don't need 38 losers in a row to achieve this, just 38 more losers than winners at some point during the 100 flips, this makes things far more likely! I said the law of large numbers was irrelevant to the trader because the trader will never trade long enough for it to make a difference. The variance experience over a finite set is far more relevant and is what I am discussing. I completely agree being prepared is essential. This I have trouble with. If you have no way to predict future events then how can you possibly asses your risk and make a low risk trade? It is relevant in the same way the coin toss experiment you witnessed was an eye opener. It gives you a whole new perspective!
  14. rdhtci, both statements are completely true but completely irrelevant What is relevant, and what you skipped over, is the accumulation of results (which is what my subject has been all along). It's this accumulation that affects traders and we see it in our draw down. So, I'll ask again. If I flip a coin 1,000,000 times and starting at 0, I add 1 for every head and subtract 1 for every tail, what's the probability of my sum returning to 0? And something more relevant to draw down, what's the probability that at some point during the count my count will reach -100 or less?
  • Create New...

Important Information

By using this site, you agree to our Terms of Use.