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Price pressures
(2010)
We study price pressures in stock prices—price deviations from fundamental value due to a risk-averse intermediary supplying liquidity to asynchronously arriving investors. Empirically, twelve years of daily New York Stock Exchange intermediary data reveal economically large price pressures. A $100,000 inventory shock causes an average price pressure of 0.28% with a half-life of 0.92 days. Price pressure causes average transitory volatility in daily stock returns of 0.49%. Price pressure effects are substantially larger with longer durations in smaller stocks. Theoretically, in a simple dynamic inventory model the ‘representative’ intermediary uses price pressure to control risk through inventory mean reversion. She trades off the revenue loss due to price pressure against the price risk associated with remaining in a nonzero inventory state. The model’s closed-form solution identifies the intermediary’s relative risk aversion and the distribution of investors’ private values for trading from the observed time series patterns. These allow us to estimate the social costs—deviations from constrained Pareto efficiency—due to price pressure which average 0.35 basis points of the value traded. JEL Classification: G12, G14, D53, D61
This paper presents a model to analyze the consequences of competition in order-flow between a profit maximizing stock exchange and an alternative trading platform on the decisions concerning trading fees and listing requirements. Listing requirements, set by the exchange, provide public information on listed firms and contribute to a better liquidity on all trading venues. It is sometimes asserted that competition induces the exchange to lower its level of listing standards compared to a situation in which it is a monopolist, because the trading platform can free-ride on this regulatory activity and compete more aggressively on trading fees. The present analysis shows that this is not always true and depends on the existence and size of gains related to multi market trading. These gains relax competition on trading fees. The higher these gains are, the more the exchange can increase its revenue from listing and trading when it raises its listing standards. For large enough gains from multi-market trading, the exchange is not induced to lower the level of listing standards when a competing trading platform appears. As a second result, this analysis also reveals a cross - subsidization effect between the listing and the trading activity when listing is not competitive. This model yields implications about the fee structures on stock markets, the regulation of listings and the social optimality of competition for volume. JEL Classification: G10, G18, G12
This paper proposes the Shannon entropy as an appropriate one-dimensional measure of behavioural trading patterns in financial markets. The concept is applied to the illustrative example of algorithmic vs. non-algorithmic trading and empirical data from Deutsche Börse's electronic cash equity trading system, Xetra. The results reveal pronounced differences between algorithmic and non-algorithmic traders. In particular, trading patterns of algorithmic traders exhibit a medium degree of regularity while non-algorithmic trading tends towards either very regular or very irregular trading patterns. JEL Classification: C40, D0, G14, G15, G20
How ordinary consumers make complex economic decisions: financial literacy and retirement readiness
(2010)
This paper explores who is financially literate, whether people accurately perceive their own economic decision-making skills, and where these skills come from. Self-assessed and objective measures of financial literacy can be linked to consumers’ efforts to plan for retirement in the American Life Panel, and causal relationships with retirement planning examined by exploiting information about respondent financial knowledge acquired in school. Results show that those with more advanced financial knowledge are those more likely to be retirement-ready.
We examined financial literacy among the young using the most recent wave of the 1997 National Longitudinal Survey of Youth. We showed that financial literacy is low; fewer than one-third of young adults possess basic knowledge of interest rates, inflation, and risk diversification. Financial literacy was strongly related to sociodemographic characteristics and family financial sophistication. Specifically, a college-educated male whose parents had stocks and retirement savings was about 45 percentage points more likely to know about risk diversification than a female with less than a high school education whose parents were not wealthy. These findings have implications for consumer policy. JEL Classification: D91
This paper investigates the accuracy and heterogeneity of output growth and inflation forecasts during the current and the four preceding NBER-dated U.S. recessions. We generate forecasts from six different models of the U.S. economy and compare them to professional forecasts from the Federal Reserve’s Greenbook and the Survey of Professional Forecasters (SPF). The model parameters and model forecasts are derived from historical data vintages so as to ensure comparability to historical forecasts by professionals. The mean model forecast comes surprisingly close to the mean SPF and Greenbook forecasts in terms of accuracy even though the models only make use of a small number of data series. Model forecasts compare particularly well to professional forecasts at a horizon of three to four quarters and during recoveries. The extent of forecast heterogeneity is similar for model and professional forecasts but varies substantially over time. Thus, forecast heterogeneity constitutes a potentially important source of economic fluctuations. While the particular reasons for diversity in professional forecasts are not observable, the diversity in model forecasts can be traced to different modeling assumptions, information sets and parameter estimates. JEL Classification: C53, D84, E31, E32, E37 Keywords: Forecasting, Business Cycles, Heterogeneous Beliefs, Forecast Distribution, Model Uncertainty, Bayesian Estimation
This paper analyzes loan pricing when there is multiple banking and borrower distress. Using a unique data set on SME lending collected from major German banks, we can instrument for effective coordination between lenders, carrying out a panel estimation. The analysis allows to distinguish between rents that accrue due to single bank lending, rents that accrue due to relationship lending, and rents that accrue due to the elimination of competition among multiple lenders. We find the relationship lending to have no discernible impact on loan spreads, while both single lending and coordinated multiple lending significantly increase the spread. Thus, contrary to predictions in the literature, multiple lending does not insure the borrower against hold-up. JEL Classification: D74, G21, G33, G34