The research of Advait Jayant
Advait Jayant researches market microstructure, manipulation, and the economics of AI infrastructure. That spans two SSRN papers, on wash trading in NFT markets and the private-to-public-to-private cycle, reports on edge AI and AI compute finance, and technical books. The full bibliography is below, mirrored on Google Scholar.
The Economics of Wash Trading
What an 85-page study of NFT markets says about fake volume, token incentives, and whether manipulation actually works.
Papers and reports
- ReportThe State of Edge AI: The Report and What It Got Right
Written before on-device AI was a platform feature: why cloud-only intelligence hits latency, privacy, and bandwidth walls.
- Working paperBeyond IPOs: The Cyclical Journey from Private to Public and Back Again
Why do firms leave the public markets they fought to enter? A study of 2,585 companies on the private-to-public-to-private cycle.
- ReportThe AiFi Thesis: Financing AI Compute as an Asset Class
The argument that AI compute stops being a cloud line item and becomes something capital markets finance directly. Then Oracle, Blackstone, and AWS made it look obvious.
Explainers and methods
- Explainer
What Is Wash Trading? Definition, Mechanics, and Why It Persists
A trader sells an asset to themselves and the tape prints real-looking volume. Here is how the oldest manipulation in finance works, and why it refuses to die.
- Explainer
NFT Markets: Structure, Efficiency, and Manipulation
Every trade is public, yet the headline numbers routinely lie. What the structure of NFT markets does to prices, volume, and trust.
- Explainer
NFT Wash Trading: Scale, Motives, and What the Data Shows
On some days, most of the reported NFT volume never involved two real people. The data on who wash trades, why, and what it changes.
- Methods
How to Detect Wash Trading: Methods That Hold Up
You cannot subpoena a wallet. Detection on public blockchains leans on graph structure, funding trails, and statistics instead.
- Law
Is Wash Trading Illegal? The Rules in Equities, Crypto, and NFTs
In regulated futures and equities the answer has been yes since 1936. In crypto and NFTs the answer is: increasingly, and retroactively.
- Case study
LooksRare and Token Incentives: A Natural Experiment in Wash Trading
Pay people per dollar of volume and they will manufacture dollars of volume. What LooksRare taught us about incentive design.
- Explainer
Crypto Wash Trading: How Exchanges Manufactured Their Own Volume
In NFT markets traders faked volume for rewards. On centralised crypto exchanges, the house often faked it for itself.
- Disambiguation
Wash Trading vs Wash Sale: Two Different Things With One Name
One is a manipulation offence, the other a tax rule. Confusing them changes what is illegal, who enforces it, and what it costs you.
- Case studies
Wash Trading Examples: Five Episodes That Show How It Works
From 1920s stock pools to trade-to-earn NFT loops: five concrete episodes, what each manipulator wanted, and how each was caught.
- Explainer
Fake Trading Volume: How to Read Market Numbers Without Being Fooled
Volume is the most quoted and least verified number in markets. A working guide to reading it like an auditor instead of a mark.
- Explainer
NFT Market Manipulation: The Complete Taxonomy
Wash trading is the headline act, but thin NFT markets invite a whole repertoire. A field taxonomy, with the evidence for each move.
- Mechanism design
Trade-to-Earn: Why Paying for Volume Buys You Wash Trading
Every incentive is a price on a behaviour. Trade-to-earn priced the one behaviour a single actor can manufacture without limit.
Publications
Google Scholar ↗The complete authored body of work, newest first within each group.
Research papers
- 2023SSRN Working Paper 4610162 · DOI 10.2139/ssrn.4610162
Cited in the Journal of Banking & Finance, European Journal of Finance, and an NBER working paper.
- 2023SSRN Working Paper 4610086 · DOI 10.2139/ssrn.4610086
Industry reports
- 2025
- 2024
Technical books
- 2020
- 2020
- 2019
- 2019
- 2019
- 2019
- 2019
Advait Jayant researches market microstructure and manipulation in crypto and NFT markets. His solo-authored paper The Economics of Wash Trading (SSRN 4610162) has been cited in the Journal of Banking & Finance, the European Journal of Finance, and an NBER working paper. He is an alumnus of London Business School, where he completed two master’s degrees (an M.Res. in Business and Management Studies and a Master of Analytics and Management) and was enrolled in the PhD programme, and holds a Computer Science degree from BITS Pilani. He works across AI infrastructure, compute markets, and crypto market structure.