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on Market Microstructure |
By: | Schlepper, Kathi; Riordan, Ryan; Hofer, Heiko; Schrimpf, Andreas |
Abstract: | This paper investigates the scarcity effects of quantitative easing (QE) policies, drawing on intra-day transaction-level data for German government bonds, purchased under the Public Sector Purchase Program (PSPP) of the ECB/Eurosystem. This paper is the first to match high-frequency QE purchase data with high-frequency inter-dealer data. We find economically significant price impacts at high (minute-by-minute) and low (daily) frequencies, highlighting the relevance of scarcity effects in bond markets. Asset purchase policies are not without side effects, though, as the induced scarcity has an adverse impact on liquidity conditions as measured by bid-ask spreads and inter-dealer order book depth. We further show that the price impact varies greatly with market conditions: it is considerably higher during episodes of illiquidity and when yields are higher. |
Keywords: | Quantitative Easing,European Central Bank,Scarcity Channel,Bond Market Liquidity,High-Frequency Data |
JEL: | E52 E63 G11 G12 H63 |
Date: | 2017 |
URL: | http://d.repec.org/n?u=RePEc:zbw:bubdps:062017&r=mst |
By: | Fr\'ed\'eric Abergel (MICS); C\^ome Hur\'e (LPMA); Huy\^en Pham (CREST, LPMA) |
Abstract: | We propose a microstructural modeling framework for studying optimal market making policies in a FIFO (first in first out) limit order book (LOB). In this context, the limit orders, market orders, and cancel orders arrivals in the LOB are modeled as Cox point processes with intensities that only depend on the state of the LOB. These are high-dimensional models which are realistic from a micro-structure point of view and have been recently developed in the literature. In this context, we consider a market maker who stands ready to buy and sell stock on a regular and continuous basis at a publicly quoted price, and identifies the strategies that maximize her P\&L penalized by her inventory. We apply the theory of Markov Decision Processes and dynamic programming method to characterize analytically the solutions to our optimal market making problem. The second part of the paper deals with the numerical aspect of the high-dimensional trading problem. We use a control randomization method combined with quantization method to compute the optimal strategies. Several computational tests are performed on simulated data to illustrate the efficiency of the computed optimal strategy. In particular, we simulated an order book with constant/ symmet-ric/ asymmetrical/ state dependent intensities, and compared the computed optimal strategy with naive strategies. |
Date: | 2017–05 |
URL: | http://d.repec.org/n?u=RePEc:arx:papers:1705.01446&r=mst |
By: | Jakree Koosakul; Ilhyock Shim |
Abstract: | A substantial body of existing research suggests that asset price volatility is harmful to market liquidity. This paper explores a contrarian view that, by creating opportunities for profit making, exchange rate volatility can be beneficial to trading activity. Utilising granular data from the Thai foreign exchange (FX) market from January 2010 to March 2016, we find that the volatility of the US dollar-Thai baht exchange rate has significant positive effects on trading volume in the spot market, except at very high levels of volatility. We also observe significant heterogeneity in such effects across different types of market participant. In particular, FX volatility has positive effects on the FX trading activity of foreign and interbank players, but it negatively affects that of local players. These results are robust when we control for potential confounding variables, such as information arrivals, that can generate a positive but non-causal co-movement between volatility and volume. |
Keywords: | asset price volatility, foreign exchange market, investor type, market liquidity, nonlinear effect |
Date: | 2017–04 |
URL: | http://d.repec.org/n?u=RePEc:bis:biswps:629&r=mst |
By: | Azi Ben-Rephael; Bruce I. Carlin; Zhi Da; Ryan D. Israelsen |
Abstract: | Previously, academics have used the supply of information that arrives to market (e.g., macroeconomic announcements, earnings reports, or news releases) to study how information affects asset prices and anomalies, and for tests of market efficiency. In this paper, we instead use measures of institutional and retail demand for information. We show that institutional demand for information is associated with increased trading volume and significant price movements. Average returns and betas are higher on days with higher institutional demand for information. The magnitude of these effects is much larger than those associated with the supply of news. However, the impact of demand for information from retail investors, while statistically significant, is quite small in magnitude. We also show that higher institutional demand alleviates mispricing in the market. In particular, higher information processing by institutional investors dampens momentum and enhances long-term reversals. As such, when demand for information increases, the market becomes more efficient. |
JEL: | G12 G14 |
Date: | 2017–03 |
URL: | http://d.repec.org/n?u=RePEc:nbr:nberwo:23274&r=mst |
By: | Jacob Gyntelberg; Peter Hördahl; Kristyna Ters; Jörg Urban |
Abstract: | We find evidence that in the market for euro area sovereign credit risk, arbitrageurs engage in basis trades between credit default swap (CDS) and bond markets only when the CDS-bond basis exceeds a certain threshold. This threshold effect is likely to reflect costs that arbitrageurs face when implementing trading strategies, including transaction costs and costs associated with committing balance sheet space for such trades. Using a threshold vector error correction model, we endogenously estimate these unknown trading costs for basis trades in the market for euro area sovereign debt. During the euro sovereign credit crisis, we find very high transaction costs of around 190 basis points, compared to around 80 basis points before the crisis. Our results show, that even when markets in times of stress are liquid, the basis can widen as high market volatility makes arbitrage trades riskier, leading arbitrageurs to demand a higher compensation for increased risk. Our findings help explain the persistent non-zero CDS-bond basis in euro area sovereign debt markets and its increase during the last sovereign crisis. |
Keywords: | sovereign credit risk, credit default swaps, price discovery, regime switch, intraday, arbitrage, transaction costs |
Date: | 2017–04 |
URL: | http://d.repec.org/n?u=RePEc:bis:biswps:631&r=mst |
By: | Senarathne, Chamil W; Jayasinghe, Prabhath |
Abstract: | The Heteroskedastic Mixture Model (HMM) of Lamoureux, and Lastrapes (1990) is extended, relaxing the restriction imposed on the mean i.e. μt-1=0 . Instead, an exogenous variable rm, along with its vector βm, that predicts return rt is introduced to examine the hypothesis that the volume is a measure of speed of evolution in the price change process in capital asset pricing. The empirical findings are documented for the hypothesis that ARCH is a manifestation of time dependence in the rate of information arrival, in line with the observations of Lamoureux, and Lastrapes (1990). The linkage between this time dependence and the expectations of market participants is investigated and the symmetric behavioural response is documented. Accordingly, the tendency of revision of expectation in the presence of new information flow whose frequency as measured by ‘volume clock’ is observed. In the absence of new information arrival at the market, investors tend to follow the market on average. When new information is available, the expectations of investors are revised in the same direction as a symmetric response to the flow of new information arrival at the market. |
Keywords: | Mixture of Distribution Hypothesis; Information Flow; Stock Volume; Systematic Risk; Capital Asset Pricing; ARCH; GARCH |
JEL: | C01 C58 D53 G12 G14 G17 |
Date: | 2017–03 |
URL: | http://d.repec.org/n?u=RePEc:pra:mprapa:78771&r=mst |