Mean Reversion Expectations and the 1987 Stock Market Crash: An Empirical Investigation

After the stock market crash of 1987, Fischer Black proposed a model in which he explained the crash by inconsistencies in the formation of expectations of mean reversion in stock returns. Following this explanation, a model that allows for mean reversion in stock returns is estimated on daily stock index data around the crash of 1987. The results strongly support Black’s hypothesis. Simulations show that on Friday Oct 16, 1987, a crash of 20 percent or more had a probability of more than seven percent.stock-market crash, mean reversion, stock return predictability, change-points

Overlaying Time Scales and Persistence Estimation in GARCH(1,1) Models

A common finding in the empirical literature is that financial volatility exhibits high persistence, or slow mean reversion of the order of months. We present evidence that financial volatility data contains more than a single time scale. After showing that the expectation of the sum of the estimates of the autoregressive coefficients of a GARCH(1,1) model is one when there are unknown parameter changes, we explore the phenomenon in simulations. For parameter changes within realistic ranges for stock-price volatility we obtain global estimates close to integration while the average data- generating mean reversion is of the order of a few days. Spectral analysis of the Dow Jones Industrial Average and the S&P500 index between 1985 and 2001 reveals a short time scale of the magnitude of 5- 10 days present in the data. Thus, two different time scales exist in the data, one of the order of months corresponding to different volatility regimes, and one of the order of days corresponding to the average mean reversion within regimes.GARCH, volatility persistence, regime switching, long memory, short memory, structural change

Letter from Margaret Mann to Mark Rich

This letter from Margaret Mann, secretary and instructor in stenography and typewriting at McMinnville College (later Linfield College), provides a response to a letter Mark Rich wrote before beginning his first year at the college. The letter answers questions regarding class requirements and his scholarship, and it explains the beginning of the fall semester was pushed back to October 1 because of a scarcity of labor.https://digitalcommons.linfield.edu/lca_rich/1001/thumbnail.jp

Environmental conditions of a salt-marsh biodiversity experiment on the island of Spiekeroog (Germany)

Field experiments investigating biodiversity and ecosystem functioning require the observation of abiotic parameters, especially when carried out in the intertidal zone. An experiment for biodiversity–ecosystem functioning was set up in the intertidal zone of the back-barrier salt marsh of Spiekeroog Island in the German Bight. Here, we report the accompanying instrumentation, maintenance, data acquisition, data handling and data quality control as well as monitoring results observed over a continuous period from September 2014 to April 2017. Time series of abiotic conditions were measured at several sites in the vicinity of newly built experimental salt-marsh islands on the tidal flat. Meteorological measurements were conducted from a weather station (WS, https://doi.org/10.1594/PANGAEA.870988), oceanographic conditions were sampled through a bottom-mounted recording current meter (RCM, https://doi.org/10.1594/PANGAEA.877265) and a bottom-mounted tide and wave recorder (TWR, https://doi.org/10.1594/PANGAEA.877258). Tide data are essential in calculating flooding duration and flooding frequency with respect to different salt-marsh elevation zones. Data loggers (DL) for measuring the water level (DL-W, https://doi.org/10.1594/PANGAEA.877267), temperature (DL-T, https://doi.org/10.1594/PANGAEA.877257), light intensity (DL-L, https://doi.org/10.1594/PANGAEA.877256) and conductivity (DL-C, https://doi.org/10.1594/PANGAEA.877266) were deployed at different elevational zones on the experimental islands and the investigated salt-marsh plots. A data availability of 80% for 17 out of 23 sensors was achieved. Results showed the influence of seasonal and tidal dynamics on the experimental islands. Nearby salt-marsh plots exhibited some differences, e.g., in temperature dynamics. Thus, a consistent, multi-parameter, long-term dataset is available as a basis for further biodiversity and ecosystem functioning studies

Outlier robust corner-preserving methods for reconstructing noisy images

The ability to remove a large amount of noise and the ability to preserve most structure are desirable properties of an image smoother. Unfortunately, they usually seem to be at odds with each other; one can only improve one property at the cost of the other. By combining M-smoothing and least-squares-trimming, the TM-smoother is introduced as a means to unify corner-preserving properties and outlier robustness. To identify edge- and corner-preserving properties, a new theory based on differential geometry is developed. Further, robustness concepts are transferred to image processing. In two examples, the TM-smoother outperforms other corner-preserving smoothers. A software package containing both the TM- and the M-smoother can be downloaded from the Internet.Comment: Published at http://dx.doi.org/10.1214/009053606000001109 in the Annals of Statistics (http://www.imstat.org/aos/) by the Institute of Mathematical Statistics (http://www.imstat.org

A structural break in the effects of Japanese foreign exchange intervention on yen/dollar exchange rate volatility

While up to the late 1990s Japanese foreign exchange intervention was fully sterilized, Japanese monetary authorities left foreign exchange intervention unsterilized when Japan entered the liquidity trap in 1999. According to previous research on foreign exchange intervention, unsterilized intervention has a higher probability of success than sterilized intervention. Based on a GARCH framework and change point detection, we test for a structural break in the effectiveness of Japanese foreign exchange intervention. We find a changing impact of Japanese foreign exchange intervention on exchange rate volatility at the turn of the millennium when Japanese foreign exchange intervention started to remain unsterilized. JEL Classification: E58, F31, F33, G15Change Point Detection, Exchange rate volatility, foreign exchange intervention, GARCH, Japan, Structural Breaks

Interaction of market and credit risk: an analysis of inter-risk correlation and risk aggregation

In this paper we investigate the interaction between a credit portfolio and another risk type, which can be thought of as market risk. Combining Merton-like factor models for credit risk with linear factor models for market risk, we analytically calculate their interrisk correlation and show how inter-risk correlation bounds can be derived. Moreover, we elaborate how our model naturally leads to a Gaussian copula approach for describing dependence between both risk types. In particular, we suggest estimators for the correlation parameter of the Gaussian copula that can be used for general credit portfolios. Finally, we use our findings to calculate aggregated risk capital of a sample portfolio both by numerical and analytical techniques. -- Die Berechnung einer bankweit aggregierten Risikokennzahl (normalerweise ausgedrückt durch das ökonomische Kapital) ist ein äußerst wichtiger Bestandteil eines modernen Risikocontrollings and als solches von besonderer Bedeutung für bankinterne als auch regulatorische Zwecke. Eine wichtige Frage dabei betrifft die Behandlung von risikoreduzierenden Diversifikationseffekten, die als Folge der Geschäftsstrategie einer Bank (z.B. durch Produktdiversifikation oder geografische Diversifikation) auftreten können. Solche Diversifikationseffekte stellen einen Wettbewerbsvorteil dar, den Banken deshalb bei der Bestimmung ihrer Kapitaladäquanz mit einbeziehen wollen. Auch die Bankenaufsicht erkennt in ihren Ausführungen über die bankinternen Kapitalbeurteilungsverfahren nach den Grundsätzen der zweiten Säule von Basel II die Existenz von Diversifikationseffekten an. Bei der praktischen Berechnung des Diversifikationseffektes unterscheidet man oft zwischen Intrarisiko- und Interrisikodiversifikation. Letztere behandelt die Diversifikation innerhalb einer Risikoart (z.B. Markt- oder Kreditrisiko), wohingegen Interrisiko-Diversifikation die Diversifikation zwischen verschiedenen Risikoarten beschreibt und meist durch eine Interrisiko-Korrelationsmatrix erfasst wird.Risk aggregation,Inter-risk correlation,economic capital,ICAAP,diversification

The Effects of Japanese Foreign Exchange Intervention: GARCH Estimation and Change Point Detection

We study the impact of Japanese foreign exchange intervention on the volatility of the yen/dollar exchange rate since the early 1990s based on a GARCH framework. Using daily intervention data provided by the Japanese Ministry of Finance, we show that the success of interventions varies over time. Measured on the total sample between 1991 and 2003 the estimation results for the impact of foreign exchange intervention on the yen/dollar exchange rate volatility are inconclusive. Sub-dividing the sample into yearly sub-periods and into intervention clusters suggests a structural break. From 1991 up to the late 1990s Japanese foreign exchange intervention seems to have increased the volatility of the yen/dollar exchange rate. In contrast in the new millennium, Japa- nese foreign exchange intervention is associated with less exchange rate volatility. Non-arbitrary segmentation by change point detection leads to similar results. The evidence in favour of recent successful Japanese foreign exchange intervention is line with theoretical evidence which implies successful intervention is the case of un-sterilized intervention.Japan, Foreign Exchange Intervention, Exchange Rate Volatility, GARCH, Change Point Detection, Liquidity Trap

Global Business Cycles: Degree of Synchronization in the Current Downturn Is Unprecedented

Empirical data analysis shows that the business cycles of industrialized nations demonstrate a fairly strong degree of synchronization in periods of growth, and a lesser degree of synchronization during periods of contraction. The current recession, however, breaks this pattern: the business cycles of industrialized nations have exhibited an unprecedented degree of synchronization since the start of the crisis. In the worst economic downturn since the end of the Second World War, the most important national economies have been drawn one after another into the maelstrom of global recession. In this paper we present a method for measuring business-cycle synchronization between individual countries. In our comparison of the current crisis with previous recessions, a focus is placed on the G7 nations and Germany's most important trading partners.Business cycle synchronisation, Markov switching models