Trading, as in standard spot or derivatives trading, is a bit of a one-dimensional game, in that it's primarily based on predicting price moving up or down based on probabilities of circumstances that have happened, are happening or about to happened.
Price has a rather definite and perpetual of sorts imprecision.
A stock (or token) price is a blunt instrument, since it collapses all opinions into a single number and you can’t just bet on why something is moving, only that it is moving.
I think the more fluid aspect of trading that makes it look like 4D is the game of probabilities involved, reality is messy, lots of moving variables, unexpected surprises, blank/white swans, etc. all of these no matter how complex it gets tends to settle down back to the price of whatever is been traded.
If I have an opinion that a company will beat earnings but the market will react negatively due to guidance, standard trading forces me to guess the net result on price.
I can't easily isolate the "beating earnings" variable from the "market sentiment" variable.
Prediction markets
To compare and contrast, despite the binary outcome with prediction markets, there's more specificity with regards to how a trade is executed upon based on a set of outcomes.
Prediction markets allow one to construct completely novel, high-specificity viewpoints.
I've heard just yesterday listening to a podcast by threadguy and tulipking that Lighter, a perp dex that is currently doing significant volume, presents a perfect example of this.
Two outcomes can be betted here:
Will Lighter TGE before the end of this year? (Currently ~85% Yes)
When TGE happens, would the FDV on launch reach $1B? (Currently ~75% Yes)
My own spin on this would be to only bet on the latter as it's fundamentally mispriced relative to the former. If they TGE, given their volume and recent raise at $1.1B, it is almost a certainty the FDV will be over $1B.
There is a 10% delta between the "TGE Yes" and "FDV > 1B" that shouldn't exist.
The former is all too risky on its own due to the arbitrary nature of dev timelines.
However, according to tulipking, one strategy that I could employ is a cross-market arbitrage.
The Play: I'd buy "Yes" on FDV > $1B (cost ~75c) AND also buy "No" on the TGE happening this year (cost ~15c).
The Math: Total cost is ~90 cents.
The Payout: If they don't TGE, my "No" hits ($1). If they do TGE and it's over $1B, my "Yes" hits ($1).
The Risk: I'd only lose if they TGE and the valuation is under $1B, which would be a "double loss" scenario that is highly improbable given the fundamentals.
As I side note, I didn't take this trade at this time of writing. I'm still a bit far off the mark with understanding prediction markets, especially the basics.
No longer just hype
I think this is the main difference with legacy trading. Other than pre-market trading for Lighter based on price speculation, nothing else can be done. You are forced to bet on the whole messy reality at once.
Whereas with prediction markets, the whole has been split into different parts, so to speak, and these parts can be bundled to create a synthetic position that offers a better risk-adjusted return than betting on the asset itself.
As the podcast puts it, standard betting apps (DraftKings, etc.) are like a calculator, prediction markets (Polymarket) are the iPhone.
You get the calculator for free, and also get the camera, the internet, and the apps.
What you essentially have now is a platform of sorts for structuring your own financial products based on conditional realities.
Previously, the whole prediction markets hype was categorize as just that, hype.
After listening to the podcast and tulipking explaining the novel mechanisms with prediction markets, I'm drawn to doing more in depth research as a curious person trying to understand what trading 2.0(or is it 3.0?) could look like.
Reference: TulipKing: Prediction Markets Supercycle
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