Notes on Cloud computing principles

This letter provides a review of fundamental distributed systems and economic Cloud computing principles. These principles are frequently deployed in their respective fields, but their inter-dependencies are often neglected. Given that Cloud Computing first and foremost is a new business model, a new model to sell computational resources, the understanding of these concepts is facilitated by treating them in unison. Here, we review some of the most important concepts and how they relate to each other

Short-term Risk Management for Electricity Retailers Under Rising Shares of Decentralized Solar Generation

Electricity retailers face increasing uncertainty due to the ongoing expansion of unpredictable, distributed generation in the residential sector. We analyze how increasing levels of households\u27 solar PV self-generation affect the short-term decisionmaking and associated risk exposure of electricity retailers in day-ahead and intraday markets. First, we develop a stochastic model accounting for correlations between solar load, residual load and price in sequentially nested wholesale spot markets across seasons and type of day. Second, we develop a computationally tractable twostage stochastic mixed-integer optimization model to investigate the trading portfolio and risk optimization problem faced by retailers. Through conditional value-at-risk we assess retailers\u27 profitability and risk exposure to different levels of PV self-generation by assuming different retail tariff schemes. We find risk-hedging trading strategies and tariffs to have greater impact in Summer and with low levels of residual load in the system, i.e. when the solar generation uncertainty affect more the households demand to be served and the wholesale spot prices. The study is innovative in unveiling the potential of dynamic electricity tariffs, which are indexed to spot prices, to sustain a high penetration of renewable energy source while promoting risk sharing between customer and retailer. Our findings have implications for electricity retailers facing load and revenue risks in wholesale spot markets, likewise for regulators and policy-makers interested in electricity market design

Decision-making under uncertainty in short-term electricity markets

In the course of the energy transition, the share of electricity generation from renewable energy sources in Germany has increased significantly in recent years and will continue to rise. Particularly fluctuating renewables like wind and solar bring more uncertainty and volatility to the electricity system. As markets determine the unit commitment in systems with self-dispatch, many changes have been made to the design of electricity markets to meet the new challenges. Thereby, a trend towards real-time can be observed. Short-term electricity markets are becoming more important and are seen as suitable for efficient resource allocation. Therefore, it is inevitable for market participants to develop strategies for trading electricity and flexibility in these segments. The research conducted in this thesis aims to enable better decisions in short-term electricity markets. To achieve this, a multitude of quantitative methods is developed and applied: (a) forecasting methods based on econometrics and machine learning, (b) methods for stochastic modeling of time series, (c) scenario generation and reduction methods, as well as (d) stochastic programming methods. Most significantly, two- and three-stage stochastic optimization problems are formulated to derive optimal trading decisions and unit commitment in the context of short-term electricity markets. The problem formulations adequately account for the sequential structure, the characteristics and the technical requirements of the different market segments, as well as the available information regarding uncertain generation volumes and prices. The thesis contains three case studies focusing on the German electricity markets. Results confirm that, based on appropriate representations of the uncertainty of market prices and renewable generation, the optimization approaches allow to derive sound trading strategies across multiple revenue streams, with which market participants can effectively balance the inevitable trade-off between expected profit and associated risk. By considering coherent risk metrics and flexibly adaptable risk attitudes, the trading strategies allow to substantially reduce risk with only moderate expected profit losses. These results are significant, as improving trading decisions that determine the allocation of resources in the electricity system plays a key role in coping with the uncertainty from renewables and hence contributes to the ultimate success of the energy transition

Do police crackdowns disrupt drug cryptomarkets? a longitudinal analysis of the effects of Operation Onymous

In recent years, there has been a proliferation of online illicit markets where participants can purchase and sell a wide range of goods and services such as drugs, hacking services, and stolen financial information. Second-generation markets, known as cryptomarkets, provide a pseudo-anonymous platform from which to operate and have attracted the attention of researchers, regulators, and law enforcement. This paper focuses on the impact of police crackdowns on cryptomarkets, and more particularly on the impact of Operation Onymous, a large-scale police operation in November 2014 that targeted many cryptomarkets. Our results demonstrate that cryptomarket participants adapt to police operations and that the impact of Operation Onymous was limited in time and scope. Of particular interest is the finding that prices did not increase following Operation Onymous, even though many dealers retired shortly after it occurre

The emergence of the fintech industry in China: An evolutionary economic geography perspective

Over the last decade, the global economy has rapidly becoming digited. Digital technologies have transformed the economy and society, affecting all sectors of activity around the world. Among them, the financial sector is one of the most digitalized sectors, and the term ‘fintech’ is coined to describe the digitalization of the financial sector. Although the global fintech landscape is currently geographically concentrated in the United States and Europe, the pace of China’s fintech development has been dramatically accelerated. However, it is quite surprising that there is hardly any study that investigates fintech in China from a subnational scale. To fill this gap, this dissertation conducts a city-level analysis of the emergence of the fintech industry in China. Theoretically, I position this dissertation within the broad literature on evolutionary economic geography (EEG), which has emerged as one of the main paradigms in economic geography. This dissertation aims to provide a comprehensive understanding of the emergence of the new industry in regions. Conventional wisdom in EEG posits that new industry in regions tends to grow out of technologically related pre-existing industries. However, this conventional understanding is somewhat technology-centric. In response, this dissertation extends the scholarly work from technology-centric to embrace the role of the demand-side market and institutional logic in the emergence of the new industry in regions. It proposes that not only supply-side technology but also demand-side market and institutional logics matter for the emergence of the new industry in regions. Moreover, this dissertation ascribes the underlying logic of how technology, market, and institutional logics matter to the agentic processes of asset modification, particularly redeploying pre-existing assets and creating new assets. In other words, the emergence of the new industry in regions results from relevant regional actors’ purposeful actions in terms of modifying technological, market, and institutional assets. Methodologically, there is a dualism in evolutionary economic geography research between qualitative and quantitative work. To seek a methodology integration, this dissertation proposes the mixed-method that is composed of four concrete approaches, namely the triangulation approach, the embedded approach, the sequential exploratory approach, and the sequential explanatory approach. Among these concrete approaches, the embedded approach is utilized in empirical work. The embedded approach in this dissertation refers to the embedding of the qualitative case study (which deals with the ‘how’ questions) into quantitative research (which deals with the ‘whether and to what extent’ questions). Empirically, this dissertation first examines the emergence of fintech industries in China’s cities based on the quantitative regression analysis (mainly dealing with the ‘whether and to what extent’ questions) and then zooms in on the city of Shenzhen, which is the largest fintech hub in southern China, based on the qualitative case study (mainly dealing with the ‘how’ questions). The findings are as follows. (1) Based on a unique dataset from 2003 – 2019, this dissertation provides a city-level analysis of the fintech industry in China. The econometric results show that fintech industries tend to emerge in cities that have more fintech-related technologies, particularly in the fields of finance, e-commerce, data sciences, and security. This confirms the principle of technological relatedness. Moreover, it finds a positive relationship between the development of the fintech industry and the demand for fintech services. To the best of my knowledge, this is the first systematic evidence of the significant positive role of the demand-side market in the emergence of the new industry in regions. (2) In order to uncover the underlying processes (the question of ‘how’) that lead to the above significantly positive effect, this dissertation resorts to the qualitative case study. The case study shows that the rise of Shenzhen’s fintech industry mainly grows out of Shenzhen’s pre-existing internet and financial industry. By systematically comparing the processes that internet and financial industry diversify into the fintech industry, it finds that the emergence of the fintech industry in Shenzhen result from internet and financial firms’ purposeful actions in terms of redeploying their pre-existing technologies, market, and institutional logics, as well as creating the new ones that are necessary for fintech but are missing for the internet or financial firms. In other words, it is the processes of asset modification, particularly redeploying pre-existing assets and creating new assets, that give rise to the birth of the fintech industry, leading to the positive relationships found in the quantitative regression analysis

2020 Media Futures

What will our media and entertainment be like in 2020

Convincing different risk characteristic individuals to provide their solar panel electricity generation to the electricity grid

Abstract. Solar availability in Finland is abundant but the effective use by the public is minimal. This thesis is to go forth and explain the benefits of solar energy but also demonstrate the financial prospects for this venture. Due to the plethora of options of this subject can be explored, this thesis paper will observe individual’s decisions with different risk characteristics. The decisions made by the different risk characteristics will be explained and how to motivate them to follow through a certain decision will be discussed. This will be done through theories and data that serve to enhance the decision making of these individuals. An insight to some theories used is Choice theory, Game Theory, and Contract theory. These theories have been explored in different research papers separately and have done with extensive research. Taking from those examples and combing them in this thesis gives a better understanding into the decision making of an individual. Previous research papers are key as the knowledge gained will become the backbone of this thesis paper. The point of this master thesis is to not provide a critical analysis on previous research papers but, to aid the progression of solar energy in Finland and suggest a potential solution that is found in these theories and data. This solution can help to increase the activity of solar panel as this type of energy is qualified for a pareto improvement. Solar energy can play a crucial role in Finland, and it starts with the individual

Crummer SunTrust Portfolio Recommendations: Crummer Investment Management [2014]

On balance, we believe the market will move modestly higher in the short-term. As we believe the economy is still recovering, we recommend over weighting the portfolio in cyclical sectors and underweighting countercyclical sectors. Like all soothsayers, we can only hope our glass is half‐full