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on Market Microstructure |
| By: | Sohaib El Karmi |
| Abstract: | We present a reproducible research framework for market microstructure combining a deterministic C++ limit order book (LOB) simulator with stochastic order flow generated by multivariate marked Hawkes processes. The paper derives full stability and ergodicity proofs for both linear and nonlinear Hawkes models, implements time-rescaling and goodness-of-fit diagnostics, and calibrates exponential and power-law kernels on Binance BTCUSDT and LOBSTER AAPL datasets. Empirical results highlight the nearly-unstable subcritical regime as essential for reproducing realistic clustering in order flow. All code, datasets, and configuration files are publicly available at https://github.com/sohaibelkarmi/High-Fr equency-Trading-Simulator |
| Date: | 2025–10 |
| URL: | https://d.repec.org/n?u=RePEc:arx:papers:2510.08085 |
| By: | Barrow, Daisy (University of Warwick) |
| Abstract: | This study investigates the relationship between market liquidity and herding behaviour in European equity markets between 2021 to 2023. While the existing literature has predominantly focused on market volatility and crisis-driven herding, the role of liquidity remains under-explored. Understanding this gap is crucial given the implications of herding for market efficiency. Using exchange-level panel data on midand large-cap firms, this study applies the Cross-Sectional Absolute Deviation (CSAD) methodology of Chang et al. (2000) to detect herding and extends the Carhart (1997) four-factor model to isolate the component of CSAD unexplained by fundamental market characteristics. Liquidity is proxied through both market breadth, via volume and turnover measures, and market depth, via a transformed Amihud (2002) ratio, allowing for a distinction between different liquidity attributes. The results reveal asymmetries, but generally suggest that breadth-based liquidity facilitates herding, supporting the idea that higher market participation amplifies signals to imitate. In contrast, depth-based liquidity appears to discourage herding, suggesting that lower transaction costs enable investors to act more independently. These findings highlight the importance of distinguishing between liquidity characteristics and demonstrate the complex and sensitive role of liquidity conditions in shaping investor behaviour. |
| Keywords: | Market Efficiency ; Liquidity ; Information Cascades ; Investor Behaviour JEL classifications: G40 ; G11 ; G12 |
| Date: | 2025 |
| URL: | https://d.repec.org/n?u=RePEc:wrk:wrkesp:92 |
| By: | Shuto Endo; Takanobu Mizuta; Isao Yagi |
| Abstract: | Order book imbalance (OBI) - buy orders minus sell orders near the best quote - measures supply-demand imbalance that can move prices. OBI is positively correlated with returns, and some investors try to use it to improve performance. Large orders placed at once can reveal intent, invite front-running, raise volatility, and cause losses. Execution algorithms therefore split parent orders into smaller lots to limit price distortion. In principle, using OBI inside such algorithms could improve execution, but prior evidence is scarce because isolating OBI's effect in real markets is nearly impossible amid many external factors. Multi-agent simulation offers a way to study this. In an artificial market, individual actors are agents whose rules and interactions form the model. This study builds an execution algorithm that accounts for OBI, tests it across several market patterns in artificial markets, and analyzes mechanisms, comparing it with a conventional (OBI-agnostic) algorithm. Results: (i) In stable markets, the OBI strategy's performance depends on the number of order slices; outcomes vary with how the parent order is partitioned. (ii) In markets with unstable prices, the OBI-based algorithm outperforms the conventional approach. (iii) Under spoofing manipulation, the OBI strategy is not significantly worse than the conventional algorithm, indicating limited vulnerability to spoofing. Overall, OBI provides a useful signal for execution. Incorporating OBI can add value - especially in volatile conditions - while remaining reasonably robust to spoofing; in calm markets, benefits are sensitive to slicing design. |
| Date: | 2025–09 |
| URL: | https://d.repec.org/n?u=RePEc:arx:papers:2509.16912 |
| By: | Qingyuan Han |
| Abstract: | Equity markets have long been regarded as unpredictable, with intraday price movements treated as stochastic noise. This study challenges that view by introducing the Extended Samuelson Model (ESM), a natural science-based framework that captures the dynamic, causal processes underlying market behavior. ESM identifies peaks, troughs, and turning points across multiple timescales and demonstrates temporal compatibility: finer timeframes contain all signals of broader ones while offering sharper directional guidance. Beyond theory, ESM translates into practical trading strategies. During intraday sessions, it reliably anticipates short-term reversals and longer-term trends, even under the influence of breaking news. Its eight market states and six directional signals provide actionable guardrails for traders, enabling consistent profit opportunities. Notably, even during calm periods, ESM can capture 10-point swings in the S&P 500, equivalent to $500 per E-mini futures contract. These findings resonate with the state-based approaches attributed to Renaissance Technologies' Medallion Fund, which delivered extraordinary returns through systematic intraday trading. By bridging normal conditions with crisis dynamics, ESM not only advances the scientific understanding of market evolution but also provides a robust, actionable roadmap for profitable trading. |
| Date: | 2025–10 |
| URL: | https://d.repec.org/n?u=RePEc:arx:papers:2510.01542 |
| By: | Althea Sterrett; Austin Adams |
| Abstract: | The programmable and composable nature of smart contract protocols has enabled the emergence of novel market structures and asset classes that are architecturally frictional to implement in traditional financial paradigms. This fluidity has produced an understudied class of market dynamics, particularly in coupled markets where one market serves as an oracle for the other. In such market structures, purchases or liquidations through the intermediate asset create coupled price action between the intermediate and final assets; leading to basket inflation or deflation when denominated in the riskless asset. This paper examines the microstructure of this inflationary dynamic given two constant function market makers (CFMMs) as the intermediate market structures; attempting to quantify their contributions to the former relative to familiar pool metrics such as price drift, trade size, and market depth. Further, a concrete case study is developed, where both markets are constant product markets. The intention is to shed light on the market design process within such coupled environments. |
| Date: | 2025–10 |
| URL: | https://d.repec.org/n?u=RePEc:arx:papers:2510.06095 |