Thread by @therobotjames

It's easy to lose money trading if you:
1. Trade too much (paying fees + impact on each txn)
2. Size positions too big (high vol hurts compounding ability + gets u rekt)
3. Shorting positive drift/risk premia

It's hard to lose money consistently if you avoid these things.

However clueless you are, you get to trade at market prices.

Imagine we can know that an asset has a fair value of $100.

You might think it's worth $150.

But if it's quoted $99 / $101, you can buy now at $101.

You were totally wrong but you still bought close to fair value.

The same mechanisms that make it hard to get an edge also make it hard for you to trade at really bad prices.

In a simple model, you might say that prices are set by:
- (risky) arbitrage and relative value in the short term
- pricing/valuation models in the long term

Both of these games are ultra-competitive.

It is hard to make money in the short term because competitive fast money playing "the arb game" chases relative value opportunities and "gets paid" to disperse the impact of large orders and other supply/demand imbalances.

It is hard to make money in the long term because the pricing/valuation game is so competitive that is hard to get an edge from public information that is available to everyone else

These things make it hard to LOSE money consistently too.

(As long as you're not trading too much, sizing too big, or fighting strong drift)

If you are relatively small in a liquid market, you get to trade at prices set by the best at those games.

This means that, in most liquid markets, the expected return from random trading is zero, less your trading costs.

You're equally unlikely to accidentally stumble on negative alpha as you are to stumble on positive alpha.

What are the implications of this?

Most importantly, it's critical to avoid the 3 Mortal Sins of trading too much, sizing too big, and fighting strong drift.

Those are really the only ways you can screw up with confidence.

So avoid them.

Second, type 2 errors in trading may be less harmful than type 1 errors.

Trading something with no edge doesn't hurt you *that much* (as long as it's not super hyperactive.)

It has only slightly -ve expectation (due to txn costs) but it costs you in (unrewarded) p&l volatility.

This perhaps offers an interesting asymmetrical opportunity.

If you are good at finding edges (on average), it can be a good idea to err on the side of trading stuff that looks marginal.

(And nearly everything looks marginal.)

This may be especially true for edges that make economic sense, but for which there is not enough data available to run any kind of reasonable statistical analysis.

You don't want to trade any old rubbish, but the skewed risk/reward of giving something a shot is attractive

I sometimes see people passing up (what I suspect are) good, simple edges because they're not 100% sure about it, or "the backtest doesn't look that great."

That's likely a problem of unrealistic expecatations and lack of diversification.

Any single edge is going to be noisy and uncertain.

The game is won not by finding a few perfect high-performing edges.

That's asking a bit much.

And it's an overconfident bet.

Edges come and edges go. Diversification is an operational essential, given this uncertainty.

The game is won by:
1. Avoiding the 3 Mortal Sins (trading too often, sizing too big, shorting drift)
2. Trading the most reliable return sources (Risk parity over various risk premia / MM if pro)
3. Diversifying across many different edges

And perhaps:
- worry a little less about whether a given edge is real or "good enough"
- be OK that some things just won't work out
- worry a little more about maximizing the probability that you always trading with a few good edges.