until 1/3/07 -78% (resulting from early trades) 1/4/07 +13.0%, 1/5/07 +5.7%, 1/8/07 +11.2%, 1/9/07 +11.4% 1/10/07 +16.2% 1/11/07 +6.3% 1/12/07 +3.6% 1/15/07 +3.6% 1/16/07 -8.9% 1/17/07 -22.1% 1/18/07 -5.5% I need 30 events to make a clear statistics. Today on 1/19/07 I had a great time making my best %-profit ever! I will send the results later.
Will I absolutely like your post. I need to know more about your stile. Can you post a graphics? We both agree that money management especially after DDs is the key. I trend to risk to much and I am not sure that a bigger account size will change my trading stile because of attached emotions. That said, I will focus on %-tages only. The total amout is what I don't care about. We have in common that we both reduce our daily live cost. I check every position and replace expenses by free services (or low cost services) when possible. I have 16 MB DSL bandwith for about $50 per month including telefone. My PC is up to date and I am meanwhile trading every day more than 4 hours. I agree with you: Trading is great. All we need is that our accounts will survive the long run. You like to contribute, so do I. All I learned I have from the WEB. Thank you community. This tread is to give back.
until 1/3/07 -78% (resulting from early trades) No Date Results 1. 1/4/07 +13.0%, 2. 1/5/07 +5.7%, 3. 1/8/07 +11.2%, 4. 1/9/07 +11.4% 5. 1/10/07 +16.2% 6. 1/11/07 +6.3% 7. 1/12/07 +3.6% 8. 1/15/07 +3.6% 9. 1/16/07 -8.9% 10. 1/17/07 -22.1% 11. 1/18/07 -5.5% 12. 1/19/07 +44.2%
Germetric growth of that last twelve days is +5.5% per trading day. With 5% growth I would double account size every 14 (70/5) trading days. There is still big variance - less control in my trading. To get this performance I risked up to 2/3 of my account in active trades. Risk in % of amount is a function of Edge. The higher the edge the higher the risk one can take. For example: No trade if edge is 50:50; 50% 1/5 of account if edge is 60:40; 60% 1/2 of account if edge is 75:25; 75% 2/3 of account if edge is 84:16; 84% If I risked 2/3 of my edge needed to bee huge in that moment. If the edge is 55.5% (55.5:44.5) the percentage risked on average shouldn't be more than 11% of my account. Can someone confirm my math? Is that correct?
I read about the Chernoff bound: http://en.wikipedia.org/wiki/Chernoff_bound If the coin is noticeably biased, say coming up on one side 60% of the time, then we can guess that side with 95% accuracy after 150 flips. Translated to trading: If the strategy is noticeably with an edge, say coming up on one winning side 60% of the time, then we can guess that edge with 95% accuracy after 150 trading days. Before that it can be pure luck! What do you think?
It's a more than 2 hours video. Focus on the last 15 to 20 minutes. Very interesting. a) Options are Volatility (dominant factor) b) Volatility reverts to it's historically mean (no ever lasting trends) c) realized volatility has persistance (memory => forecast possible) d) alpha is in volatility, i.e. high frequency data e) volatility is tradable via VIX futures and options f) black and schooles formular doesn't work because of fat tail distribution http://video.google.de/videoplay?docid=-5001142862056244558&q=niederhoffer Let me know your thoughts.
Very interested, and I think this is tangentially related to the following post I had on a different thread to which no one has ventured an answer yet: From Acrary: "How often should you hit a new equity high? It can be calculated by using the % losing trades. Here's how, take the % of losing trades and multiply it by itself until the number is approx. .01 (meaning 99% chance of seeing a run of however many times you do the mutiplication). For example, if I have a method that loses 40% of the time, then the number will be (.4*.4*.4*.4*.4 = .0124). This means a method with 40% losers will have no more than 5 losers in a row 99% of the time. Next, take the number of consecutive losses and multiply by 3. In this case, the number will be 15. This is called the trading cycle. The cycle is the maximum number of trades that should happen before a new equity high is achieved. Draw a line every 15 trades on your statements and make sure a new equity high is hit within the 15 trade period." I was wondering if someone could clarify the above from Acrary. He recommends having at least 100 trades in your sample to start with. Ok, so let's say you win 60%, lose 40% in that 100 trade sample, so 60 winners, 40 losers. The probability of 5 losers in a row is 0.4 raised to the power of 5 which is ~ 1%. (i) So does that mean that once out of 100 trades, you can expect to have 5 consecutive losers and that out of 200 trades, you can expect to have a run of 5 consecutive losers occur two times? (ii) Also, what would happen if you are using n systems, each with its own win rate and the sum total of all trades from all systems would lead to a given win rate as well. How would you compute the probability of consecutive losers? Could it be that diversification of multiple systems could also lead to a lower probability of consecutive losses? Does anyone know the math for this? (iii) Back to Acrary: Why does he multiply the number of consecutive losses by 3 to get to the trading cycle? Does anyone know the reasoning behind this? Any thoughts on this?
ES335 this may give you more information. Loss series can be very long it there are phases of no 'memory' in the market. And then you should decrease your %-bet according the Kelly formula - and not even have the same or an increased bet size. http://en.wikipedia.org/wiki/Gambler's_fallacy Another good information about why traders should be careful "... Because people attempt to understand and make order out of the market, they assume that the longer a trend continues, the more likely it will suddenly turn around. More importantly, traders are usually willing to bet larger amounts of money on that assumption. Thus, traders want to pick tops and bottoms in a trendâa behavior that tends to be as dangerous as stepping in front of a moving freight train, hoping it will stop and turn around just for you. These biases are usually referred to as the gamblerâs fallacy. They have resulted in the ruin of millions of traders over the ages. The gamblerâs fallacy is one of those biases, which make trading difficult without a system and proper money management. However, traders frequently develop counter-trend following systems because of this biasâusually with disastrous results. " Source: http://www.iitm.com/Weekly_update/Weekly_289_Sept_20_2006.htm
That's exactly where I pick up my formula from. The example I gave before use a 50% win ratio, 6 consecutive loss @ >1%. I found (I) need more 12 trades (6x2) to be able to up size. 1.) Pure mathsmatic: 6 loss @ >1%, then you will have 6 win @ >1% for a 50 winning percentage system. 2.) Whatever you net after the 12 trades (6 wins, 6 losses), is the equity base big enough to support the additional contract? Not for me. Upping size from 3 to 4 contracts will takes 20 trades assuming 10 wins, 10 losses, no more than 6 consecutive loss, from 4 to 5 will be 16 trades, from 5 to 6 will be 12 trades (or 14s, depends where the losses distribute with in those trade). I guess Acrary use 3x the consecutive losses, so even if you don't know how the losses are distributes within the coming trades, there is a rough # of trades that he can surely comeout ahead. 3.) Regarding multi-systems, I would say this is a grey area. Will all you systems stop working at the same time to result in a a consecutive loss beyond 5? From one of Acrary old treads (System Development with Acrary?), he indeed use 5~8 systems (forgot), my guess is different breakouts in different time frames, and if one system went to hell due to not measuring the market right, the other systems should be OK or less effected under the same situation.