I kinda agree with you. However, theoretically, I would have been more than happy to put my money in an actively managed fund IF that fund was managed by someone with a very high intelligence and who was able to sit still. By sitting still, I mean not buying and selling all the time. Often, it's far more profitable to sit on shares for many years, rather than buy and sell all the time. But I guess those fund managers are expected to come into some office every day at least from 9 to 5, regardless of whether there is anything to do. Also, they probably have co-workers and bosses who ask them what they're doing. Maybe it would be kinda boring to answer "nothing" every day for like 2 years in a row.

I watched a documentary recently that suggested that they gain % for every X period they add value (over risk-free rate?), but don't pay back any % for losses they make? This the situation?

They could do things other money managers couldn't - short stocks (i.e. hedging against a fall, hence their names), better analysts, investments in more diversified instruments, early HFT.

They would often take a fee of two and twenty - that is to say 2% of the money you lent them (every year), plus 20% of the profit they made from that money.

If you gave them $10 million, they'd take $200k as a fee every year, then 20% of the profit they made. So let's say they made you $1 mill a year, they'd be paid in the first year $200k fees and $200k performance fees.

However nowadays there's millions of them, and almost all of them lose money as there weren't that many profitable niches to begin with, and a lot of them were lucky anyway (survivorship bias).

Of course any reported results on hedge fund returns are kinda funky for the reason of bias that you mention.

Survivorship bias is huge in this industry. There have been plenty of funds with awesome runs, but few have lasted 20+ years.

PS: The financial industry also loves to point at old funds as being above average while quietly killing off lot's of tiny funds and growing others over time. IMO, this goes past survivorship bias and into the old con where you mail 1024 people the results of a game, then 512 people you got right, then 256... Until you have great history with your last sucker.

There are hundreds of strategies in hedgefunds from HFT to Macro to volatility trading to commercial ground rents to God Knows What™ - so I'd really like to see what was being done for this kind of analysis (and who by and what data they had access to).

Past performance is a lot like the false positive problem in medical testing. A 99% correct test on a condition affecting 1% of the population is not useful. Similarly looking at past performance for a hedge fund is a poor way of identifying those with "alpha" (if you believe true alpha exists at all, which is entirely dependent on your point of view).

Take Mr Buffet as a spurious example. If he leaves the fund, it won't affect past performance for some time. So do you want to buy into B-H without him - just because it used to make money? Or would you go into his new fund because you think he has a process that works.

Good sysadmins as well.

Somewhere along the way operators think that if they don't push a button every fifteen minutes they aren't earning their pay (I blame bad management and production pressure). So when in doubt, look busy. It has awful and confusing effects on processes, leading to long term hard-to-diagnose noise in otherwise stable systems.

I think the same principle applies here. We want vigilant, patient, and wise did managers. Not just super active and excitable ones.

I am not against ETF, in fact that's what I would use, but it comes with its own problems.

Tomorrow I will buy 10 shares of XYZ at any price, and everyone knows this. XYZ is worth $100/share and today that is the price. If one other person in the world owns XYZ shares they can sell it to me for $200,$300, whatever price they name. If 2 people own shares, there will be competition, and I'll buy at the cheapest price available. If 1000 people own shares I will still have to pay more then $100, but if there is true competition on price then I should only pay slightly over $100.

Say company X is getting bigger, and pretty much qualifies to get into the S&P500 at the next revision of the index, it currently trades around 100.

When it gets into the S&P500 all the ETF buyers will buy this stock, that will push the price up to 110. Some of them will buy it at 100, some will buy it at 110 and some anywhere in the middle.

Now a bunch of hedge funds anticipate the ETF will do that and start buying it ahead of the stock going to the index. The price of that stock will rise to 102, 105, perhaps 107 if you have lots of people doing this arbitrage.

When the ETFs buyers pile in, they will be picking up the stock somewhere between 105 and 110, not 100 and 110.

Now one can argue this is the problem of the bank maintaining the ETF, because as far as the ETF investors are concerned, they own something that tracks the index, if it costs more to replicate the index, it is not their problem. But the way I see it is that the new stock will enter the index at an inflated price, and the price will converge again to the fair value when all the buying is done (instead of the price going up after the stock joins the index and converge again). That means that the ETF investors will have a lower performance than what they would get if no one was arbitraging them.

In the medium term active and passive management will eventually reach equilibrium. Passive funds cannot perform price discovery as well and rely on active funds to do this. However the ability of computers to discover prices will eventually exceed that of humans not possessing insider knowledge. My money is, literally, with the computers.

An academic analysis like what you linked to has to assume everybody have settled on the same definitions and valuations.

See my other comment describing what a perfect answer looks like.

I solve huge NP-hard problems every day, I've never seen any suggestion there is a useful way to solve marking pricing.

You have not seen any suggestion to solve this problem, does not mean it isn't NP-hard.

>> we just might not have to computing power to calculate it.

There is a perfect answer, and there will almost never be enough computing power to calculate it. It is always approximated.

So you'll have more "perfect" answers than people, and no way to select any one of them.

It's not a valid argument against the fact that everyone does have their marginal benefit and marginal costs for every good and service that can translate to a binary decision of whether they would purchase a good or service at a given price.

Just because you can't see it doesn't mean it's not there. And I'm not saying it's impossible to find out individuals marginal benefits and costs, because in markets you very well can. Stock traders, when evaluating whether a stock would go up or down, would often buy a bunch of stock, see how the market takes it, then sell a bunch, and by measuring how fast the market eats his orders, he can estimate the aggregate marginal benefit and cost of holding the stock, and then speculate accordingly.

I think this fact is more like an axiom.

With NP-hard problems like Sudoku, that's easy. Slightly simplifying, the definition of NP-hard is "easy to check the answer, hard to find it".

EDIT: Added rabbit ears for simple.

You don't need to solve an NP hard problem to beat human intervention. You just have to be faster and more accurate.

I do think that computers could outperform humans on the supply side, calculating the costs of production relative to competitors better than humans. The demand side is trickier but again computers would do a better job calculating available cash and then ranking marginal goods' likelihood of being purchased based on existing prices.

As long as prices and production processes are public knowledge computers will do better than people at modeling the economy. Humans only gain an advantage through insider knowledge and trade secrets.

Is it? I mean, I see how it's reflexive (and so chaotic) but NP-hard is the halting problem: given a program and it's input, decide if it halts. E.g. what is the input to your market function? It's like asking if the world halts.

The thing about all complexity analysis is that it ignores input/output.

Just that its NP-hard doesn't mean it's as hard as the halting problem, it could be easily decidable in exponential time.

Complexity analysis is all about the size of the input, it doesn't ignore it.

It will depend on your bank, but anecdotally it seems commission free mutual funds are more common than commission free ETFs. If you are the type who wants to invest X% of every paycheck (i.e. making multiple trades a month), are only investing a small amount of money, or are only investing for the short to medium term, you are likely better off with the the higher fee and lower commission. Retirement savings tend to be none of those three categories, so ETFs are almost universally better in that regard.

https://personal.vanguard.com/us/whatweoffer/stocksbondscds/...

Roboadvisors like Wealthfront solve this problem more elegantly and at lower cost.

This is (Canadian) RBC - Direct Investing.

In addition this particular fund also significantly outperformed other ETFs during 2008-09.

Anything sold by the big banks in Canada is almost always a ridiculous rip-off.

Even better might be something like Wealthsimple.

(Not affiliated with either company except as a customer)

1. I think passive money is generally not taking any position on whether an asset is over or under priced, and as a class tends to be very inactive. I doubt it either increases or decreases arb that much.

2. I think what would increase arb opportunities would be:

A. A critical mass of misinformed active managers

B. So few active managers that the market is gameable

However, as the number of active managers decreases, one would think that the misinformed ones would go first (A), and that (B) won't be a linear progression, but a sudden tipping point at a very low level of active management.

Actually, I sort of think the final statement is reversed. As the number of active managers declines, and the average active manager becomes more competent, it will become harder for the active managers to find profitable arbitrage opportunities.