Alpha in Academia

Academic finance research for market professionals. Papers, assumptions, frictions, robustness, and failure modes. 9,000+ subscribers →

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Financial Twitter is full of confident market takes.

Academic finance is full of tested claims most investors never read.

Alpha in Academia exists to close that gap.

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Full implementation with code in the paid deep dive: https://t.co/Tacgqkbp89

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VWAP execution runs on a volume forecast, and the usual benchmark forecast is a historical average.

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SPAR, which learns each ticker's periodic volume structure, cut average tracking error to 4.33bp, versus 7.19bp for the historical baseline and 9.41bp for a Kalman filter. Better on all 10 tickers tested, with the biggest gains where volume is most back-loaded (INTC, AMD).

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Paper link in our May 30 Recent Academic Research, below: https://t.co/2BzJ43KQCD

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Hourly ML models on Bitcoin print money in backtests and lose it to transaction costs.

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One added filter, dropping low-conviction forecasts to cut turnover, pushed the top configuration above 65% annualized net of costs. XGBoost was harder to beat than the neural nets.

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The complete tests, code included, are in the paid deep dive: https://t.co/qjpFDEziZV

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On Kalshi, "CPI above 3.0%" at 40c and "above 3.5%" at 22c means an 18% chance it lands between. Stack every threshold and you have a daily-updating forecast distribution for inflation, unemployment, and the Fed.

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Caveat: the probabilities are risk-neutral, and inflation tails run rich because hedgers buy them.

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Our June 6 roundup has the details and the paper link, below: https://t.co/JTD7ULqpuJ

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A portfolio running 15% volatility loses 1.125% a year to volatility drag, the gap between average and compounded returns.

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A recent paper's rule-based borrowing policy, applied after drawdowns, recovered close to 100% of that drag in 30-year simulations, even at 9% borrowing costs, as long as leverage stays inside the rule's boundary.

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Paper link in our June 6 Recent Academic Research, below: https://t.co/JTD7ULqpuJ

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Bond market makers grade themselves on hit ratio: the share of client requests won. Winning informed flow costs more than winning a retail rebalance, and the raw metric treats them the same.

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A recent paper strips credit factors, carry, and index trends from post-trade performance to score clients on residual quality. Quotes tighten for benign flow, widen for toxic, and the service mandate survives.

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Full notes and the paper link in the May 30 edition, below: https://t.co/2BzJ43KQCD

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Bad news sticks. In decades of WSJ archives, negative sentiment decays far more slowly than positive sentiment of the same magnitude.

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Aggregate sentiment indices mask the whole effect.