# Impact of Stock Market Structure on Intertrade Time and Price Dynamics

**Authors:** Ainslie Yuen, Plamen Ch. Ivanov  
**arXiv:** [physics/0508203](https://arxiv.org/abs/physics/0508203)  
**Date:** 2005-08-28  
**Summary page:** https://www.summarizepaper.com/en/paper/physics--0508203v1/

## Key points

- Study by Ainslie Yuen and Plamen Ch. Ivanov compares NYSE and NASDAQ stock markets
- Focus on debate: stock price behavior from market structure or company-specific characteristics
- Hypothesis: Analyzing intertrade time (ITT) provides insight into internal market mechanism
- Robust scale-invariant temporal organization in ITT independent of company attributes, influenced by market structure
- NASDAQ-listed stocks show stronger correlations in transaction timing within a trading day compared to NYSE-listed stocks
- Link between power-law correlations in ITT and price fluctuations observed
- Higher correlations in absolute price returns and increased price volatility associated with stronger correlations in ITT across time scales
- Heightened correlations in ITT for NASDAQ stocks align with increased correlations in absolute price returns and higher volatility levels
- Market structure may influence price behavior through information embedded within transaction timing patterns

## Summary

In their study titled "Impact of Stock Market Structure on Intertrade Time and Price Dynamics," authors Ainslie Yuen and Plamen Ch. Ivanov delve into the differences between the NYSE and NASDAQ stock markets. They focus on the ongoing debate regarding whether variations in stock price behavior stem from market structure or company-specific characteristics. To address this question, the researchers hypothesize that analyzing the times between consecutive transactions (ITT) for stocks listed on both exchanges may provide a clearer insight into the internal market mechanism compared to external factors like demand and supply. Through their analysis, Yuen and Ivanov uncover a robust scale-invariant temporal organization in ITT that is independent of individual company attributes but influenced by market structure. Notably, they find that NASDAQ-listed stocks display stronger correlations in transaction timing within a trading day when compared to NYSE-listed stocks. This suggests that market structure plays a significant role in influencing transaction patterns. Furthermore, the researchers observe a link between stronger power-law correlations in ITT and corresponding price fluctuations. Higher correlations in absolute price returns and increased price volatility are associated with stronger correlations in ITT across various time scales. This indicates a significant connection between the dynamical properties of ITT and subsequent price movements. Comparing their findings from the NYSE and NASDAQ, Yuen and Ivanov demonstrate that heightened correlations in ITT for NASDAQ stocks align with increased correlations in absolute price returns and higher volatility levels. This implies that market structure may influence price behavior through information embedded within transaction timing patterns. Overall, this research sheds light on how market structure impacts stock price dynamics by examining transaction timing intricacies across different exchanges.