Would love to read those papers if you have them, sound very interesting.Without skill or transaction costs, the distribution of terminal one-year wealth (cumulative trading profits) would have a near zero mean but would be heavily right skewed. The median and mode would be to the left of (less than) the mean. So more than 50% would be losers. The math of this was worked out in a Bouchaud paper around six or eight years ago and is also touched on in Piketty's book a few years ago (and expanded on a little more in a recent paper where Piketty was a co-author, the name of which escapes me at the moment). I'll try to find the Bouchaud paper and post it here tomorrow if I find it.
Edit: The argument in Piketty et al is obscured by their focus on generally positive return on capital (postive interest rate, investment return, rent, ect) but it works out even if expected return is zero. Consider two consecutive coin flips, risking 100% of your stake on each flip. Expectation is zero, but 75% of the time you'll end up minus 1 and 25% of the time +3. A bit like the Petersburg game: expectation (mean) is infinity but you'd only pay a few dollars for it.
In the four years combined, a total of 13,224 customers experienced aggregate losses of nearly $220 million (€175 million), with the remaining 1,575 customers earning a combined $17.51 million (€13.8 million).
Interesting. My thinking was that random trading is more or less is a random draw from the market which should asymptote to the distribution of the market. I am guessing that once you start chaining random returns that is not true any more, but it's not intuitive to me yet. Very interesting, would really like to read the paper!Without skill or transaction costs, the distribution of terminal one-year wealth (cumulative trading profits) would have a near zero mean but would be heavily right skewed. The median and mode would be to the left of (less than) the mean. So more than 50% would be losers.
Ok...glad @Xela jumped in on this one. To reiterate my point, there are selective forces at work that make the distribution not a normal statistical distribution. To explain those selective forces, someone with the requisite background to understand the inner working sufficiently to explain:Well, it's a random process nonetheless, with people washing out and people entering at random.
It isn't.
The huge difference responsible for the very different collective outcomes you've observed (and about which you're definitely right) isn't directly because of the differences between the asset classes: it's mostly because the trading participants of those different markets are different groups of people with different approaches and attitudes.
The entire world of retail forex "brokers" (they're not actually brokers at all - just counterparty market-makers pretending to be brokers) is designed and set up specifically to attract an enormous turnover of customers most of whom are destined gradually, inevitably, inexorably to lose: typically they're undercapitalised, over-optimistic, prone to gambling, attracted by "free bonuses" and competitions, they don't really understand what a broker is, they're typically undereducated (at least in the ways directly relevant to what they're trying to do and how to do it), they're overleveraged, and they tend to have unrealistic expectations which lead to more or less deluded perceptions of what they hope to achieve and how quickly. And the "brokers" concerned are highly skilled at targeting and attracting them, because that's how they make most of their own livings.
Most aspiring forex traders significantly overestimate the extent to which they can make profits quickly (while also actually significantly underestimating how well they could potentially do much more slowly, with the requisite patience and discipline, by developing real skills built on a foundation of numeracy and understanding/experience of the generally counterintuitive worlds of probability and statistics).
"Investors" are - by comparison - far more concerned with capital preservation, and are less gambling-oriented, and unsurprisingly they tend overall to do better.
The asset classes with which each "group" is engaged are necessarily different because of the ways their markets are structured, thus giving the misleading appearance that one asset class is "harder" than the others. In short, the facts you've oberserved are indisputable, but the reason you (and many others!) have attributed to this phenomenon really isn't quite right. Tom's post above, however, is exactly right.
Just FYI, a quick glance at the tick data - median b/o for EUR is 0.4 pips. Also, 1 pip is more or less equivalent to the bid/ask spread you see on the spooz and even 3 pips is miles tighter than what you get in VIX futures. You should mainly compare bid/offer to the volatility that the asset is realizing.When forex started Euro/US Dollar spread was 3 pips, hmmmm $30 bucks !!!
