The hottest Performance analysis Substack posts right now

And their main takeaways
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Why Do Olympic Hosts Win More Medals?

Cremieux Recueil • 301 implied HN points • 18 Feb 26
🎾 Sports Performance analysis
  1. Hosts win more medals mainly because they can enter many more athletes, so sheer numbers produce more podiums even if each athlete is on average weaker.
  2. After controlling for delegation size, hosts still earn extra golds in judged sports, implying judges favor home athletes; that judged-sport boost appears even when there are no home crowds.
  3. Common explanations like wealth, population, distance, climate, jet lag, neighbor spillovers, or adding events don’t explain the effect, and smaller countries gain proportionally more because their delegation size jumps bigger when they host.

Groq Inference Tokenomics: Speed, But At What Cost?

SemiAnalysis • 10708 implied HN points • 21 Feb 24
🕹 Technology Performance analysis
  1. Groq AI hardware showcases impressive speed and cost efficiency, outperforming other inference services while charging less.
  2. While speed is vital, supply chain diversification plays a significant role in evaluating hardware's revolutionary potential.
  3. Understanding the total cost of ownership is crucial in deploying AI software, with significant impacts from chip microarchitecture and system architecture.

How bad is it at Man Utd?

Grace on Football • 766 implied HN points • 23 Sep 23
🎾 Sports Performance analysis
  1. Manchester United's managerial structure needs clarity and definition for success
  2. Erik ten Hag emphasizes coaching and player training in the Dutch football manager tradition
  3. United's performance needs improvement for a chance at a successful season
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Turnaround Tuesdays on Steroids

Quant Trading Rules • 79 implied HN points • 26 May 24
💰 Finance Performance analysis
  1. The Turnaround Tuesdays trading strategy is based on stocks rebounding on Tuesdays after a down Monday, with simple entry and exit rules tested over 31 years.
  2. Expanding the strategy to include Tuesdays and Wednesdays improved results, increasing annual returns and win rates while maintaining high simplicity.
  3. Utilizing leverage by applying the strategy to a leveraged ETF like TQQQ can significantly boost annual returns, although it may lead to more frequent and deeper drawdowns.

Better Descriptive Statistics for Low-Latency Profiling

Low Latency Trading Insights • 137 implied HN points • 06 Feb 24
🕹 Technology Performance analysis
  1. Better descriptive statistics are needed for low-latency profiling to accurately capture rare events and spikes.
  2. Descriptive statistics like mean, median, skewness, and kurtosis may be misleading in non-normally distributed data.
  3. Self-adjusting histograms with log-based ranges can provide more accurate data representation and efficient storage.

ChatGPT can predict analyst forecast changes

Klement on Investing • 4 implied HN points • 19 Nov 24
💰 Finance Performance analysis
  1. ChatGPT can analyze earnings calls and predict how analysts will change their forecasts. This means it can assess important company factors like growth and risk.
  2. The Analyst Insight Score (AIS) created from ChatGPT's analysis is better at predicting analyst actions and stock prices than traditional methods. It's about two to four times more effective.
  3. There's concern that as AI like ChatGPT improves in its analysis, it might replace human jobs in finance. This includes roles like equity analysts and fund managers.

Past performance is indicative of future results

Klement on Investing • 3 implied HN points • 04 Dec 24
💰 Finance Performance analysis
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How is LLaMa.cpp possible?

Artificial Fintelligence • 4 HN points • 16 Mar 23
🕹 Technology Performance analysis
  1. Large deep learning models like LLaMa can run locally on a variety of hardware with optimizations and weight quantization.
  2. Memory bandwidth is crucial for deep learning GPUs, with memory being the bottleneck for inference performance.
  3. Quantization can significantly reduce memory requirements for models, making them more manageable to serve, especially on GPUs.