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Institute
- Center for Financial Studies (CFS) (39) (remove)
We model the dynamics of ask and bid curves in a limit order book market using a dynamic semiparametric factor model. The shape of the curves is captured by a factor structure which is estimated nonparametrically. Corresponding factor loadings are assumed to follow multivariate dynamics and are modelled using a vector autoregressive model. Applying the framework to four stocks traded at the Australian Stock Exchange (ASX) in 2002, we show that the suggested model captures the spatial and temporal dependencies of the limit order book. Relating the shape of the curves to variables reflecting the current state of the market, we show that the recent liquidity demand has the strongest impact. In an extensive forecasting analysis we show that the model is successful in forecasting the liquidity supply over various time horizons during a trading day. Moreover, it is shown that the model’s forecasting power can be used to improve optimal order execution strategies.
Analyzing interest rate risk: stochastic volatility in the term structure of government bond yields
(2009)
We propose a Nelson-Siegel type interest rate term structure model where the underlying yield factors follow autoregressive processes with stochastic volatility. The factor volatilities parsimoniously capture risk inherent to the term structure and are associated with the time-varying uncertainty of the yield curve’s level, slope and curvature. Estimating the model based on U.S. government bond yields applying Markov chain Monte Carlo techniques we find that the factor volatilities follow highly persistent processes. We show that slope and curvature risk have explanatory power for bond excess returns and illustrate that the yield and volatility factors are closely related to industrial capacity utilization, inflation, monetary policy and employment growth. JEL Classification: C5, E4, G1
Despite their importance in modern electronic trading, virtually no systematic empirical evidence on the market impact of incoming orders is existing. We quantify the short-run and long-run price effect of posting a limit order by proposing a high-frequency cointegrated VAR model for ask and bid quotes and several levels of order book depth. Price impacts are estimated by means of appropriate impulse response functions. Analyzing order book data of 30 stocks traded at Euronext Amsterdam, we show that limit orders have significant market impacts and cause a dynamic (and typically asymmetric) rebalancing of the book. The strength and direction of quote and spread responses depend on the incoming orders’ aggressiveness, their size and the state of the book. We show that the effects are qualitatively quite stable across the market. Cross-sectional variations in the magnitudes of price impacts are well explained by the underlying trading frequency and relative tick size.
We introduce a regularization and blocking estimator for well-conditioned high-dimensional daily covariances using high-frequency data. Using the Barndorff-Nielsen, Hansen, Lunde, and Shephard (2008a) kernel estimator, we estimate the covariance matrix block-wise and regularize it. A data-driven grouping of assets of similar trading frequency ensures the reduction of data loss due to refresh time sampling. In an extensive simulation study mimicking the empirical features of the S&P 1500 universe we show that the ’RnB’ estimator yields efficiency gains and outperforms competing kernel estimators for varying liquidity settings, noise-to-signal ratios, and dimensions. An empirical application of forecasting daily covariances of the S&P 500 index confirms the simulation results.
We examine intra-day market reactions to news in stock-specific sentiment disclosures. Using pre-processed data from an automated news analytics tool based on linguistic pattern recognition we extract information on the relevance as well as the direction of company-specific news. Information-implied reactions in returns, volatility as well as liquidity demand and supply are quantified by a high-frequency VAR model using 20 second intervals. Analyzing a cross-section of stocks traded at the London Stock Exchange (LSE), we find market-wide robust news-dependent responses in volatility and trading volume. However, this is only true if news items are classified as highly relevant. Liquidity supply reacts less distinctly due to a stronger influence of idiosyncratic noise. Furthermore, evidence for abnormal highfrequency returns after news in sentiments is shown. JEL-Classification: G14, C32
Recent empirical research suggests that measures of investor sentiment have predictive power for future stock returns at intermediate and long horizons. Given that sentiment indicators are widely published, smart investors should exploit the information conveyed by the indicator and thus trigger an immediate market response to the publication of the sentiment indicator. The present paper is the first to empirically analyze whether this immediate response can be identified in the data. We use survey-based sentiment indicators from two countries (Germany and the US). Consistent with previous research we find predictability at intermediate horizons. However, the predictability in the US largely disappears after 1994. Using event study methodology we find that the publication of sentiment indicators affects market returns. The sign of this immediate response is the same as the sign of the intermediate horizon predictability. This is consistent with sentiment being related to mispricing but is inconsistent with the sentiment indicator providing information about future expected returns.
JEL-Classification: G12, G14
This paper provides a joint analysis of household stockholding participation, stock location among stockholding modes, and participation spillovers, using data from the US Survey of Consumer Finances. Our multivariate choice model matches observed participation rates, conditional and unconditional, and asset location patterns. Financial education and sophistication strongly affect direct stockholding and mutual fund participation, while social interactions affect stockholding through retirement accounts only. Household characteristics influence stockholding through retirement accounts conditional on owning retirement accounts, unlike what happens with stockholding through mutual funds. Although stockholding is more common among retirement account owners, this fact is mainly due to their characteristics that led them to buy retirement accounts in the first place rather than to any informational advantages gained through retirement account ownership itself. Finally, our results suggest that, taking stockholding as given, stock location is not arbitrary but crucially depends on investor characteristics. JEL Classification: G11, E21, D14, C35
We merge administrative information from a large German discount brokerage firm with regional data to examine if financial advisors improve portfolio performance. Our data track accounts of 32,751 randomly selected individual customers over 66 months and allow direct comparison of performance across self-managed accounts and accounts run by, or in consultation with, independent financial advisors. In contrast to the picture painted by simple descriptive statistics, econometric analysis that corrects for the endogeneity of the choice of having a financial advisor suggests that advisors are associated with lower total and excess account returns, higher portfolio risk and probabilities of losses, and higher trading frequency and portfolio turnover relative to what account owners of given characteristics tend to achieve on their own. Regression analysis of who uses an IFA suggests that IFAs are matched with richer, older investors rather than with poorer, younger ones.
Opting out of the great inflation: German monetary policy after the break down of Bretton Woods
(2009)
During the turbulent 1970s and 1980s the Bundesbank established an outstanding reputation in the world of central banking. Germany achieved a high degree of domestic stability and provided safe haven for investors in times of turmoil in the international financial system. Eventually the Bundesbank provided the role model for the European Central Bank. Hence, we examine an episode of lasting importance in European monetary history. The purpose of this paper is to highlight how the Bundesbank monetary policy strategy contributed to this success. We analyze the strategy as it was conceived, communicated and refined by the Bundesbank itself. We propose a theoretical framework (following Söderström, 2005) where monetary targeting is interpreted, first and foremost, as a commitment device. In our setting, a monetary target helps anchoring inflation and inflation expectations. We derive an interest rate rule and show empirically that it approximates the way the Bundesbank conducted monetary policy over the period 1975-1998. We compare the Bundesbank´s monetary policy rule with those of the FED and of the Bank of England. We find that the Bundesbank´s policy reaction function was characterized by strong persistence of policy rates as well as a strong response to deviations of inflation from target and to the activity growth gap. In contrast, the response to the level of the output gap was not significant. In our empirical analysis we use real-time data, as available to policy-makers at the time. JEL Classification: E31, E32, E41, E52, E58