Smoothing the payoff for efficient computation of Basket option prices

We consider the problem of pricing basket options in a multivariate Black Scholes or Variance Gamma model. From a numerical point of view, pricing such options corresponds to moderate and high dimensional numerical integration problems with non-smooth integrands. Due to this lack of regularity, higher order numerical integration techniques may not be directly available, requiring the use of methods like Monte Carlo specifically designed to work for non-regular problems. We propose to use the inherent smoothing property of the density of the underlying in the above models to mollify the payoff function by means of an exact conditional expectation. The resulting conditional expectation is unbiased and yields a smooth integrand, which is amenable to the efficient use of adaptive sparse grid cubature. Numerical examples indicate that the high-order method may perform orders of magnitude faster compared to Monte Carlo or Quasi Monte Carlo in dimensions up to 35

On consolidation: Nonviolent struggle as resource for democratic citizenship

Tras las Revoluciones de Colores y la Primavera Árabe, las investigaciones que vinculan la resistencia no violenta (RNV) y la democratización se incrementaron notablemente. Sin embargo, los estudios sobre su efecto en la consolidación democrática siguen siendo escasos. A través de una interpretación neotocquevilleana de democracia, este artículo desarrolla que las protestas de RNV contra gobiernos autoritarios proporcionan recursos importantes para el desarrollo de una ciudadanía democrática y pueden afectar positivamente a la democratización. Como consecuencia de estas luchas, la agencia individual de cada ciudadano aumenta, lo que les permite participar y resistir las represiones si es preciso. A nivel colectivo los activistas participantes sobrepasan sus límites, y la agencia colectiva de toda la población se ve influenciada de forma sostenible al crear una narrativa común sobre el éxito de la lucha. El triunfo de estos hitos simbólicos brinda la oportunidad de reconectar con un movimiento de masas renovado. Por último, estas movilizaciones están integradas en un contexto internacional: las olas de protestas como la Primavera Árabe generan redes internacionales de activistas y simpatizantesAfter the Colour Revolutions and the Arab Spring the research, linking nonviolent Resitence (NVR) and democratisation increased drastically. Nevertheless, research focussing on the effect on democratic consolidation remains scarce. Based on a neo-Tocquevillean understanding of democracy, I argue that NVR against authoritarian rule provides important resources for the development of democratic citizenship and can positively affect democratisation. Because of the struggle for democracy, the individual agency of each citizen rises, enabling him/her to participate and to resist backlashes if necessary. On a collective level and transgressing the circle of the participating activist, the collective agency of the whole population is sustainably affected in creating a collective narrative of the successful struggle of the people. These successful and iconic events provide opportunities to reconnect renewed mass mobilization. Finally yet importantly, such movements are embedded into an international context. Waves of contention like the Arab Spring leave international networks of activists and supporter

Global Militarisation Index 2021

Every year, BICC's Global Militarisation Index (GMI) maps the relative weight and importance of a country's military apparatus in relation to its society as a whole. The Index is financially supported by Germany’s Federal Ministry for Economic Cooperation and Development. The GMI 2021 is an anniversary edition. Its first part reflects, as usual, current developments and trends based on the latest available data. It covers 153 countries and is based on the latest available figures (in most cases, data for 2020). The ten countries with the highest levels of militarisation in the GMI 2021 are Israel, Oman, Azerbaijan, Kuwait, Armenia, Saudi Arabia, Brunei, Bahrain, Singapore and Russia. These countries allocate particularly high levels of resources to the military compared to other areas of society. Besides countries primarily from conflict regions in the Middle East, three European countries can also be found here, all of which are involved in violent conflicts. A further three - Greece and Cyprus, both EU member states, and Ukraine - are among the Top 20. In the regional focus on Europe, one overall trend of the GMI 2021 becomes particularly clear: Despite the decrease in global GDP as a result of the COVID-19 pandemic, countries are spending more resources on the military in absolute terms and as a proportion of their economic output. Another regional focus this time is on Sub-Saharan Africa. In West Africa, in particular, the security situation has deteriorated dramatically over the past few years. Therefore, it is particularly interesting to look at the dynamics of militarisation on that continent. Alongside relatively stable countries, such as Botswana, Namibia, Mauritania, Angola, Gabon and Guinea-Bissau, countries with current violent conflicts, such as Chad, South Sudan and Mali, can be found among the Top 10. The second part of the GMI looks at the global and regional development of militarisation over the past 20 years. This overall view of global militarisation between 2000 and 2020 shows that, except for an interim peak in 2005, it initially decreased steadily. Our resource-based concept of militarisation explains this as follows: It is due to the increase in the world's population and that of global financial resources, which cause the proportion of the military sector in the GMI to decrease from 2000 to 2018. This, however, does not imply "true demilitarisation", as is evidenced by the absolute increase in military spending over the period under review (SIPRI, 2020). Since 2019, this trend has reversed again. In the past two years, rising militarisation can be observed again across the globe, mainly because the resources allocated to the military are increasing in absolute and in relative terms

Global Militarisation Index 2022

Every year, ICC's Global Militarisation Index (GMI) maps the relative weight and importance of a country's military apparatus in relation to its society as a whole. The Index is financially supported by Germany’s Federal Ministry for Economic Cooperation and Development. Its first part reflects current developments and trends based on the latest available data. It covers 154 states and is based on the latest available figures (in most cases, data for 2021). The ten countries with the highest level of militarisation in the GMI 2022 are Israel, Kuwait, Armenia, Singapore, Oman, Bahrain, Greece, Russia, Brunei and Saudi Arabia. These countries allocate particularly large amounts of resources to their military compared to other areas of society. As far as the general militarisation trend is concerned, the GMI 2022 offers a seemingly contradictory picture. It appears that the general upward trend of the previous years is not continuing. This is mainly due to the drop in relative military expenditure, which, measured as a share of GDP (gross domestic product), fell on average from 2.3 to 2.2 per cent, which, in turn, is mainly due to the economic recovery after the Covid-19 pandemic. At the same time, despite a positive population trend, the number of heavy weapons increased in relative and absolute terms, reaching 396,914 this year, a figure last measured in 2012. The second part of the GMI focuses on two regional aspects. For one, we will investigate the planned enlargement of NATO to include Sweden and Finland as member states. Using the three GMI parameters of personnel, financial resources and heavy weapons, we compare NATO with Russia and the Collective Security Treaty Organisation (CSTO). In addition, we take up the 100 billion special fund for the Bundeswehr and sketch out two different scenarios for the militarisation of Germany for the next five years. This year, the conflict between China, Taiwan and the so-called AUKUS countries (Australia, United Kingdom and United States) in the China Sea and the Pacific Ocean continued to escalate. The second regional focus is, therefore, on East Asia and Oceania. Here, we contrast the military potential of the AUKUS countries with that of China. We estimate the degree of militarisation of North Korea and Taiwan, two key countries in the regional conflict. However, as this estimate is based on divergent or older data sources, it is not included in the GMI dataset or the official ranking. This year, the GMI has also evolved methodologically: We complemented the Heavy Weapons Index by including unmanned combat aerial vehicles (UCAVs) and loitering munitions (so-called kamikaze drones) as well as satellites

Multi-Level Fine-Tuning, Data Augmentation, and Few-Shot Learning for Specialized Cyber Threat Intelligence

Gathering cyber threat intelligence from open sources is becoming increasingly important for maintaining and achieving a high level of security as systems become larger and more complex. However, these open sources are often subject to information overload. It is therefore useful to apply machine learning models that condense the amount of information to what is necessary. Yet, previous studies and applications have shown that existing classifiers are not able to extract specific information about emerging cybersecurity events due to their low generalization ability. Therefore, we propose a system to overcome this problem by training a new classifier for each new incident. Since this requires a lot of labelled data using standard training methods, we combine three different low-data regime techniques - transfer learning, data augmentation, and few-shot learning - to train a high-quality classifier from very few labelled instances. We evaluated our approach using a novel dataset derived from the Microsoft Exchange Server data breach of 2021 which was labelled by three experts. Our findings reveal an increase in F1 score of more than 21 points compared to standard training methods and more than 18 points compared to a state-of-the-art method in few-shot learning. Furthermore, the classifier trained with this method and 32 instances is only less than 5 F1 score points worse than a classifier trained with 1800 instances

Globaler Militarisierungsindex 2021

Der Globale Militarisierungsindex (GMI) des BICC bildet alljährlich das relative Gewicht und die Bedeutung des Militärapparats von Staaten im Verhältnis zur Gesellschaft als Ganzes ab. Der Index wird durch das Bundesministerium für Wirtschaftliche Zusammenarbeit und Entwicklung (BMZ) gefördert. Der GMI 2021 ist eine Jubiläumsausgabe. Der erste Teil des Berichtes reflektiert, wie gewohnt, auf Grundlage der neuesten Daten aktuelle Entwicklungen und Trends. Er umfasst 153 Staaten und basiert auf den aktuell vorliegenden Zahlen, in der Regel sind das die Daten des Jahres 2020. Die zehn Länder, die im GMI 2021 den höchsten Militarisierungsgrad aufweisen, sind Israel, Oman, Aserbaidschan, Kuwait, Armenien, Saudi-Arabien, Brunei, Bahrain, Singapur und Russland. Diese Staaten stellen dem Militär im Verhältnis zu anderen gesellschaftlichen Bereichen besonders viele Ressourcen zur Verfügung. Neben vornehmlich Staaten aus Konfliktregionen des Nahen und Mittleren Ostens, sind auch hier drei europäische Länder präsent, die jeweils in Gewaltkonflikte involviert sind. Drei weitere - die beiden EU-Mitglieder Griechenland und Zypern sowie die Ukraine - sind unter den Top 20 zu finden. Im regionalen Fokus Europa wird ein Gesamttrend des GMI 2021 besonders deutlich: Trotz des Absinkens des weltweiten BIP in Folge der Covid 19-Pandemie wenden Staaten in absoluten Zahlen und im Verhältnis zur Wirtschaftsleistung mehr Ressourcen für das Militär auf. Ein weiterer regionaler Fokus liegt diesmal auf Subsahara Afrika. Insbesondere in Westafrika verschlechterte sich die Sicherheitslage in den vergangenen Jahren dramatisch. Daher ist eine Betrachtung der Militarisierungsdynamiken auf dem Kontinent besonders interessant. So rangieren unter seinen Top 10 neben relativ stabilen Ländern wie Botswana, Namibia, Mauretanien, Angola, Gabun und Guinea-Bissau auch Staaten mit aktuellen Gewaltkonflikten wie Tschad, Südsudan und Mali. Der zweite Teil des GMI 2021 betrachtet die globale und regionale Entwicklung von Militarisierung über die vergangenen 20 Jahre. Die Gesamtbetrachtung der globalen Militarisierung zwischen 2000 und 2020 ergibt, dass diese, bis auf ein Zwischenhoch im Jahr 2005, bis 2018 zunächst kontinuierlich sinkt. Unser ressourcenbezogenes Konzept von Militarisierung erklärt dies so: Es ist das Anwachsen sowohl der Weltbevölkerung als auch der globalen finanziellen Mittel, die im GMI den Anteil des militärischen Sektors von 2000 bis 2018 geringer werden lässt. Dies bedeutet jedoch keine "echte Demilitarisierung", wie die absolute Steigerung der Militärausgaben im Bezugszeitraum belegt (SIPRI 2020). Seit 2019 hat sich dieser Trend wieder umgekehrt. In den letzten zwei Jahren ist weltweit eine steigende Militarisierung zu beobachten, was vor allem darauf zurückzuführen ist, dass die dem Militär zugewiesenen Ressourcen nicht nur absolut, sondern auch relativ steigen

Smoothing the payoff for efficient computation of basket option prices

We consider the problem of pricing basket options in a multivariate Black Scholes or Variance Gamma model. From a numerical point of view, pricing such options corresponds to moderate and high dimensional numerical integration problems with non-smooth integrands. Due to this lack of regularity, higher order numerical integration techniques may not be directly available, requiring the use of methods like Monte Carlo specifically designed to work for non-regular problems. We propose to use the inherent smoothing property of the density of the underlying in the above models to mollify the payoff function by means of an exact conditional expectation. The resulting conditional expectation is unbiased and yields a smooth integrand, which is amenable to the efficient use of adaptive sparse grid cubature. Numerical examples indicate that the high-order method may perform orders of magnitude faster compared to Monte Carlo or Quasi Monte Carlo in dimensions up to 25

ThreatCrawl: A BERT-based Focused Crawler for the Cybersecurity Domain

Publicly available information contains valuable information for Cyber Threat Intelligence (CTI). This can be used to prevent attacks that have already taken place on other systems. Ideally, only the initial attack succeeds and all subsequent ones are detected and stopped. But while there are different standards to exchange this information, a lot of it is shared in articles or blog posts in non-standardized ways. Manually scanning through multiple online portals and news pages to discover new threats and extracting them is a time-consuming task. To automize parts of this scanning process, multiple papers propose extractors that use Natural Language Processing (NLP) to extract Indicators of Compromise (IOCs) from documents. However, while this already solves the problem of extracting the information out of documents, the search for these documents is rarely considered. In this paper, a new focused crawler is proposed called ThreatCrawl, which uses Bidirectional Encoder Representations from Transformers (BERT)-based models to classify documents and adapt its crawling path dynamically. While ThreatCrawl has difficulties to classify the specific type of Open Source Intelligence (OSINT) named in texts, e.g., IOC content, it can successfully find relevant documents and modify its path accordingly. It yields harvest rates of up to 52%, which are, to the best of our knowledge, better than the current state of the art.Comment: 11 pages, 9 figures, 5 table