CFS working paper series
https://gfk-cfs.de/working-papers/
Refine
Year of publication
Document Type
- Working Paper (696)
Language
- English (696) (remove)
Has Fulltext
- yes (696)
Is part of the Bibliography
- no (696)
Keywords
- Deutschland (46)
- Geldpolitik (43)
- USA (43)
- Europäische Union (26)
- Schätzung (23)
- monetary policy (22)
- Bank (20)
- Monetary Policy (18)
- Haushalt (17)
- Venture Capital (17)
2008, 42
Central counterparties
(2008)
Central counterparties (CCPs) have increasingly become a cornerstone of financial markets infrastructure. We present a model where trades are time-critical, liquidity is limited and there is limited enforcement of trades. We show a CCP novating trades implements efficient trading behaviour. It is optimal for the CCP to face default losses to achieve the efficient level of trade. To cover these losses, the CCP optimally uses margin calls, and, as the default problem becomes more severe, also requires default funds and then imposes position limits.
2008, 41
Algorithmic trading has sharply increased over the past decade. Equity market liquidity has improved as well. Are the two trends related? For a recent five-year panel of New York Stock Exchange (NYSE) stocks, we use a normalized measure of electronic message traffic (order submissions, cancellations, and executions) as a proxy for algorithmic trading, and we trace the associations between liquidity and message traffic. Based on within-stock variation, we find that algorithmic trading and liquidity are positively related. To sort out causality, we use the start of autoquoting on the NYSE as an exogenous instrument for algorithmic trading. Previously, specialists were responsible for manually disseminating the inside quote. As stocks were phased in gradually during early 2003, the manual quote was replaced by a new automated quote whenever there was a change to the NYSE limit order book. This market structure change provides quicker feedback to traders and algorithms and results in more message traffic. For large-cap stocks in particular, quoted and effective spreads narrow under autoquote and adverse selection declines, indicating that algorithmic trading does causally improve liquidity.
2008, 39
We consider a multi-period rational expectations model in which risk-averse investors differ in their information on past transaction prices (the ticker). Some investors (insiders) observe prices in real-time whereas other investors (outsiders) observe prices with a delay. As prices are informative about the asset payoff, insiders get a strictly larger expected utility than outsiders. Yet, information acquisition by one investor exerts a negative externality on other investors. Thus, investors’ average welfare is maximal when access to price information is rationed. We show that a market for price information can implement the fraction of insiders that maximizes investors’ average welfare. This market features a high price to curb excessive acquisition of ticker information. We also show that informational efficiency is greater when the dissemination of ticker information is broader and more timely.
2008, 40
We find and describe four futures markets where the bid-ask spread is bid down to the fixed price tick size practically all the time, and which match counterparties using a pro-rata rule. These four markets´ offered depths at the quotes on average exceed mean market order size by two orders of magnitude, and their order cancellation rates (the probability of any given offered lot being cancelled) are significantly over 96 per cent. We develop a simple theoretical model to ex- plain these facts, where strategic complementarities in the choice of limit order size cause traders to risk overtrading by submitting over-sized limit orders, most of which they expect to cancel.
2008, 53
This paper analyzes liquidity in an order driven market. We only investigate the best limits in the limit order book, but also take into account the book behind these inside prices. When subsequent prices are close to the best ones and depth at them is substantial, larger orders can be executed without an extensive price impact and without deterring liquidity. We develop and estimate several econometric models, based on depth and prices in the book, as well as on the slopes of the limit order book. The dynamics of different dimensions of liquidity are analyzed: prices, depth at and beyond the best prices, as well as resiliency, i.e. how fast the different liquidity measures recover after a liquidity shock. Our results show a somewhat less favorable image of liquidity than often found in the literature. After a liquidity shock (in the spread or depth or in the book beyond the best limits), several dimension of liquidity deteriorate at the same time. Not only does the inside spread increase, and depth at the best prices decrease, also the difference between subsequent bid and ask prices may become larger and depth provided at them decreases. The impacts are both econometrically and economically significant. Also, our findings point to an interaction between different measures of liquidity, between liquidity at the best prices and beyond in the book, and between ask and bid side of the market.
2008, 52
Previous evidence suggests that less liquid stocks entail higher average returns. Using NYSE data, we present evidence that both the sensitivity of returns to liquidity and liquidity premia have significantly declined over the past four decades to levels that we cannot statistically distinguish from zero. Furthermore, the profitability of trading strategies based on buying illiquid stocks and selling illiquid stocks has declined over the past four decades, rendering such strategies virtually unprofitable. Our results are robust to several conventional liquidity measures related to volume. When using liquidity measure that is not related to volume, we find just weak evidence of a liquidity premium even in the early periods of our sample. The gradual introduction and proliferation of index funds and exchange traded funds is a possible explanation for these results.
2008, 50
This paper addresses and resolves the issue of microstructure noise when measuring the relative importance of home and U.S. market in the price discovery process of Canadian interlisted stocks. In order to avoid large bounds for information shares, previous studies applying the Cholesky decomposition within the Hasbrouck (1995) framework had to rely on high frequency data. However, due to the considerable amount of microstructure noise inherent in return data at very high frequencies, these estimators are distorted. We offer a modified approach that identifies unique information shares based on distributional assumptions and thereby enables us to control for microstructure noise. Our results indicate that the role of the U.S. market in the price discovery process of Canadian interlisted stocks has been underestimated so far. Moreover, we suggest that rather than stock specific factors, market characteristics determine information shares.
2008, 49
Innovative automated execution strategies like Algorithmic Trading gain significant market share on electronic market venues worldwide, although their impact on market outcome has not been investigated in depth yet. In order to assess the impact of such concepts, e.g. effects on the price formation or the volatility of prices, a simulation environment is presented that provides stylized implementations of algorithmic trading behavior and allows for modeling latency. As simulations allow for reproducing exactly the same basic situation, an assessment of the impact of algorithmic trading models can be conducted by comparing different simulation runs including and excluding a trader constituting an algorithmic trading model in its trading behavior. By this means the impact of Algorithmic Trading on different characteristics of market outcome can be assessed. The results indicate that large volumes to execute by the algorithmic trader have an increasing impact on market prices. On the other hand, lower latency appears to lower market volatility.
2008, 47
Macro announcements change the equilibrium riskfree rate. We find that treasury prices reflect part of the impact instantaneously, but intermediaries rely on their customer order flow in the 15 minutes after the announcement to discover the full impact. We show that this customer flow informativeness is strongest at times when analyst forecasts of macro variables are highly dispersed. We study 30 year treasury futures to identify the customer flow. We further show that intermediaries appear to benefit from privately recognizing informed customer flow, as, in the cross-section, their own-account trade profitability correlates with access to customer orders, controlling for volatility, competition, and the announcement surprise. These results suggest that intermediaries learn about equilibrium riskfree rates through customer orders.
2008, 48
We report evidence that the presence of hidden liquidity is associated with greater liquidity in the order books, greater trading volume, and smaller price impact. Limit and market order submission behavior changes when hidden liquidity is present consistent with at least some traders being able to detect hidden liquidity. We estimate a model of liquidity provision that allows us to measure variations in the marginal and total payoffs from liquidity provision in states with and without hidden liquidity. Our estimates of the expected surplus to providers of visible and hidden liquidity are positive and typically of the order of one-half to one basis points per trade. The positive liquidity provider surpluses combined with the increased trading volume when hidden liquidity is present are both consistent with liquidity externalities.