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Systemic co-jumps
(2016)
The simultaneous occurrence of jumps in several stocks can be associated with major financial news, triggers short-term predictability in stock returns, is correlated with sudden spikes of the variance risk premium, and determines a persistent increase (decrease) of stock variances and correlations when they come along with bad (good) news. These systemic events and their implications can be easily overlooked by traditional univariate jump statistics applied to stock indices. They are instead revealed in a clearly cut way by using a novel test procedure applied to individual assets, which is particularly effective on high-volume stocks.
This paper addresses whether and to what extent econometric methods used in experimental studies can be adapted and applied to financial data to detect the best-fitting preference model. To address the research question, we implement a frequently used nonlinear probit model in the style of Hey and Orme (1994) and base our analysis on a simulation stud. In detail, we simulate trading sequences for a set of utility models and try to identify the underlying utility model and its parameterization used to generate these sequences by maximum likelihood. We find that for a very broad classification of utility models, this method provides acceptable outcomes. Yet, a closer look at the preference parameters reveals several caveats that come along with typical issues attached to financial data, and that some of these issues seems to drive our results. In particular, deviations are attributable to effects stemming from multicollinearity and coherent under-identification problems, where some of these detrimental effects can be captured up to a certain degree by adjusting the error term specification. Furthermore, additional uncertainty stemming from changing market parameter estimates affects the precision of our estimates for risk preferences and cannot be simply remedied by using a higher standard deviation of the error term or a different assumption regarding its stochastic process. Particularly, if the variance of the error term becomes large, we detect a tendency to identify SPT as utility model providing the best fit to simulated trading sequences. We also find that a frequent issue, namely serial correlation of the residuals, does not seem to be significant. However, we detected a tendency to prefer nesting models over nested utility models, which is particularly prevalent if RDU and EXPO utility models are estimated along with EUT and CRRA utility models.
Microeconomic modeling of investors behavior in financial markets and its results crucially depends on assumptions about the mathematical shape of the underlying preference functions as well as their parameterizations. With the purpose to shed some light on the question, which preferences towards risky financial outcomes prevail in stock markets, we adopted and applied a maximum likelihood approach from the field of experimental economics on a randomly selected dataset of 656 private investors of a large German discount brokerage firm. According to our analysis we find evidence that the majority of these clients follow trading pattern in accordance with Prospect Theory (Kahneman and Tversky (1979)). We also find that observable sociodemographic and personal characteristics such as gender or age don't seem to correlate with specific preference types. With respect to the overall impact of preferences on trading behavior, we find a moderate impact of preferences on trading decisions of individual investors. A classification of investors according to various utility types reveals that the strength of the impact of preferences on an investors' rading behavior is not connected to most personal characteristics, but seems to be related to round-trip length.
Shortcomings revealed by experimental and theoretical researchers such as Allais (1953), Rabin (2000) and Rabin and Thaler (2001) that put the classical expected utility paradigm von Neumann and Morgenstern (1947) into question, led to the proposition of alternative and generalized utility functions, that intend to improve descriptive accuracy. The perhaps best known among those alternative preference theories, that has attracted much popularity among economists, is the so called Prospect Theory by Kahneman and Tversky (1979) and Tversky and Kahneman (1992). Its distinctive features, governed by its set of risk parameters such as risk sensitivity, loss aversion and decision weights, stimulated a series of economic and financial models that build on the previously estimated parameter values by Tversky and Kahneman (1992) to analyze and explain various empirical phenomena for which expected utility doesn't seem to offer a satisfying rationale. In this paper, after providing a brief overview of the relevant literature, we take a closer look at one of those papers, the trading model of Vlcek and Hens (2011) and analyze its implications on Prospect Theory parameters using an adopted maximum likelihood approach for a dataset of 656 individual investors from a large German discount brokerage firm. We find evidence that investors in our dataset are moderately averse to large losses and display high risk sensitivity, supporting the main assumptions of Prospect Theory.
Ongoing demographic change will lead to a relative scarcity of raw labor to the effect that output growth will be decreasing in the next decades, a secular stagnation. As physical capital will be relatively abundant, this decrease of output will be accompanied by reductions of asset returns. We quantify these effects for the US economy by developing an overlapping generations model with risky and risk-free assets. Without adjustments of human capital, risky returns decrease until 2035 by about 0.7 percentage point, and the risk-free rate by about one percentage point, leading to substantial welfare losses for asset rich households. Per capita output is reduced by 6%. Endogenous human capital adjustments strongly mitigate these effects. We conclude that human capital policies will be crucial in the context of labor shortages.
We study whether the presence of low-latency traders (including high-frequency traders (HFTs)) in the pre-opening period contributes to market quality, defined by price discovery and liquidity provision, in the opening auction. We use a unique dataset from the Tokyo Stock Exchange (TSE) based on server-IDs and find that HFTs dynamically alter their presence in different stocks and on different days. In spite of the lack of immediate execution, about one quarter of HFTs participate in the pre-opening period, and contribute significantly to market quality in the pre-opening period, the opening auction that ensues and the continuous trading period. Their contribution is largely different from that of the other HFTs during the continuous period.
The equity trading landscape all over the world has changed dramatically in recent years. We have witnessed the advent of new trading venues and significant changes in the market shares of existing ones. We use an extensive panel dataset from the European equity markets to analyze the market shares of five categories of lit and dark trading mechanisms. Market design features, such as minimum tick size, immediacy and anonymity; market conditions, such as liquidity and volatility; and the informational environment have distinct implications for order routing decisions and trading venues' resulting market shares. Furthermore, these implications differ distinctly for small and large trades, probably because traders jointly optimize their trade size and venue choice. Our results both confirm and go beyond current theoretical predictions on trading in fragmented markets.
Using two datasets containing demographically representative samples of the Dutch population, I study how lifetime experiences of aggregate labor market conditions affect personality. Three sets of findings are reported. First, experienced aggregate unemployment is negatively correlated with the levels of all Big Five personality traits, except for conscientiousness (no significant correlation). Second, in panel data models with individual fixed effects I find that changes in experienced aggregate unemployment cause changes in emotional stability and agreeableness for men, and conscientiousness for women. The correlation is positive, and effects are economically large. Thirdly, I report suggestive evidence that the main driver is experienced aggregate unemployment, instead of other macroeconomic variables as experienced GDP, stock market returns or inflation. Taken together, these findings suggest that changes in Big Five personality traits are systematically related to experienced aggregate labor market conditions.
This paper is the outcome of a related broader project, exploring the explanatory power of the Legal Theory of Finance, which proposes a new institution-based analytical framework for the analysis of phenomena of financial markets. One of its most important theoretical assumptions, the legal construction of financial markets, is highlighted by the example of the private creation of money by structured finance products in this paper. Further implications can then be shown referring to pari passu clauses and collective action clauses, which are both exhibit a differential application of these legal rules according to the hierarchical status of the respective market participant, and can therefore endanger sovereign debt restructurings. Legal instruments to avoid this are briefly explored. An example of another key role of the law in crisis that is the task to resolve the tension between market discipline and financial stability is exemplified by the regulation of the OTC derivatives market and proposals of effective loss-sharing among CCPs. Related questions about the significance of legal rules to ensure financial stability are raised in the analysis of minimum capital requirements under Basel III.
“Institutional Overburdening” to a large extent was a consequence of the “Great Moderation”. This term indicates that it was a period in which inflation had come down from rather high levels. Growth and employment were at least satisfying and variability of output had substantially declined. It was almost unavoidable that as a consequence expectations on future actions of central banks and their ability to control the economy reached an unprecedented peak which was hardly sustainable. Institutional overburdening has two dimensions. One is coming from exaggerated expectations on what central banks can achieve (“expectational overburdening”). The other dimension is “operational overburdening” i.e. overloading the central bank with more and more responsibilities and competences.