nep-mst New Economics Papers
on Market Microstructure
Issue of 2015‒12‒20
six papers chosen by
Thanos Verousis

  1. Queue Imbalance as a One-Tick-Ahead Price Predictor in a Limit Order Book By Martin D. Gould; Julius Bonart
  2. Cross-sectional dependence in idiosyncratic volatility By KALNINA, Ilze; TEWOU, Kokouvi
  3. Carry Trades, Order Flow and the Forward Bias Puzzle By Francis Breedon; Dagfinn Rime; Paolo Vitale
  4. Illiquidity in the stock and FX markets: an investigation of their cross-market dynamics By Banti, Chiara
  5. Machine Learning for Semi-Strong Efficiency Test of Inter-Market Wheat Futures By Phélippé-Guinvarc'h, Martial; Cordier, Jean
  6. Do investors trade too much? A laboratory experiment By Joao da Gama Batista; Domenico Massaro; Jean-Philippe Bouchaud; Damien Challet; Cars Hommes

  1. By: Martin D. Gould; Julius Bonart
    Abstract: We investigate whether the bid/ask queue imbalance in a limit order book (LOB) provides significant predictive power for the direction of the next mid-price movement. We consider this question both in the context of a simple binary classifier, which seeks to predict the direction of the next mid-price movement, and a probabilistic classifier, which seeks to predict the probability that the next mid-price movement will be upwards. To implement these classifiers, we fit logistic regressions between the queue imbalance and the direction of the subsequent mid-price movement for each of 10 liquid stocks on Nasdaq. In each case, we find a strongly statistically significant relationship between these variables. Compared to a simple null model, which assumes that the direction of mid-price changes is uncorrelated with the queue imbalance, we find that our logistic regression fits provide a considerable improvement in binary and probabilistic classification for large-tick stocks, and provide a moderate improvement in binary and probabilistic classification for small-tick stocks. We also perform local logistic regression fits on the same data, and find that this semi-parametric approach slightly outperform our logistic regression fits, at the expense of being more computationally intensive to implement.
    Date: 2015–12
  2. By: KALNINA, Ilze; TEWOU, Kokouvi
    Abstract: This paper introduces a framework for analysis of cross-sectional dependence in the idiosyncratic volatilities of assets using high frequency data. We first consider the estimation of standard measures of dependence in the idiosyncratic volatilities such as covariances and correlations. Next, we study an idiosyncratic volatility factor model, in which we decompose the co-movements in idiosyncratic volatilities into two parts: those related to factors such as the market volatility, and the residual co-movements. When using high frequency data, naive estimators of all of the above measures are biased due to the estimation errors in idiosyncratic volatility. We provide bias-corrected estimators and establish their asymptotic properties. We apply our estimators to high-frequency data on 27 individual stocks from nine different sectors, and document strong cross-sectional dependence in their idiosyncratic volatilities. We also find that on average 74% of this dependence can be explained by the market volatility.
    Keywords: High frenquency data; Idiosyncratic volatility; Factor structure; Cross-sectional returns
    JEL: C22 C14
    Date: 2015
  3. By: Francis Breedon (Queen Mary University of London); Dagfinn Rime (BI Norwegian Business School); Paolo Vitale (Università Gabriele d'Annunzio)
    Abstract: We investigate the relation between foreign exchange (FX) order flow and the forward bias. We outline a decomposition of the forward bias according to which a negative correlation between interest rate differentials and order flow creates a time-varying risk premium consistent with that bias. Using ten years of data on FX order flow we find that more than half of the forward bias is accounted for by order flow -- with the rest being explained by expectational errors. We also find that carry trading increases currency-crash risk in that order flow generates negative skewness in FX returns.
    Keywords: Forward premium puzzle, FX microstructure, Carry trade, Survey data
    JEL: F31 G14 G15
    Date: 2015–12
  4. By: Banti, Chiara
    Abstract: In this paper, I investigate the illiquidity channel linking the stock and FX markets.The evidence of co-movement and cross-market spillovers is supportive of important dynamics in illiquidity, especially during the recent crisis. To clarify the nature of these dynamics, I consider the role of two important players on both markets, institutional investors and dealers. Overall, correlated institutional trading contributes to liquidity across markets. Furthermore, as funding availability reduces in times of crisis, dealers' funding constraints affect the observed dynamics. Finally, both correlated institutional trading and dealers' funding constraints are potential triggers of systemic illiquidity spirals.
    Date: 2015
  5. By: Phélippé-Guinvarc'h, Martial; Cordier, Jean
    Abstract: This paper proposes an original work on world wheat futures market efficiency test to conclude on the semi-strong inefficiency of wheat futures. Our model uses american and european data together to estimate pair trading arbitrage returns on the wheat futures market. Some variables like transportation and balance sheet of USDA are significative in CART regression. Then, pair trading arbitrage is predictible with public information and we deduce of the semi-strong inefficiency of inter-market wheat futures.
    Keywords: semi-strong efficiency, agricultural commodities
    JEL: G14 Q11 Q14
    Date: 2015–06–01
  6. By: Joao da Gama Batista; Domenico Massaro; Jean-Philippe Bouchaud; Damien Challet; Cars Hommes
    Abstract: We run experimental asset markets to investigate the emergence of excess trading and the occurrence of synchronised trading activity leading to crashes in the artificial markets. The market environment favours early investment in the risky asset and no posterior trading, i.e. a buy-and-hold strategy with a most probable return of over 600%. We observe that subjects trade too much, and due to the market impact that we explicitly implement, this is detrimental to their wealth. The asset market experiment was followed by risk aversion measurement. We find that preference for risk systematically leads to higher activity rates (and lower final wealth). We also measure subjects' expectations of future prices and find that their actions are fully consistent with their expectations. In particular, trading subjects try to beat the market and make profits by playing a buy low, sell high strategy. Finally, we have not detected any major market crash driven by collective panic modes, but rather a weaker but significant tendency of traders to synchronise their entry and exit points in the market.
    Date: 2015–12

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