Bibliographic record
Abstract
This paper extends the Efficient Markets Hypothesis (EMH) into a novel setting in which traders can travel back in time to exploit future information. We consider a fully specified trading model with risk-neutral, rational investors and a single, infinitely-lived asset. Agents can, at a fixed cost, build time machines, travel to the past, and trade using knowledge of future dividends and prices. Under a self-consistent, single-timeline theory of time travel, we show that no arbitrage opportunities can persist. In equilibrium, the asset price fully reflects not only all current and past information but also all future information that could have been acted upon by backward-travelling arbitrageurs. We state and prove an Extended Efficient Markets Hypothesis (EEMH), showing that time travel does not undermine but rather reinforces the no-arbitrage conditions at the heart of the EMH. We conclude by discussing the relevance of known constraints on the EMH, alternative theories of time travel and the challenges of empirically identifying time-travelling traders. Journal of Economic Literature Codes: G14, Z10. • Shows that time travel does not undermine the Efficient Markets Hypothesis (EMH) but rather reinforces, as any arbitrage opportunities would have already been exploited and eliminated. • Develops a formal trading model where agents can build time machines at fixed cost to exploit future information. • Shows prices reflect all information – past, present and future – that could ever be used for arbitrage. • Demonstrates how self-consistency constraints and rational expectations ensure market efficiency. • Argues that evidence of time travel cannot be found in financial data since time travellers’ actions would be indistinguishable from normal price movements in an efficient market.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.001 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; both teacher heads agree on what is shown here.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".