If you don't want to lose money...

Discussion in 'Trading' started by crgarcia, Mar 24, 2007.

  1. As George Soros said: "the first step to make money, is not to lose money"

    So, if you don't want to lose money...

    A. Your strategy has to be effective more than 50% of the times.

    B. If your trading is lossing, close the transaction ASAP, since you have much less money than the market, even if you are a billionaire.

    Why? Because of the gambler's fallacy/gambler's ruin:

    Consider a coin-flipping game with two players where each player has a 50% chance of winning each flip. After a flip the loser transfers one penny to the winner. The game ends when one player has all the pennies. If there is no other limit on the number of flips, the probability that the game will eventually end this way is 100%. If player one has n1 pennies and player two n2 pennies, the chances P1 and P2 that players one and two, respectively, will end penniless are:

    P1= n2 / (n1+n2)
    P2= n1 / (n1+n2)

    It follows that the player that starts with fewer pennies is most likely to fail. Even with equal odds, the longer one gambles, the greater the chance that the player starting out with the most pennies wins. However, this does not imply positive expected value for the richer player since, for each complete game (many flips) that the richer player loses, he will forfeit more pennies than his poorer playmate.

    Consider players with 90 and 10 pennies respectively, repeating the game 100 times. The player with 90 pennies is expected to win 90 out of 100 complete games, winning 10 pennies each game. However, he is also expected to lose 10 games, each time forfeiting all 90 of his pennies. So after the series of 100 games, the richer player is expected to win 90*10=900 pennies, and lose 10*90=900 pennies. Despite the fact that after any single game, one player ends up with all the pennies, the expected result over many games is for both players to break even. Note that the law of large numbers implies that the ratio of wins converges to 9:1, meaning that each player's winnings or losses, as a percentage of total amount wagered, goes to 0.

    A casino generally has:

    * many more pennies than any player thus ensuring that the player is much more likely than the casino to experience gambler's ruin;
    * odds that favor the casino resulting in negative expected return for the player; and
    * various risk management techniques that limits their maximum loss.

    The combination of above ensures that the casino will in the vast majority of cases come out ahead in the long run. For an illustration, see this Gambler's Ruin simulation:
  2. This is a valuable contribution to the board.
  3. Your dissertation begins with a false premise. Plenty of strategies exist which have less than a 50% win rate, yet the 'system' produces profitable results - even after commissions and fees. In addition, plenty of strategies exist which have super high win rates, but they fail to produce profitable results - even before commissions and fees.

    - Spydertrader
  4. I'm interested as to what kind of high-percentage winning trades are losing money before fees and commissions - if you have a trade with a 60% chance of success, even if the winner and loser are equal, after 100 trades you have 20 positive transactions.

    Even if you only pulled in 50% of your 20 transactions after the fees for your breakevens, you still have 10 positive net transactions in a hundred.

    If someone is crazy enough to trade something where the average loser is higher than the average winner, then that sort of situation can lead to losses even at a 70% success rate.

    But Spydertrader, I'm just wondering exactly what you mean by your "high percentage" trades. Mine do pretty well most days.
  5. Um to make moeny buy stocks that go up
  6. Here's what I don't understand, what's this concept of breaking the bank. The 'game' never ends, it's only played once. And if you're good it's going to be an upward equity curve.
  7. maxpi


    Here's an account simulator based on percent winners and win/loss ratios. It is very interesting to run 100 simulations of a 50% winning setup with equal win/loss ratio. You can see that one guy would be saying he had the HG and the other one would be posting about how trading is fixed. This is just about what goes on all the time, most traders are just a little this side of random IMO and don't quite realize it, some are winning at the moment and some are not.

  8. I did not say "high percentage winning trades" are losing money. Clearly they are not. I did say ...

    In other words, if a system has 9 wins of a quarter, and one loss of $2.50 USD, the system has a win rate of 90%, but an overall loss of 25 cents before commissions and fees.

    I never said i would ever trade such a system. I only wanted to show that 'win rate' isn't the only thing on which one needs to focus as the OP implied.

    Again, you have decided I meant 'high percentage trades' when I clearly said win rate. I apologize if I wasn't clear in my original post.
  9. One of my casino favorites.

    You own a small casino in Las Vegas. It has 50 standard slot machines. Identical in appearance, they're identical in the function.
    They have exactly the same payout ratios. The things that cause the payouts are exactly the same. They occur in the same percentages. But there's one machine in this group of slot machines that, no matter where you put it among the 50, in fairly short order, when you go to the machines at the end of the day, there will be 25% more winnings from this one machine than from any other machine. What is different about that heavy-winning machine?


    What’s different about that machine is people have used modern electronics to give a higher ratio of near misses. That machine is going bar, bar, lemon. Bar, bar, grapefruit, way more often than normal machines, and that will cause heavier play. How do you get an answer like that? Easy. Obviously, there’s a psychological cause: That machine is doing something to trigger some basic psychological response. If you know the psychological factors, if you’ve got them on a checklist in your head, you just run down the factors, and, boom!, you get to one that must explain this occurrence.