When the strategy is a machine-learning model, standard validation lies to you: overlapping labels leak across a naive k-fold split and manufacture a phantom score. Here are the four mechanism-level gates I make any live ML model clear before it touches capital, and the war-story of a model that looked excellent until I purged and embargoed the folds and watched it collapse.
Global Financial Integrity's estimate of Syria's illicit financial outflows over 2000 to 2009 circulates as US$23.6 billion, often with a loss per Syrian attached. The report it is credited to gives two figures rather than one, divides by nobody, and was not yet published on the day the number first appeared.
When your live P&L drifts from the backtest you validated, the culprit is almost never psychology. It is code: the same metric computed two subtly different ways in research and in the live sizing path. Here is the parity oracle I now gate on, and the deeper rule behind it: live and research must call the same code, not two copies of it.
An International Labour Organization factsheet says rebuilding Syria could cost "USD250 to USD 900+ billion". Follow its footnote and the upper figure turns out to be something else: the UN Development Programme's estimate of what the war cost, most of it output that was never produced. Here is the chain, link by link, and what the one number from a full assessment actually measures.
A hypothetical: the Syrian government receives US$25 billion next month. Could its banks hold the money, its offices turn it into projects, its laws carry the contracts and its people build them, and how long would it take? On the record I keep, the answer is not yet, not at that scale and not quickly, with exceptions the record names: multilateral grants, budget support and operators' own capital.
A data-quality gate that crash-loops on corrupt, stale or all-NaN data is not broken, it is working: the alternative is fail open, trading on garbage with silent defaults. Here is the war-story from both sides, the honest flip where an over-eager gate locked me out of a market, and the one portable rule: on bad data, refuse to trade and alert loudly, never proceed with a default that looks like data.
My earlier book on Syria went on sale the week the World Bank published its estimate of what rebuilding the country would cost. My book said US$250 billion to US$400 billion. The Bank said US$216 billion. Here is what my range was missing, what else did not survive being checked, and why the corrections became a second book.
The Financial Times reports that Syria's Sovereign Fund was valued at US$50 billion last year by the finance minister. The figure traces back to an unpublished ministry estimate relayed by an economist, with no date, method or basis. The only asset value the fund's own officials have given in public is about US$2.5 billion, and its deputy director said in August that its assets were still being counted. Set against the economy and the World Bank's capital stock, damage and reconstruction figures, here is what fifty billion would have to mean, and why, without a stated basis, it cannot yet be checked.
A bar carries one timestamp, but that stamp is ambiguous: is a bar labelled 09:00 the open of the coming interval or the close of the last one? Vendors disagree, and reading the wrong edge is a clean one-bar look-ahead that sails through review. Here is the war-story, why the leak is invisible, and the ingest rule I now enforce on every feed.