Are REITs more resilient than non-REITs? Evidence from natural experiments

REITs draw attention from investors around the world, yet our understanding of the various risks associated with such securities is limited. Using the introduction of Arrowhead, a low-latency high-frequency trading platform, to the Tokyo Stock Exchange and the financial crisis of 2008 as natural experiments, we compare the resilience of REITs and equities in terms of liquidity and volatility. The results indicate that the introduction of Arrowhead improved the quality of the Japanese REIT market but also increased the probability of flash crashes. We also find that although the financial crisis significantly deteriorated overall equity market quality, the Japanese REIT market was resilient. Finally, using a difference-in-differences regression model, we show that the higher transparency and better price discovery of REITs, compared to non-REITS, protected them from the negative effects of the financial crisis and the introduction of Arrowhead. Overall, our analysis shows that REITs are more resilient than non-REITs.     

Market impact: a systematic study of the high frequency options market

This paper deals with a fundamental subject that has seldom been addressed in recent years, that of market impact in the options market. Our analysis is based on a proprietary database of metaorders—large orders that are split into smaller pieces before being sent to the market—on one of the main Asian markets. In line with our previous work on the equity market [Said, E., Bel Hadj Ayed, A., Husson, A. and Abergel, F., Market impact: A systematic study of limit orders. Mark. Microstruct. Liq., 2018, 3(3&4), 1850008.], we propose an algorithmic approach to identify metaorders, based on some implied volatility parameters, the at the money forward volatility and at the money forward skew. In both cases, we obtain results similar to the now well-understood equity market: Square-Root Law, Fair Pricing Condition and Market Impact Dynamics.     

The legacy of state socialism on attitudes toward immigration

Does the politico–economic system affect preferences for immigration? In this study, I show that individuals exposed to life under state socialism have formed and persistently hold different attitudes toward immigration. By exploiting the division and reunification of Germany, I estimate the influence of state socialism on attitudes toward immigration. Drawing on rich individual panel data, I find that East Germans who lived under state socialism, are 15 percent more likely to oppose immigration than West Germans who spent their entire life in a democratic, capitalist country. This difference in attitudes toward immigration is persistent over time and across space, and largest for cohorts born and raised under state socialism. This gap in attitudes can be traced back to a longer-term deterioration in trust. Evidence from members of a group that opposed the authoritarian system highlights the importance of state socialist ideology for attitude formation.     

跳频信号的归一化多普勒频差最大似然估计

针对双站定位涉及的跳频信号多普勒频差估计问题，提出了归一化的频差最大似然估计算法，利用两个定位站接收到的跳频脉冲串信号，构建一个关于基准跳频频率多普勒频差的似然函数，通过网格搜索得到使似然函数最大的多普勒频差估计，既解决了跳频信号在不同跳频频率上多普勒频差不一致的问题，又充分利用在不同频率的脉冲串信号提高了多普勒频差估计精度。通过仿真对算法的性能进行了评估，结果表明，与基于子空间的算法比较，在脉冲数达到240个时，所提算法执行效率提升30%以上。     

广义空间调制系统的正则化OMP检测算法

在广义空间调制（GSM）系统中，最大似然（ML）检测可以取得最优的检测性能，然而其计算复杂度随激活天线数的增加急剧增长。针对这一问题，提出了一种基于稀疏重构理论的低复杂度检测算法——正则化正交匹配追踪（ROMP）算法。该算法首先根据信道矩阵和当前残差的内积选取多个候选激活天线索引，接着对候选天线索引按正则化标准进行可靠性验证，剔除错误索引，缩小信号的搜索空间，最后通过求解最小二乘问题估计信号。仿真结果表明，与经典的正交匹配追踪（OMP）算法相比，所提算法以少许复杂度的增加为代价极大提升了检测性能，能够在检测性能与复杂度之间取得更好的折中。     

Time and frequency domain causality Testing: The causal linkage between FDI and economic risk for the case of Turkey

This study aims to explore the causal relationship between economic risk and foreign direct investment (FDI) inflows for the case of Turkey. With the aim of establishing robust findings for the research in mind, both traditional and modern causality techniques are utilized; time domain Granger (1969, “Investigating Causal Relations by Econometric Models and Cross-Spectral Methods.” Econometrica 37: 424–438.), Toda and Yamamoto (1995, “Statistical Inference in Vector Autoregressions with Possibly Integrated Processes.” Journal of Econometrics 66 (1–2): 225–250.), Fourier Toda-Yamamoto and frequency domain Breitung and Candelon (2006, “Testing for short- and long-run causality: A frequency-domain approach.” Journal of Econometrics 132 (2): 363–378.) spectral causality test. Our empirical findings reveal that; economic risk changes in Turkey significantly lead to changes in FDI inflows. However, there is no evidence of causality running from FDI to economic risk. The findings imply that economic risk is an essential determinant of FDI inflows in Turkey. Our findings are compatible with historical macroeconomic developments in Turkey and imply important policy implications. The results of this study can be generalized for other emerging economies that have similar macroeconomic environments, in order to create useful policy implications regarding FDI inflow.     

Individually rational rules for the division problem when the number of units to be allotted is endogenous

We study individually rational rules to be used to allot, among a group of agents, a perfectly divisible good that is freely available only in whole units. A rule is individually rational if, at each preference profile, each agent finds that her allotment is at least as good as any whole unit of the good. We study and characterize two individually rational and efficient families of rules, whenever agents' preferences are symmetric single-peaked on the set of possible allotments. Rules in the two families are in addition envy-free, but they differ on whether envy-freeness is considered on losses or on awards. Our main result states that (a) the family of constrained equal losses rules coincides with the class of all individually rational and efficient rules that satisfy justified envy-freeness on losses and (b) the family of constrained equal awards rules coincides with the class of all individually rational and efficient rules that satisfy envy-freeness on awards.     

The endo–exo problem in high frequency financial price fluctuations and rejecting criticality

The endo–exo problem lies at the heart of statistical identification in many fields of science, and is often plagued by spurious strong-and-long memory due to improper treatment of trends, shocks and shifts in the data. A class of models that has shown to be useful in discerning exogenous and endogenous activity is the Hawkes process. This class of point processes has enjoyed great recent popularity and rapid development within the quantitative finance literature, with particular focus on the study of market microstructure and high frequency price fluctuations. We show that there are important lessons from older fields like time series and econometrics that should also be applied in financial point process modelling. In particular, we emphasize the importance of appropriately treating trends and shocks for the identification of the strength and length of memory in the system. We exploit the powerful Expectation Maximization algorithm and objective statistical criteria (BIC) to select the flexibility of the deterministic background intensity. With these methods, we strongly reject the hypothesis that the considered financial markets are critical at univariate and bivariate microstructural levels.     

Why you should use high frequency data to test the impact of exchange rate on trade

This study suggests that testing the impact of exchange rate on trade should be done using high-frequency data. Using different data frequencies for identical periods and specifications between the US and Canada, we show that low-frequency data might suppress and distort the evidence of the impact of exchange rate on trade in the short run and the long run.