[QUOTE=“PipMeHappy;761121”] I like this section of the article, it made me smile: <img src=“301 Moved Permanently”/>[/QUOTE] 
Whats the funny part , never mind we laugh together to it ))) I guess its wrongly translated
I think this is not only comparing casino games with forex also there is chart for comparing forex brokers with mainly stock brokers , and can see the people who trade longer term on their stock ! Can we get tht conclusion from this too? Different style of trading
Lmao!Quite True
The comparisons I always find interesting (though very predictable!), in this context, when they’re sometimes published, are the independently audited proportions of winning/losing forex accounts at [I]genuine[/I] forex brokers, who prefer their clients to be profitable, compared with those at the [I]counterparty market-makers[/I] who have a direct incentive for their clients to lose money because they themselves are holding the other side of their own clients’ trades!
Those tell a [I][U]very[/U][/I] clear and interesting story. 
Another interesting article, thanks.
[QUOTE=“lexys;762071”] The comparisons I always find interesting (though very predictable!), in this context, when they’re sometimes published, are the independently audited proportions of winning/losing forex accounts at genuine forex brokers, who prefer their clients to be profitable, compared with those at the counterparty market-makers who have a direct incentive for their clients to lose money because they themselves are holding the other side of their own clients’ trades! Those tell a very clear and interesting story. ;)[/QUOTE]
Yes dear lexys
Yes, good thoughts and interesting points of view.
how much Traders Expect to Make per Month
You will see results of an interesting survey of more
than 1500 traders done a year ago at a webinar which I attended. Such a large
number of participants in a survey makes the survey results rather valid and
credible. Please note traders were trading various markets not only forex.
The focus of the survey was to determine how much
money people had for trading and what their expectations were from trading in a
financial sense.
Participate
in a survey
BEFORE YOU WATCH THE VIDEO or read the rest of the article, please write your view/answers to the
following questions in the Comments section:
How much do you believe traders have in their trading accounts on
average?
How much profit do they expect to make per month in % terms?
A VIDEO
version of this article is available on YouTube at [SURVEY RESULTS] How (under)funded are trading accounts? Compare with your situation! - YouTube
Note 1: If
clicking on the video link doesn’t work just copy the link into your browser.
Note 2: The
text below is not an exact transcript of the video.
1st
survey question: How much money do you have?
This question addressed the overall financial
situation of the respondends i.e. in life in general, not just in trading.
Enough or plenty: 54%
Not enough: 21%
Can’t make ends meet: 24%
We can see that 1
in 4 traders came into trading with the hope of earning money for living
which they could not make elsewhere. This is rather alarming because we all
know that trading is a risky business! Betting your life on it isn’t reasonable to say the least.
2nd
survey question: How much capital can you use for trading?
Less than $1000: 11%
$1000-$2.000:
5%
$2000-$5000: 7%
$5000-$10000: 12%
$10000-$50000: 30%
More than $50000: 35%
If you remember answers to 1st question you
can see that many webinar attendees had a lot of money. In fact, there were many
pensioners present at the webinar. They wanted to make more money with their savings. So it
comes as no surprise that many attendees had or intended to have large trading accounts.
3rd
survey question: How much money do you want to make from trading per month?
Less than $1000: 13%
$1000-$2000: 17%
$2000-$3000: 16%
$3000-$5000: 18%
$5000-$10000: 21%
More than $10000: 15%
We can see that the majority of people didn’t intend
to become rich from trading as they were targeting relatively low amounts in
absolute terms.
However, 1 in 7
traders intended to make a very good living from trading if $10,000 per month
can be taken as such an amount that guarantees that.
Performing
an analysis of the data so far shows …
Note: As the
exact distribution of survey data isn’t available I performed a linear interpolation
to derive the numbers below. While the exact numbers cannot be known they don’t
impact the final conclusion which is valid in my opinion.
65% of the traders with large trading accounts.
Had on average $50000 in their
trading accounts
Wanted to make $7033 or 14% per
month
35% of the traders with smaller trading accounts:
Had on average $3642 in their
trading accounts
Wanted to make $1208 or 33% per month
The numbers show that traders with larger accounts
want to make less profit in relative terms per month than traders with smaller
accounts. This makes sense as a lower percentage of a large account is a large
number in absolute terms.
Getting 14% or 33% per month is surely possible.
Dukascopy trading contest winners make a few hundred and even more than one
thousand percent per month.
However, there is a more important conclusion that we
can make. Assuming that the spectrum of various strategies will be more or less
the same across all traders than traders with smaller amounts must risk
approximately 2.5 times per trade more than traders with larger accounts.
It is reasonably easy to enter a trading contest with say
$5000 that one can lose and their life will not change. Then one can enter with
say 10% risk per position and if all goes well there is a huge profit at the end of
the month.
But if one doesn’t have enough money to make ends
meet…what can that person do? How much can they risk to make such profits?
There was one last question in the survey. The answers
will shock you and show you the trading world of a small trader in a different
light.
The last survey
question: How much starting capital can you lose in trading?
None: 23%
25% of capital: 17%
50% of capital: 16%
75% of capital: 18%
100% of capital: 21%
This is no joke! These are true results!!!
1 in 4
traders cannot afford to lose ANY money!!!
And 1 in 5
can lose very little!!
How mind boggling is that?
What is the FINAL CONCLUSION?
If we are to believe the numbers (I can assure you
that they were really taken from the webinar) then the numbers speak for
themselves:
approximately 1 in 3 traders wants to
make more than 30% profit per month
with zero or little risk!
Is it possible? Yes, anything is possible in this universe.
Is it probable? No, it is not very probable.
Is it reasonable? This is a subjective question. My
opinion is that it is not reasonable. It doesn’t make sense. We can clearly see
how people end up destroying their lives
with trading due to unreasonable expectations.
My opinion is just my opinion. It is subjective. You
surely have yours. It is subjective as well. So lets look at something
objective to be able to see how reasonable those expectations were.
What do
professional traders make?
This guy is Peter Brandt. He has been a professional
trader for decades. He trades various markets, currencies as well.
On his web site there is a publicly available audit of
his trading done by IRS for the periods 1981-1995 and 2007-2009 which is 18
years of trading.
The audit shows that:
14 out of 18 years were profitable
4 out of 18 years were losing years
i.e. his capital at the end of year was lower than at the start!
His
compounded annual growth (i.e per year!!!) was 41.59%.
Scientist Discovered Why Most Traders Lose Money – 24 Surprising Statistics
Why most traders lose money - scientists found out“95% of all traders fail” is the most commonly used trading related statistic around the internet. But no research paper exists that proves this number right. Research even suggests that the actual figure is much, much higher. In the following article we’ll show you 24 very surprising statistics economic scientists discovered by analyzing actual broker data and the performance of traders. Some explain very well why most traders lose money.
80% of all day traders quit within the first two years. 1
Among all day traders, nearly 40% day trade for only one month. Within three years, only 13% continue to day trade. After five years, only 7% remain. 1
Traders sell winners at a 50% higher rate than losers. 60% of sales are winners, while 40% of sales are losers.2
The average individual investor under performs a market index by 1.5% per year. Active traders under perform by 6.5% annually. 3
Day traders with strong past performance go on to earn strong returns in the future. Though only about 1% of all day traders are able to predictably profit net of fees. 1
Traders with up to a 10 years negative track record continue to trade. This suggest that day traders even continue to trade when they receive a negative signal regarding their ability. 1
Profitable day traders make up a small proportion of all traders – 1.6% in the average year.However, these day traders are very active – accounting for 12% of all day trading activity. 1
Among all traders, profitable traders increase their trading more than unprofitable day traders. 1
Poor individuals tend to spend a greater proportion of their income on lottery purchases and their demand for lottery increases with a decline in their income. 4
Investors with a large differential between their existing economic conditions and their aspiration levels hold riskier stocks in their portfolios. 4
Men trade more than women. And unmarried men trade more than married men. 5
Poor, young men, who live in urban areas and belong to specific minority groups invest more in stocks with lottery-type features. 5
Within each income group, gamblers under perform non-gamblers. 4
Investors tend to sell winning investments while holding on to their losing investments. 6
Trading in Taiwan dropped by about 25% when a lottery was introduced in April 2002. 7
During periods with unusually large lottery jackpot, individual investor trading declines. 8
Investors are more likely to repurchase a stock that they previously sold for a profit than one previously sold for a loss. 9
An increase in search frequency [in a specific instrument] predicts higher returns in the following two weeks. 10
Individual investors trade more actively when their most recent trades were successful.11
Traders don’t learn about trading. “Trading to learn” is no more rational or profitable than playing roulette to learn for the individual investor.1
The average day trader loses money by a considerable margin after adjusting for transaction costs.
[In Taiwan] the losses of individual investors are about 2% of GDP.
Investors overweight stocks in the industry in which they are employed.
Traders with a high-IQ tend to hold more mutual funds and larger number of stocks. Therefore, benefit more from diversification effects.
Conclusion: Why Most Traders Lose Money Is Not Surprising Anymore
After going over these 24 statistics it’s very obvious to tell why traders fail. More often than not trading decisions are not based on sound research or tested trading methods, but on emotions, the need for entertainment and the hope to make a million dollars in your underwear. What traders always forget is that trading is a profession and requires skills that need to be developed over years. Therefore, be mindful about your trading decisions and the view you have on trading. Don’t expect to be a millionaire by the end of the year, but keep in mind the possibilities trading online has.
————
– 1Barber, Lee, Odean (2010): Do Day Traders Rationally Learn About Their Ability?
– 2Odean (1998): Volume, volatility, price, and profit when all traders are above average
– 3Barber, & Odean (2000): Trading is hazardous to your wealth: The common stock investment performance of individual investors
– 4 Kumar: Who Gambles In The Stock Market?
– 5 Barber, Odean (2001): Boys will be boys: Gender, overconfidence, and common stock investment
– 6Calvet, L. E., Campbell, J., & Sodini P. (2009). Fight or flight? Portfolio rebalancing by individual investors.
–7Barber, B. M., Lee, Y., Liu, Y., & Odean, T. (2009). Just how much do individual investors lose by trading?
– 8Gao, X., & Lin, T. (2011). Do individual investors trade stocks as gambling? Evidence from repeated natural experiments
– 9Strahilevitz, M., Odean, T., & Barber, B. (2011). Once burned, twice shy: How naïve learning, counterfactuals, and regret affect the repurchase of stocks previously sol.
– 10Da, Z., Engelberg, J., & Gao, P. (2011). In search of attention
– 11De, S., Gondhi, N. R. & Pochiraju, B. (2010). Does sign matter more than size? An investigation into the source of investor overconfidence
Why, how and when you Can Use Aggressive Money Management
you
will see proof that using only one strategy with positive expectancy can make
your rich but can also make you poor. Trading results depend upon the
statistical distribution of trades which nobody can control.
What
you CAN control are many other factors, amongst them is your investment portfolio
structure, or better, the various strategy-market combinations. Doing this
right increases the chance of your trading being a profitable activity. See how
it is done.
Note of caution. This article is for
a serious trader who is prepared to put to use parts of his brain that process
mathematics and related sciences. Traders need to use mathematics and statistics for
proper analysis in order to develop proper trading approaches.
Please note also that numbers are shown using the European format ie. a comma is used as a decimal separator and a full stop as a thousands separator.
What is the standard advice you hear/read about money management (MM)?
The standard
advice one gets when s/he starts trading is to trade (very) small. “Risk 1% or
less per trade. Maybe 2%. Maximum 3% not too often!”
Such advice
is normally not supported by any serious background information. Why not risk
0,1% or 10% for example?
By the way,
there is nothing wrong with 10%, 1% or 0,1% or x% as long as one understands
why s/he uses that and what to expect as a probable result. Most traders don’t
understand this from a mathematical point of view because they hate mathematics
or find it boring, not to mention statistics or probability calculations. And
most importantly, nobody ever explained this to them.
Most MM
seems to be based on the logic that:
Most
traders lose therefore a lower risk per trade will at least prolong their trading.
Most
traders cannot control their emotions and by risking more they wipe out their account
unnecessarily fast so they should risk less per trade.
Furthermore,
very few traders seem to understand more than the simplest MM aspects. Of those
who understand MM, not many are prepared to go through an emotional rollercoaster of a large drawdown which is INEVITABLE with aggressive MM
techniques.
However,
such a drawdown can be optimised with a proper portfolio structure which is
described below.
We will compare the
performance/profitability of 3 strategies
Backtesting
of these strategies showed the following parameters:
Strategy
A
Win% =
40%, RRR (Reward to Risk Ratio) = 3
Expectancy
= 60%
A
simple explanation of expectancy is that it defines how much of your risk you
get back per trade if the statistical distribution of trades is ideal (which
never is!)
One
possible formula for calculating expectancy =
(Win% * RRR – Loss% * 1)/100%
Strategy
B
Win% =
75%, RRR = 1
Expectancy
= 50%.
Strategy
C
Win% =
50%, RRR = 1.5
Expectancy
= 25%.
We have one BIG problem with these strategies:
Strategies
A and B are proprietary and we don’t know how they function. We only know
their results.
Strategy
C is our newly developed strategy. According to the numbers from
backtesting it is inferior to the
proprietary strategies. But those two strategies are out of our reach so
what can we do to compete with them (if this is what we need to do)?
What happens when we apply standard MM?
Let’s assume
we have an account with $100.000. I used a Monte Carlo
simulation of 1.000 iterations of 200 trades with trades distributed in a
random fashion but in line with the theoretical W/L ratio of each strategy.
Note: This Monte Carlo simulation worked
in a mathematically ideal trading world with no spread, commission, slippage, broker stop hunting, central bank interventions and without the changing mind of the market.
Why 200
trades? If you have 1 trade per day this is about a year’s worth of trading.
Here are the
results, based on Excel calculations using RAND()
function.
Not surprisingly, strategies line up in
profitability according to their expectancy.
If
we run 10.000 simulations, we should expect wider extremes but also an average
which is not too far from the one calculated in 1.000 iterations.
The
results are below but only for 2% risk per trade and only for the first 2
strategies. We already know that Strategy C cannot compete with the other two
strategies due to its low expectancy.
If
we want to compete with Strategies A and B as far as profitability is concerned
we need to employ aggressive money management. Let’s say we decide to risk 5%
per trade.
The
results of Monte Carlo simulations are below.
The average
and highest final equity of Strategy C is now the best. Not surprising with a
risk of 5%!
However, we
have a PROBLEM. The lowest final
equity is way below the initial equity of $100.000. So we can see that by
applying aggressive money management it is possible to make as much money and
more with Strategy C as with the other two strategies but also to lose a lot of
money.
How can we solve a problem of the potential negative extremes in the
portfolio equity?
So far we
have used one strategy in one account. If we got hit by a statistically “good”
set of 200 trades, our performance was good. If we got hit by a “bad” set of
trades, we lost money.
We cannot
control the win/loss distribution. The
market does what the market wants to do. So if we trade this way with
aggressive MM, we will rely on LUCK a lot! We may end up extremely rich or
extremely poor. Not a persuasive enough argument if one cannot afford to lose
much money.
In the next
section you can see how we can minimise
our reliance on luck and increase our chance of success.
What happens if we use a different
portfolio structure?
One good way
to approach this is to show what happens when we divide our account into 10
sub-accounts of $10.000, each running one strategy-market combination which is
not correlated with other strategy-market combinations. (I told you it was a simulation in an ideal trading world. We need to start with a simple example to be able to understand it!)
All
strategies in those sub-accounts have the same parameters as Strategy C to keep
things simple. Of course, the trade outcome distribution is randomly
distributed in line with W/L ratio. We still risk 5% of the sub-account per
trade.
The results
after 10.000 iterations are shown below. Previous results are also included for
comparison.
The average
final amount in the portfolio is similar to the average final amount when
trading Strategy C on one large account. The BIG difference is in the highest
and the lowest final equity!!!
While we
lose a lot on the upside, we also gain a lot on the downside. In fact, we
sacrifice the upside to minimise the downside potential. But as capital
preservation should be a prime concern (no profit can be generated with no money!)
this is a good outcome.
The worst
case scenario in this particular portfolio situation is not any more a loss of
the initial equity but a decent profit which is higher that the
lowest final equity with strategies A and B.
The explanation of why this is so is beyond the scope of this article.
The reader who is interested in exploring the topic of money management in more
detail will surely find appropriate books for his/her perusal.
What is a possible conclusion of this simulation/study?
A conclusion
is simple: a diversified portfolio of non-correlated strategy-market
combinations minimises the profit and loss potential but allows us to use an
aggressive MM approach.
Please do
not forget that in trading we are always talking probabilities. Nothing is 100%
certain. An optimised portfolio structure cannot eliminate the possibility of a
failure. We can still lose it all despite our knowledge, experience and an
optimised portfolio structure if we get hit by a long enough losing streak.
However, the described approach can at least increase our chances of success.
What does this mean for YOUR
TRADING?
If
you have never looked at money management, strategy correlation and market correlation in
more detail I suggest you do it if you want to be successful in the long run.
While you can be successful without this knowledge and understanding, the
chances are vastly improved if you become more proficient in the mentioned
topics.
An
added benefit is that you will be able to participate actively in any
discussion about 0,1% or 10% or whatever % risk per trade. Trading “gurus” will
not be able to pull wool over you eyes.
Last
but not least: The more you know in trading the less luck and reliance on
others is required.
[B]NEWBIE GUIDE[/B] : :44:
Forex Broker Reviews | Forex Scam Alerts
CFTC / NFA Regulated Forex Broker Reviews | Forex Scam Alerts
How To Start Trading Forex Safely | Forex Scam Alerts
Learn About Forex Scams | Forex Scam Alerts
…
Jesus , look at Deutsche Bank…
Living a risky life… 
Thanks for the sharing.
Thanks for the sharing.
hey thank youuu , yes its a good articles
maybe that was last one ,i couldn’t bring enough attention and discussion in to the thread , many newbie members and other but shy to comment
keep going guys and have a good one
: ) ^.^