An information-based model of target stock price runup in the market for corporate control

The stock price runup of target firms in the market for corporate control has been anecdotally attributed to inside trading. Moreover, the empirical merger and acquisitions literature documents a time-varying level and duration of the stock price runup of target firms. Using a market microstructure approach, we model stock price runup as a stochastic process that shifts between a random walk without drift and a predictable process dependent on a parsimonious set of state variables. Consistent with the market microstructure literature, predictability in prices can be exploited only by the informed trader. The model is capable of explaining the complex stylized facts observed in stock price runup. It is also consistent with the merger wave literature, as we find that capital liquidity, economic growth, and market valuations drive the complex dynamics of stock price runup.     

Random walk or a run. Market microstructure analysis of foreign exchange rate movements based on conditional probability

Using tick-by-tick data for the dollar–yen and euro–dollar exchange rates recorded on the actual transaction platform, a ‘run’—continuous increases or decreases in deal prices for the past several ticks—does have some predictable information on the direction of the next price movement. Deal price movements, that are consistent with order flows, tend to continue a run once it is started. Indeed, conditional probabilities of a run continuing in the same direction after several consecutive observations exceed 0.5. However, quote prices do not show such a run tendency. Hence, a random walk hypothesis is refuted in a simple test of a run using tick-by-tick data. In addition, a longer continuous increase of the price tends to be followed by a larger reversal. The findings suggest that those market participants who have access to real-time, tick-by-tick transaction data may have an advantage in predicting exchange rate movements. The findings reported here also lend support to the momentum trading strategy.     

Revisiting the intertemporal risk–return relation: asymmetrical effect of unexpected volatility shocks

We suggest that an unexpected volatility shock is an important risk factor to induce the intertemporal relation, and the conflicting findings on the relation could be attributable to an omitting variable bias resulting from ignoring the effect of an unexpected volatility shock on the relation. With the effect of an unexpected volatility shock incorporated in estimation, we find a strong positive intertemporal relation for the US monthly excess returns for 1926:12–2008:12. We also find a significant link between the asymmetric mean-reversion and the intertemporal relation in that the quicker reversion of negative returns is attributed to the negative intertemporal relation under a prior negative return shock.     

行为如何影响资产定价——理论模型与实证分析

本文基于金融经济学中状态价格与随机折现因子等理论的分析,认为资产定价会受到行为因素的影响.在此基础上本文提出了状态价格函数,并建立了行为影响资产定价的多项式模型.     

Change analysis of a dynamic copula for measuring dependence in multivariate financial data

This paper proposes a new approach to measure dependencies in multivariate financial data. Data in finance and insurance often cover a long time period. Therefore, the economic factors may induce some changes within the dependence structure. Recently, two methods have been proposed using copulas to analyse such changes. The first approach investigates changes within the parameters of the copula. The second determines the sequence of copulas using moving windows. In this paper we take into account the non-stationarity of the data and analyse the impact of (1) time-varying parameters for a copula family, and (2) the sequence of copulas, on the computations of the VaR and ES measures. We propose tests based on conditional copulas and the goodness-of-fit to decide the type of change, and further give the corresponding change analysis. We illustrate our approach using the Standard & Poor 500 and Nasdaq indices in order to compute risk measures using the two previous methods.     

Trust in,trust out: a real cost of sudden and significant financial loss

This study examines the loss of trust that occurs when individuals suffer from sudden and significant financial loss. We use a qualitative case study to show that individuals lose trust in a range of parties, including financial advisors, banks, credit providers, government and perhaps most damagingly of all, oneself. Such outcomes are concerning as all financial services are based on trust between various parties, and trust is important in making financial decisions. A lack of trust can lead to poorer individual and societal outcomes. It also suggests that trends to financial self‐sufficiency have risks, which impact well beyond monetary losses.