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on Market Microstructure |
| By: | Claudia Foroni (Norges Bank); Pierre Guérin (Bank of Canada); Massimiliano Marcellino (Bocconi University, IGIER and CEPR) |
| Abstract: | We analyze how to incorporate low frequency information in models for predicting high frequency variables. In doing so, we introduce a new model, the reverse unrestricted MIDAS (RU-MIDAS), which has a periodic structure but can be estimated by simple least squares methods and used to produce forecasts of high frequency variables that also incorporate low frequency information. We compare this model with two versions of the mixed frequency VAR, which so far had been only applied to study the reverse problem, that is, using the high frequency information for predicting low frequency variables. We then implement a simulation study to evaluate the relative forecasting ability of the alternative models in finite samples. Finally, we conduct several empirical applications to assess the relevance of quarterly survey data for forecasting a set of monthly macroeconomic indicators. Overall, it turns out that low frequency information is important, particularly so when it is just released. |
| Keywords: | Mixed-Frequency VAR models, temporal aggregation, MIDAS models |
| JEL: | E37 C53 |
| Date: | 2015–10–29 |
| URL: | http://d.repec.org/n?u=RePEc:bno:worpap:2015_13&r=mst |
| By: | Ahmet Sensoy |
| Abstract: | After the recent nancial crisis, few issues receive more attention than central banks' actions or major macroeconomic announcements in markets. Motivated by this fact, we investigate the impact of specic macro-announcements on liquidity commonal-ity in Turkey. Using a weighted spread constructed by a proprietary database of order ows, we reveal that among several developed countries, only U.S. monetarypolicy and macroeconomic announcements raise commonality in liquidity. More-over, commonality is signicantly aected (increased) only beyond the best price quotes, showing that researchers may obtain misleading results on commonality if they consider spread at the best price levels as a liquidity proxy. |
| Keywords: | Commonality in liquidity, order book, monetary policy, macroeconomic announcements, market microstructure |
| JEL: | D23 D82 G11 G12 |
| Date: | 2015–10 |
| URL: | http://d.repec.org/n?u=RePEc:bor:wpaper:1529&r=mst |
| By: | Lim, Kian-Ping; Thian, Tze-Chung; Hooy, Chee-Wooi |
| Abstract: | This paper examines the relationship between shareholdings of various investor groups and stock liquidity for Malaysian public listed firms over the 2002-2009 sample period. Using the Amihud illiquidity ratio, we extend the literature by addressing the issues of investor heterogeneity, trading account types and the interactions of competing liquidity channels. The analysis reveals that only local institutions and local individual investors who trade through the direct accounts are significantly associated with the liquidity of domestic firms. In contrast, the significant liquidity effect for foreign investors operates through the nominee accounts. While institutional ownership exhibits a linear negative relationship, our findings on local individuals and foreign nominees differ greatly from previous studies in that their relationship with stock liquidity is non-monotonic. Apart from the widely researched information asymmetry and trading effects, we find that liquidity is also driven by the largely ignored information competition channel. An important insight from our findings is that the large shareholdings by any particular investor group is detrimental to stock liquidity as they exacerbate information asymmetry, reduce the degree of competition and lower the level of trading activity. |
| Keywords: | Investor groups; Stock liquidity; Information asymmetry; Information competition; Trading; Malaysia |
| JEL: | G12 G32 |
| Date: | 2015–07–25 |
| URL: | http://d.repec.org/n?u=RePEc:pra:mprapa:67602&r=mst |
| By: | Enrique Mart\'inez-Miranda; Peter McBurney; Matthew J. Howard |
| Abstract: | Market manipulation is a strategy used by traders to alter the price of financial securities. One type of manipulation is based on the process of buying or selling assets by using several trading strategies, among them spoofing is a popular strategy and is considered illegal by market regulators. Some promising tools have been developed to detect manipulation, but cases can still be found in the markets. In this paper we model spoofing and pinging trading, two strategies that differ in the legal background but share the same elemental concept of market manipulation. We use a reinforcement learning framework within the full and partial observability of Markov decision processes and analyse the underlying behaviour of the manipulators by finding the causes of what encourages the traders to perform fraudulent activities. This reveals procedures to counter the problem that may be helpful to market regulators as our model predicts the activity of spoofers. |
| Date: | 2015–11 |
| URL: | http://d.repec.org/n?u=RePEc:arx:papers:1511.00740&r=mst |