Abstract: We construct a new systemic risk measure that quantifies vulnerability to fire-sale spillovers using detailed repo market data for broker-dealers and regulatory balance sheet data for U.S. bank holding companies. For broker-dealers, vulnerabilities in the repo market are driven by flight-to-quality episodes, when liquidity and leverage can change rapidly. We estimate that an exogenous 1 percent decline in the price of all assets financed with repos leads to losses due to fire sale spillovers of 8 percent of total broker-dealer equity on average and over 12 percent during the financial crisis. For bank holding companies, vulnerabilities to fire-sales are equally sizable but build up slowly over time. Our measure signals build-up of systemic risk starting in the early 2000s, ahead of many other measures. Our measure also predicts low quantiles of macroeconomic outcomes above and beyond other existing measures, especially at longer horizons.

Abstract: Savings accounts are owned by most households, but little is known about the performance of households’ investments. We create a unique dataset by matching information on individual savings accounts from the DNB Household Survey with market data on account-specific interest rates and characteristics. We document considerable heterogeneity in returns across households, which can be partly explained by financial sophistication. A one-standard deviation increase in financial literacy is associated with a 13% increase compared to the median interest rate. We isolate the usage of modern technology (online accounts) as one channel through which financial literacy has a positive association with returns.

Abstract: Written for undergraduate and graduate students of finance, economics and business, the third edition of Financial Markets and Institutions provides a fresh analysis of the European financial system. Combining theory, data and policy, this successful textbook examines and explains financial markets, financial infrastructures, financial institutions and the challenges of financial supervision and competition policy. The third edition features greater discussion of the financial and euro crises, including extensive analysis of their causes and impact, as well as their remedies. New material covers unconventional monetary policies, the Banking Union, the Basel 3 capital adequacy framework for banking supervision, macroprudential policies and state aid control applied to banks. The new edition also features wider international coverage, with greater emphasis on comparisons with countries outside the European Union. Visit the companion website at www.cambridge.org/de_Haan3e for password-protected PowerPoint lecture slides, solutions, figures and tables for instructors, and exercises for students.

Abstract: The California Independent System Operator (CAISO) has implemented Convergence Bidding (CB) on February 1, 2011 under Federal Energy Regulatory Commission’s September 21, 2006 Market Redesign and Technology Upgrade Order. CB is a financial mechanism that allows market participants, including electricity suppliers, consumers and virtual traders, to arbitrage price differences between the day-ahead (DA) market and the real-time (RT) market without physically consuming or producing energy. In this paper, market efficiency is defined in terms of trading profitability, where a zero-profit competitive equilibrium implies market efficiency (Jensen in, J Financial Econ 6(2):95–101, 1978). We analyze market data in the CAISO electric power markets, and empirically test for market efficiency by assessing the performance of trading strategies from the perspective of virtual traders. By viewing DA–RT spreads as payoffs from a basket of correlated assets, we can formulate a chance constrained portfolio selection problem, where the chance constraint takes two different forms as a value-at-risk constraint and a conditional value-at-risk constraint, to find the optimal trading strategy. A hidden Markov model (HMM) is further proposed to capture the presence of the time-varying forward premium. This is meant to be a contribution to the modeling of regime shifts in the electricity forward premium with unobservable states. Our backtesting results cast doubt on the efficiency of the CAISO electric power markets, as the trading strategy generates consistent profits after the introduction of CB, even in the presence of transaction costs. Nevertheless, by comparing with the performance before the introduction of CB, we find that the profitability decreases significantly, which enables us to identify the efficiency gain brought about by CB. Convincing evidence for the improvement of market efficiency in the presence of CB is further provided by the test for the Bessembinder and Lemmon (J Finance 57(3):1347–1382, 2002) model.

Abstract: Stock movements are essentially driven by new information. Market data, financial news, and social sentiment are believed to have impacts on stock markets. To study the correlation between information and stock movements, previous works typically concatenate the features of different information sources into one super feature vector. However, such concatenated vector approaches treat each information source separately and ignore their interactions. In this article, we model the multi-faceted investors' information and their intrinsic links with tensors. To identify the nonlinear patterns between stock movements and new information, we propose a supervised tensor regression learning approach to investigate the joint impact of different information sources on stock markets. Experiments on CSI 100 stocks in the year 2011 show that our approach outperforms the state-of-the-art trading strategies.

Abstract: This paper investigates the incentives market participants have in the German electricity balancing mechanism. Strategic over and undersupply positions are the result of existing stochastic arbitrage opportunities between the spot market and the balancing mechanism. Clear indications for strategic behavior can be observed in aggregate market data. These structural imbalances increase the need for reserve capacity, raise system security concerns, and therefore place significant costs on consumers. The underlying problem is the disconnect between spot market, reserve capacity market and balancing mechanism. Alternative market design options discussed in this paper suggest better alignment between these markets/mechanisms.

Abstract: In France as in many European countries, grid-connected photovoltaics (PV) took off between 2008 and 2010, driven by an overly attractive feed-in tariff scheme that failed to take into account the rapid evolutions of PV technologies and markets. This unexpected expansion of a policy-dependent market led to a moratorium on feed-in tariffs followed by a consultation with stakeholders in 2010–2011. This article analyses the build-up, explosion and resolution of this crisis by focusing on the market and political effects of feed-in tariffs in the years 2008 to 2011. The consultation is analysed as an attempt at the political organisation and representation of the emerging PV sector. The paper shows that it failed to constitute a reliable representation of it, and that the government addressed the difficulty to control the sector by closing down both the market and the political space. It concludes that the good functioning of feed-in tariffs requires work of market organisation as much as of political construction, since their regulation relies on market data and on political compromises.

Abstract: This article gives an overview of results of the market data collected in the OrganicDataNetwork project, which was funded by the European Union (EU) under ist 7th framework programme for research, demonstration and technological development and ended in 2014. Under this project, for the first time, detailed organic market data for all European countries was collected and stored in one single database, which is available online.

Abstract: This paper examines the link between financial openness and financial development through panel data analysis on advanced and emerging market countries. Using indices, financial openness together with institutional and educational variables explains a large part of the variation in financial development across countries and over time. Our analysis demonstrates that different indexing strategies serve to find better measures for financial openness and financial development in comparison with the individual indicators used in the literature. Our principal-component-type financial openness index conveys a positive effect on financial development independent from the lag structure or specifications used.

Abstract: Innovation-driven durable goods markets see substantial changes in quality and available choice sets and subsequent changes of the reference quality in the market over time. Considering the multi-attribute characteristics of these goods, it is important for businesses to identify attribute-specific competitive landscapes and develop competitive innovation strategies at the product attribute level. Therefore, this paper proposes a reference-dependent choice model for product quality at the product attribute level that can capture the asymmetric effect of innovation shocks on product demand, i.e., the innovation elasticity of demand, as well as the competitive market structure in product innovation. Moreover, we confirm that there is a certain quality span for a product attribute where the values of products depreciate most significantly due to innovation shocks, which we refer to as the innovation shadow zone. We demonstrate the effectiveness of the proposed approach in developing attribute-specific product innovation strategies using U.S. mobile telephone market data.

Abstract: been implemented in an attempt to integrate financial services into growth objectives in Nigeria. Further, the global financial crisis has illustrated the potentially disastrous consequences of weak financial sector policies for financial development and their impact on the economic outcomes. The crisis has challenged conventional thinking in financial sector policies and has led to much debate on how best to achieve sustainable development. Nigerian financial market has been noted to be one of the largest in Sub-Saharan Africa with regard to diversity of institutions and instruments (3). The Nigerian financial system can be broadly divided into two sub-sectors, namely: the informal and the formal sectors. The informal sector comprises the local money lenders, the thrifts, savings associations, etc. This component is poorly developed, limited in reach, and not integrated into the formal financial system. The formal financial system on the other hand can be further sub-divided into capital and money market institutions. It is made up of the banks and non-bank financial institutions. The system became liberalized in the 1980s when the structural adjustment program me was introduced. The system has undergone significant changes in terms of the policy environment, number of institutions, ownership structure, depth and breadth of markets, as well as in the regulatory framework. The financial system comprises of the central bank, commercial banks, mutual funds, brokerage firms, discount houses, and stock exchange, to mention just few. These institutions trade in financial instruments such as domestic currency, foreign currency,

Abstract: In complex financial systems, the sector structure and volatility clustering are respectively important features of the spatial and temporal correlations. However, the microscopic generation mechanism of the sector structure is not yet understood. Especially, how to produce these two features in one model remains challenging. We introduce a novel interaction mechanism, i.e., the multi-level herding, in constructing an agent-based model to investigate the sector structure combined with volatility clustering. According to the previous market performance, agents trade in groups, and their herding behavior comprises the herding at stock, sector and market levels. Further, we propose methods to determine the key model parameters from historical market data, rather than from statistical fitting of the results. From the simulation, we obtain the sector structure and volatility clustering, as well as the eigenvalue distribution of the cross-correlation matrix, for the New York and Hong Kong stock exchanges. These properties are in agreement with the empirical ones. Our results quantitatively reveal that the multi-level herding is the microscopic generation mechanism of the sector structure, and provide new insight into the spatio-temporal interactions in financial systems at the microscopic level.

Abstract: Zero rating, the practice of not charging data to a mobile broadband subscriber’s contract, is emerging a potent issue in telecom policy. While zero rating of mobile subscriptions has been extant for almost two decades with little to no controversy. Zero rating has become increasingly popular in both developed and developing countries and plays a particularly important role in developing countries, where the costs of mobile data services are higher relative to per capita incomes. About half of all mobile operators employ the strategy in some way. In fact network operators have used the equivalent of such strategies to incentivize both subscribers and content providers to be part of their network for well over a century. In the last two years, however, zero rating become a flashpoint in the net neutrality debate. Whether a country allows it has become a litmus test for net neutrality supporters to certify the strength of the rules. At issue is whether operators and their customers should have the freedom to create contracts for mobile broadband service based on their preferences and constraints or whether mobile Internet service must be sold in a so-called “neutral” fashion where the only differentiating parameters are speed and megabytes. As the Internet increasingly transitions to mobile platforms, and the likelihood that the next two third of world who yet to come online will do so via mobile, who and how to provision mobile bandwidth has is an important, complex issue. This paper examines the arguments for and against zero rating and the charges that zero rating hurts competition and consumers. It formulates 5 assertions based on the alleged harms and attempts to test them with empirical analysis from quantitative and qualitative perspectives. The paper reviews the leading database of financial information of the world’s mobile operators to see whether the impact of zero rating may be observed, for example with undue financial benefits earned by operators through the use of zero rating. To understand the issue more closely, the paper reviews zero rating in Chile, Netherlands, and Slovenia, countries which have banned some forms of the practice. The paper then examines whether there is harm to consumers and innovation by reviewing a leading database of mobile application market data. The paper concludes by suggesting reasons why zero rating is maligned in telecom policy debates.

Abstract: Stock price movements are claimed to be chaotic and unpredictable, and mainstream theories of finance refute the possibility of realizing risk-free profit through predictive modelling. Despite this, a large body of technical analysis work maintains that price movements can be predicted solely from historical market data, i.e., markets are not completely efficient. In this paper we seek to test this claim empirically by developing a novel stochastic trading algorithm in the form of a linear model with a profit maximization objective. Using this method we show improvements over the competitive buy-and-hold baseline over a decade of stock market data for several companies. We further extend the approach to allow for non-stationarity in time, and using multi-task learning to modulate between individual companies and the overall market. Both approaches further improve the predictive profit. Overall this work shows that market movements do exhibit predictable patterns as captured through technical analysis.

Abstract: In complex financial systems, the sector structure and volatility clustering are respectively important features of the spatial and temporal correlations. However, the microscopic generation mechanism of the sector structure is not yet understood. Especially, how to produce these two features in one model remains challenging. We introduce a novel interaction mechanism, i.e., the multi-level herding, in constructing an agent-based model to investigate the sector structure combined with volatility clustering. According to the previous market performance, agents trade in groups, and their herding behavior comprises the herding at stock, sector and market levels. Further, we propose methods to determine the key model parameters from historical market data, rather than from statistical fitting of the results. From the simulation, we obtain the sector structure and volatility clustering, as well as the eigenvalue distribution of the cross-correlation matrix, for the New York and Hong Kong stock exchanges. These properties are in agreement with the empirical ones. Our results quantitatively reveal that the multi-level herding is the microscopic generation mechanism of the sector structure, and provide new insight into the spatio-temporal interactions in financial systems at the microscopic level.

Abstract: The invention provides a marketing analysis data market system. The marketing analysis data market system comprises a data access layer, a data extraction module, a data conversion module, a data cleaning module, a log and alarm sending module and a data downloading module, a data packet of the data access layer contains office data, external data and service data, and models of the system includes a data logic model and a data physics module. Firstly, necessity in designing the marketing data market is analyzed and ETL data processing including noise data processing, data uniformity and data quality and the like is analyzed by discussing a data integration method, and various data sources can be reorganized and processed by a data transition tool. In addition, the physics model in the data market is realized according to the physic list structure of the logic model. Finally, application prospect of the data market in the marketing analysis is expected.

Abstract: This paper presents an analytical benchmark model for national intraday adjustment needs under consideration of fundamental drivers, market concentration and portfolio internal netting. The benchmark model is used to calculate the intraday market outcomes if (i) large and small players as well as transmissions operators trade and (ii) only large players and transmission system operators trade. Transaction costs may prevent the competitive fringe from intraday market participation. The theoretical national intraday trading volumes are calculated with market data from three European countries with auction-based intraday markets (Italy, Portugal, Spain) and four countries with continuous intraday markets (Denmark, France, Germany, United Kingdom). The model results allow two main conclusions: The competitive fringe is not trading on exchanges in Denmark and France but in Germany. The second conclusion is that the high observed volumes in auction-based intraday markets cannot be explained by fundamentals or the auction-based design but are mainly caused by market peculiarities. The same result applies to the UK.

Abstract: The paper investigates the relationship between foreign ownership and dividend policy of firms in the Vietnam stock market. In other words, we attempt to shed light on the following questions: 1) Are foreign investors in Vietnam stock markets more likely to choose firms that pay high dividends?; 2) Do foreign investors cause firms to increase dividends when they have substantial shareholdings in Vietnamese firms? We use a rich and detailed data set, including both market data and firm attributes from 2007 to 2012. We employ a wide range of econometric techniques for panel data analysis including fixed effects and random effects. We further use the GMM estimator to address the bias due to the endogeneity and other biases of least squared estimators. We find that foreign investors in Vietnam prefer to invest in firms that pay low dividend and when become a larger shareholder, foreign investors tend to force firm managers to pay fewer dividends and retain higher income to exploit future emerging market opportunities.

Abstract: Financial performance is one of the factors used by investors in buying shares. For companies, improving financial performance is a must in order to keep the company's stock attractive to investors. Financial statements published by the company are a reflection of the company's financial performance. These financial statements are the result of the accounting process that is intended to provide the financial information of a company. The financial information can be used by users for making investment decisions. Performance is the result of the fulfillment of the tasks assigned. Company performance describes how individualsin the company tries to achieve a goal. Company performance illustrates the magnitude of the results in a process that has been achieved compared with the company’s goal. The purpose of this study is to find out factors determining financial performance. The objects of this study are property and real estate companies listed on the Indonesia Stock Exchange (IDX) during the period of 2007 – 2012. Data for this study stems from secondary data gathered by analyzing financial statement of the sample companies. The data is then analyzed with Eviews 7.2 Panel Data Regression Analysis. The research findings can be summarized as follows. Variable leverage and Firm Age has an effect on financial performance. Other variables like liquidity, Firm Size, Managerial Ownership and Block holder Ownership have no effect on financial performance. JEL Classification code: G31

Abstract: Information technology service providers bid on high valued services deals in a competitive environment. To price these deals, the traditional bottom up approach is to prepare a complete solution, i.e., know the detailed services to be offered to the client, find the exact costs of these services, and then add a gross profit to reach the bidding price. This is a very time consuming and resource intensive process. There is a business need to get quick (agile) early estimates of both cost and price using a core set of high level data for the deal. In this paper, we develop a two-step top down approach for doing this. In the first step, we mine historical and market data to come up with estimates on the cost and price. We provide some numerical results based on industry data that statistically shows that there is a benefit of using historical data in this step beside the traditional way of using market data. Because the bidding price is not the sole factor affecting the chances of winning a deal, we then enter the different price points in a predictive analytics model (step two) to calculate the relative probability of winning the deal at each point. Such probabilities with the corresponding prices can provide significant insights to the business helping them reach quick reliable pricing.

Abstract: The positive relation between stock price changes and trading volume (price–volume relationship) as a stylized fact has attracted significant interest among finance researchers and investment practitioners. However, until now, consensus has not been reached regarding the causes of the relationship based on real market data because extracting valuable variables (such as information-driven trade volume) from real data is difficult. This lack of general consensus motivates us to develop a simple agent-based computational artificial stock market where extracting the necessary variables is easy. Based on this model and its artificial data, our tests have found that the aggressive trading style of informed agents can produce a price–volume relationship. Therefore, the information spreading process is not a necessary condition for producing price–volume relationship.

Abstract: We examine whether a particular put-call ratio, derived from a unique set of market data, can be used to predict directional moves in asset prices during various market conditions between March 2005 and December 2012. Our findings show: 1) specific market participant option trading volume is shown to be a predecessor to asset price movements; 2) portfolios adjusted for risk, momentum and transaction costs exhibit abnormal excess returns. These findings suggest that short positions of a specific market participant improve the overall performance of a given portfolio.

Abstract: This study empirically investigates the impacts of the financial derivative usage on corporate debt capability and stock return using Korean non-financial firms’ data from 2002 to 2012. Empirical results support the conjecture that financial derivatives tend to increase debt capability by transferring risks and reducing financial cost. Derivative user firms turn out to have better stock market performance especially during period with the tight credit market. Unexpected contractionary monetary policy is negatively correlated with corporate stock return and the negative relationship becomes more significant in case of the derivative non-user firms. Financial derivatives usage of the individual firm plays an important role in increasing debt capability and achieving better stock performances.

Abstract: The Linked Data movement has facilitated efficient data sharing in many domains. However, people in rural developing areas are mostly left out. Lack of relevant content and suitable interfaces prohibit potential users in rural communities to produce and consume Linked Data. In this paper, we present a case study exposing locally produced market data as Linked Data, which shows that Linked Data can be meaningful in a rural, development context. We present a way of enriching the market data with voice labels, allowing for the development of applications that (re-)use the data in voice-based applications. Finally, we present a prototype demonstrator that provides access to this linked market data through a voice interface, accessible to first generation mobile phones.

Abstract: Introduction to the Theories and Varieties of Modern Crime in Financial Markets explores statistical methods and data mining techniques that, if used correctly, can help with crime detection and prevention. The three sections of the book present the methods, techniques, and approaches for recognizing, analyzing, and ultimately detecting and preventing financial frauds, especially complex and sophisticated crimes that characterize modern financial markets. The first two sections appeal to readers with technical backgrounds, describing data analysis and ways to manipulate markets and commit crimes. The third section gives life to the information through a series of interviews with bankers, regulators, lawyers, investigators, rogue traders, and others. The book is sharply focused on analyzing the origin of a crime from an economic perspective, showing Big Data in action, noting both the pros and cons of this approach. Provides an analytical/empirical approach to financial crime investigation, including data sources, data manipulation, and conclusions that data can provide Emphasizes case studies, primarily with experts, traders, and investigators worldwide Uses R for statistical examples