Is Trading like Gambling?

Discussion in 'Psychology' started by scalpmaster, Oct 18, 2006.

Is trading like gambling

  1. Yes, every moment in time is independent

    15 vote(s)
  2. Maybe, depending on the method used

    27 vote(s)
  3. Sometimes, when i win it's not!

    2 vote(s)
  4. No, I can cut my losses slowly

    11 vote(s)
  1. If every moment in time is independent of the next,
    then trading is no different from gambling (except you
    cut loss bit by bit).

    Every event in time is mutually exculsive like in lotteries,
    therefore historical data/technical analysis
    is just a self fullfilling prophecy
    enforced by man(powerful ones)

    If the markets are like some casinos where even a time traveller
    can never win because the future is change after he place
    the bet, wouldn't that mess up the space time continuum?
    Perhaps that's how the universe is keep in check?

    :p :p :p
  2. Drew07


    Hope this isnt a stupid question...I'm relatively new. While we're on the topic: Do support and resistance levels exist because these are recognized by the majority as important levels? Or is there just an amount of shares that are going to remain illiquid as they are held buy institutions that don't trade them daily unless there is big news?
  3. Rocko1


    You should take a class in statistics.
    Gambling is generally when you have an expectancy of lower than 0, but you keep buying them lottery tickets because you don't understand the math behind it...
  4. 1000


    No trading is the opposite of gambling. And just as an aside, this page is etched in my memory.

    I. Statistics

    i. Introduction

    1. Statistics can be used to describe and compare data distributions (frequency distributions), by categorizing the data into fixed numeric interval points and plotting the number of observations in each category (interval frequency) against the category descriptor (e.g. interval mean or range)
    2. Because of random errors, repeated observations or measurements of the same value are not identical / give different results
    3. The observation results have a “normal distribution,” described as a bell-shaped (Gaussian), curve with a maximum population mean (μ), corresponding to the central tendency of the population, and a population standard deviation or spread (σ)
    4. Statistics derived from a sample or subset of a population can be used to estimate the population parameters.

    ii. Frequency distribution

    1. Estimates of population mean
    a. Mean
    i. The population mean is the best estimate of the true value (μ) for a finite number of observations, and is equal to the sum of all the observations ÷ total number of observations
    ii. Accuracy is the degree to which the measured value agrees with the true value (μ)
    iii. Error (or bias) is the difference between the measured value and the true value (μ)
    b. Median
    i. The median is the midmost value of a data distribution, when all the values are arranged in increasing or decreasing order, for an odd number of observations the median is the middle value, and for an even number of observations the median is the arithmetic mean of the two middle values
    ii. For a normal distribution, the median is equal to the mean
    iii. The median is less affected by outliers or a skewed distribution
    c. Mode
    i. The mode is the most frequently occurring value or values in a frequency distribution
    ii. The mode is useful for non-normal distributions, especially those that are bimodal

    2. Estimates of variability
    a. Variance S2
    i. The variance (s², σ²) is the estimate of the variability or error in n observations
    ii. Described by population variance σ² for infinite observations, and sample variance s² for finite observations
    iii. S² = (∑Xi² - (∑Xi)²/n)÷(n-1)
    iv. S² = (∑(Xi – X mean)²)÷(n-1)
    v. (n-1) is the number of degrees of freedom (df)
    b. Range
    i. For a very small number of observations, the range (w) can be used to estimate the variability or error in n observations
    ii. W = |X largest – X smallest |
    c. Standard deviation
    i. The square root of the variance √s²
    ii. Standard deviation (σ, s, SD) is the estimate of the variability or error in n observations
    iii. S= √s² = √((∑Xi² - (∑Xi)²/n)÷(n-1)) or
    iv. S = √s² = √((∑(Xi – X mean)²)÷(n-1))
    v. Where (n-1) is the number of degrees of freedom (df)
    d. Precision
    i. Precision is the reproducibility, the degree to which replicated measurements or repeated observations of the same value, agree with each other i.e. “made in exactly the same way”
    ii. Expressed as the relative standard deviation
    iii. %RSD,RSD = (standard deviation σ ÷ population mean μ) x 100

    3. Standard deviation of the mean (Sm)
    a. Standard deviation of the mean (Sm), is the standard error of the mean (SEM), and it is an estimate of the variability or error in the mean of n observations
    b. Used to establish confidence intervals for describing the mean of a data set, or when comparing the means of two data sets
    c. Sm = (standard deviation σ / √n)
  5. So What is the expectancy in trading?

    If it varies, then it is as subjective as gambling.

    For those who believe statistics can improve trading,
    you should take a class in common sense.
  6. Options is considered gambling by the Canadian province of British Columbia, options are probably considered gambling by most governments.

    They did a survey on peoples gambling habits about a year ago and options was listed along with lotto tickets and casinos. Forex wasn't listed because it's rather new and governments are usually slow in updating things.
  7. Rocko1


    Gambling probability isn't subjective most of the time, your expectancy at a casino is ALWAYS below 0.
    Only time you have an edge is when you apply strategy then the term gambling doesn't apply anymore, e.g. card counting, basic strategy at black jack and etc.

    Trading without a plan/strategy is considered gambling, because this is when your demise is almost assured.

    Trading with a strategy of fixed probabilities where you have the edge therefore can not be defined as "gambling".

    Gambling is when the probability of losing is higher than winning.
  8. Fixed Probabilities...I like that. Tell me more on how to
    FIX my chances so that I can have an EDGE.
  9. Rocko1


    This is something I have developed after about 40 books in financial probabilities, risk management, technical analysis, economics, and fundamental analysis; then a year of strategy testing, and a year of live trading.

    You're fooling yourself if you think it's possible to learn from reading a forum on the internet.
  10. You can develop a strategy that increases your probability of winning and therefore gives you a statistical advantage. There are no guarantees the edge will last forever, but they do exist. Your job is to find them.
    #10     Oct 18, 2006