Altcoin alpha research: test the process, not just the backtest
A research workflow for controlling data leakage, selection bias, unrealistic execution, and the temptation to confuse a fitted chart with a durable edge.
A Hedge Lab collection
Research & alpha
Make the strategy explain itself.
An alpha claim needs an economic mechanism, a realistic cost model, and an evidence trail. These articles examine cash-and-carry and backtesting to show how an attractive headline can differ from an implementable strategy.
Begin with carry to distinguish a quoted spread from a net result and dated futures from perpetual funding. Then examine the research workflow to understand point-in-time data, trial history, validation, and execution assumptions. The two guides meet at the same question: would the claimed result survive the conditions the model leaves out?
Market neutrality describes an intended exposure relationship, not immunity from financing, custody, or operational losses. Likewise, historical model performance is not the same as a live track record. This collection emphasizes those distinctions without promoting a trading system. A sound research outcome can be deciding that the evidence is insufficient, that costs remove the apparent edge, or that a simpler approach deserves consideration.
2 guides in this collection
Cash-and-carry in crypto: the risks behind a market-neutral label
Follow a hypothetical spot-and-futures trade from entry to expiry, separating a quoted basis from net return, financing needs, and execution risk.
Start with the risk.
The strategy comes next.
Build your understanding, one useful question at a time.