Impact is not just volatility

Bucci, Frédéric; Mastromatteo, Iacopo; Benzaquen, Michael; Bouchaud, Jean‐Philippe

doi:10.1080/14697688.2019.1622768

Cited by 11 publications

(8 citation statements)

References 26 publications

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“…15 indicates that, by controlling for both T and η, market impact is mainly dependent on √ T η = √ φ. Third, as shown explicitly in (Bucci et al, 2019b), market impact curves of metaorders with φ 5 • 10 −4 (roughly 80% of those in the ANcerno database) are independent on T and consistent with a square root dependence on φ. Once more, impact of the remaining small metaorders are better described by a linear relation.…”

Section: Market Impact Of Metaorderssupporting

confidence: 60%

“…Once more, impact of the remaining small metaorders are better described by a linear relation. (Bucci et al, 2019b) also shows that the variance of impact depends linearly on T , as expected by the diffusivity of price, and this price uncertainty largely exceeds the average reaction impact contribution (which in turn explains why the R 2 in the market impact estimation is typically very small).…”

Section: Market Impact Of Metaordersmentioning

confidence: 82%

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Order flow and price formation

Lillo¹

2021

Preprint

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I present an overview of some recent advancements on the empirical analysis and theoretical modeling of the process of price formation in financial markets as the result of the arrival of orders in a limit order book exchange. After discussing critically the possible modeling approaches and the observed stylized facts of order flow, I consider in detail market impact and transaction cost of trades executed incrementally over an extended period of time, by comparing model predictions and recent extensive empirical results. I also discuss how the simultaneous presence of many algorithmic trading executions affects the quality and cost of trading.

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Section: Market Impact Of Metaorderssupporting

confidence: 60%

Section: Market Impact Of Metaordersmentioning

confidence: 82%

Order flow and price formation

Lillo¹

2021

Preprint

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“…We would therefore expect to see a transition from the linear to the square-root regime to occur for some point smaller than ∆x. Indeed, this transition point is seen in the data and occurs for an imbalance of around .01 although it varies depending on the duration of the order (Bucci et al, 2019).…”

Section: Volatility and Price Impactmentioning

confidence: 81%

A Quantum Oscillator Model of Stock Markets

Orrell

2024

Quantum Economics and Finance

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Classical oscillators have long been used to model financial time series, but suffer from the drawback that the underlying system does not behave like a mechanical spring: there are no regular oscillations, and price is not a well-defined mechanical quantity but always has a degree of uncertainty. In recent years a number of authors have attempted to address these problems by basing their models on quantum harmonic oscillators, which always have a non-zero volatility, however the role of other features that are characteristic of quantum systems, such as discrete energy levels, has not been clear. This paper develops a quantum model in which the energy level corresponds to an integer number of transactions. The model is derived by quantizing entropic forces which represent the intentions of buyers and sellers to transact as a function of price. It is shown that the model captures the non-Gaussian nature of financial statistics, and correctly predicts empirical phenomena including the square-root law of price impact, along with its associated variance.

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“…Finally, Tóth et al [37] proposed an alternative theory based on a dynamical description of supply and demand, called the Latent Liquidity Theory (LLT). This approach, developed further in several papers [38][39][40][41][42][43][44], provides a natural statistical interpretation for the square-root law and its apparent universality. It also makes further predictions, in particular concerning the decay of impact once the metaorder has been executed [40,42].…”

Section: The Latent Liquidity Theorymentioning

confidence: 99%

The Inelastic Market Hypothesis: A Microstructural Interpretation

Bouchaud¹

2021

Preprint

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We attempt to reconcile Gabaix and Koijen's (GK) recent Inelastic Market Hypothesis with the orderdriven view of markets that emerged within the microstructure literature in the past 20 years. We review the most salient empirical facts and arguments that give credence to the idea that market price fluctuations are mostly due to order flow, whether informed or non-informed. We show that the Latent Liquidity Theory of price impact makes a precise prediction for GK's multiplier M , which measures by how many dollars, on average, the market value of a company goes up if one buys one dollar worth of its stocks. Our central result is that M is of order unity, as found by GK, and increases with the volatility of the stock and decreases with the fraction of the market cap. that is traded daily. We discuss several empirical results suggesting that the lion's share of volatility is due to trading activity.

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Impact is not just volatility

Cited by 11 publications

References 26 publications

Order flow and price formation

Order flow and price formation

A Quantum Oscillator Model of Stock Markets

The Inelastic Market Hypothesis: A Microstructural Interpretation

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