Not end of 2008/early 2009 IMO.
I am sure people lost and won fortunes no doubt, as I said I am guessing very much that the greatest amount were losers and in a very big way.
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Risk reward ratio and winning odds
- Thread starter traderzhangSan
- Start date
Not end of 2008/early 2009 IMO.
I am sure people lost and won fortunes no doubt, as I said I am guessing very much that the greatest amount were losers and in a very big way.
Quote from Algo_Design_Kid:
Not end of 2008/early 2009 IMO.
I am sure people lost and won fortunes no doubt, as I said I am guessing very much that the greatest amount were losers and in a very big way.
For amateurs it was a dangerous time, for experienced traders it was like shooting fish in a barrel. I'm not sure who you were referring to when saying that "we" should stay out of the market until VIX <25.
Quote from alexandermerwe:
Correct. But if you do not specify the order of the events, but just their number, the probabilities change.
In the first example, the event is {heads occur 4 times}.
P{heads occurs 5 times in 5 trials} = 5/32
In the second example, the event is {heads occurs 2 times}
P{heads occurs 2 times in 5 trials} = 10/32
Just a minor clarification on what you wrote, so that neophytes won't be misled. The true probability remains, and does not change,.5 heads and .5 tails (assuming an unbiased coin, of course.) In the Pocketchange experiment, the sample size is 5. Using a sample size of five to estimate the true probability naturally will result in different probabilities of heads or tails being calculated for samples of five tosses. Each of these probabilities are simply imperfect estimates of the true probability which in this experiment is known to be 0.5. If you tossed the coin in an unbiased manner five times and repeated that an infinite number of times, we can all rest assured that the average probability of all the individual probabilities calculated from sets of five coin tosses would be 0.5 heads and 0.5 tails.
You don't need to specify the order of the events, i.e., observations. The only requirement needed to get, eventually, the correct average probability is that the events be observed in random order, i.e., in no particular order. "Random" doesn't mean that the datum being estimated from individual observations is random, it isn't. "Random" means that the observations are made in random order.
Quote from Dustin:
For amateurs it was a dangerous time, for experienced traders it was like shooting fish in a barrel. I'm not sure who you were referring to when saying that "we" should stay out of the market until VIX <25.
Yeah, I've heard a lot of people referencing it was like shooting fish in a barrel. But I am guessing most were using a SIM account with an unlimited stop loss as well. GL to you the rest of the way no matter which side you were on.
I understand but the example was a specific wager where exactly one sequence results in a bust. All other combination's win with varying payouts directly related to your wagers.
The point I was trying to make was relating this example to trading with tight stops and small profit taking. Tried to demonstrate even with 97% odds of winning if you don't take sufficient profits you end up losing.
The point I was trying to make was relating this example to trading with tight stops and small profit taking. Tried to demonstrate even with 97% odds of winning if you don't take sufficient profits you end up losing.
Quote from intradaybill:
No, the probability of getting two heads in a sequence of five tosses is not the same as the probability of getting any sequence in 5 tosses.
In general the probability of getting k heads in n tosses is not the same as the probability of the outcome of any n tosses.
This affects drawdown probability, as the probability of getting a number of losers in a row is always lower than getting the same losers spread in the same number of trades. Someone would think this is to their advantage but it turns out the equity reduction is always the same. Think about it
2 winners followed by 3 losers
1 winner then 1 loser then 1 winner then 2 losers
The end result is the same although the probability is much different. This should ring some bells. There are some deep conceptual problems in applying a priori probability to the real world.