New Economics Papers
on Market Microstructure
Issue of 2014‒02‒15
four papers chosen by
Thanos Verousis

  1. Rock around the Clock: An Agent-Based Model of Low- and High-Frequency Trading By Sandrine Jacob Leal; Mauro Napoletano; Andrea Roventini; Giorgio Fagiolo
  2. Multi-scale Representation of High Frequency Market Liquidity By Anton Golub; Gregor Chliamovitch; Alexandre Dupuis; Bastien Chopard
  3. A tale of fire-sales and liquidity hoarding By Aleksander Berentsen; Benjamin Müller
  4. Implied Volatility and the Risk-Free Rate of Return in Options Markets By Marcelo Bianconi; Scott MacLachlan; Marco Sammon

  1. By: Sandrine Jacob Leal; Mauro Napoletano; Andrea Roventini; Giorgio Fagiolo
    Abstract: We build an agent-based model to study how the interplay between low- and high- frequency trading affects asset price dynamics. Our main goal is to investigate whether high-frequency trading exacerbates market volatility and generates flash crashes. In the model, low-frequency agents adopt trading rules based on chrono- logical time and can switch between fundamentalist and chartist strategies. On the contrary, high-frequency traders activation is event-driven and depends on price fluctuations. High-frequency traders use directional strategies to exploit market in- formation produced by low-frequency traders. Monte-Carlo simulations reveal that the model replicates the main stylized facts of financial markets. Furthermore, we find that the presence of high-frequency trading increases market volatility and plays a fundamental role in the generation of flash crashes. The emergence of flash crashes is explained by two salient characteristics of high-frequency traders, i.e., their ability to i) generate high bid-ask spreads and ii) synchronize on the sell side of the limit order book. Finally, we find that higher rates of order cancellation by high-frequency traders increase the incidence of flash crashes but reduce their duration.
    Keywords: Agent-based models, Limit order book, High-frequency trading, Low-frequency trading, Flash crashes, Market volatility
    Date: 2014–04–02
  2. By: Anton Golub; Gregor Chliamovitch; Alexandre Dupuis; Bastien Chopard
    Abstract: We introduce an event based framework of directional changes and overshoots to map continuous financial data into the so-called Intrinsic Network - a state based discretisation of intrinsically dissected time series. Defining a method for state contraction of Intrinsic Network, we show that it has a consistent hierarchical structure that allows for multi-scale analysis of financial data. We define an information theoretic measurement termed Liquidity that characterises the unlikeliness of price trajectories and argue that the new metric has the ability to detect and predict stress in financial markets. We show empirical examples within the Foreign Exchange market where the new measure not only quantifies liquidity but also acts as an early warning signal.
    Date: 2014–02
  3. By: Aleksander Berentsen; Benjamin Müller
    Abstract: We extend the analysis of the interbank market model of Gale and Yorulmazer (2013) by studying a larger set of trading mechanisms. A trading mechanism, which allows for randomized trading, restores efficiency. In contrast to Gale and Yorulmazer, we find that fire-sale asset prices are efficient and that no liquidity hoarding occurs in equilibrium. While Gale and Yorulmazer find that the market provides insufficient liquidity, we find that it provides too much liquidity.
    Keywords: Fire-sales, lotteries, liquidity hoarding, interbank markets, indivisibility
    JEL: G12 G21 G33 D83
    Date: 2014–01
  4. By: Marcelo Bianconi; Scott MacLachlan; Marco Sammon
    Abstract: This paper implements an algorithm that can be used to solve systems of Black-Scholes equations for implied volatility and implied risk-free rate of return. After using a seemingly unrelated regressions (SUR) model to obtain point estimates for implied volatility and implied risk-free rate, the options are re-priced using these parameters in the Black-Scholes formula. Given this re-pricing, we find that the difference between the market and model price is increasing in moneyness, and decreasing in time to expiration and the size of the bid ask spread. We ask whether the new information gained by the simultaneous solution is useful. We find that after using the SUR model, and re-pricing the options, the varying risk-free rate model yields Black-Scholes prices closer to market prices than the fixed risk-free rate model. We also find that the varying risk-free rate model is better for predicting future evolutions in model-free implied volatility as measured by the VIX. Finally, we discuss potential trading strategies based both on the model-based Black-Scholes prices and on VIX predictability.
    Keywords: re-pricing options, forecasting volatility, seemingly unrelated regression, implied volatility
    JEL: G13 C63
    Date: 2014

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