1,720,998 research outputs found
A Mobile Computing Based Tool for Low-Emission Driving
No full textMargaritis, Dimitris/0000-0001-5056-1170; Dimokas, Nikos/0000-0003-2856-0969Recent advances in communications and mobile computing boosted the green mobility. Mobile Computing is the ability to provide computing technology in mobile environments while Green mobility aims to reduce vehicle emissions. The paper introduces a tool consisting of a mobile application and an information system that aims to collect and analyse the user's driving style, with a specific focus on emission reduction. To achieve that, relevant user information such as accelerometer, gyroscope, location and on-board diagnostics data are being collected transparently and continuously for the sake of developing the driving assistance tool for low-emission driving. Based on the collected information and a scoring algorithm, the user's driving style is analysed in real time and transcribed in a score. The proposed tool provides recommendations to the drivers when the score is bad and aggregated data to the authorities. The tool offers straightforward recommendations, while the driver is on the way, that can lead to prevention of high-emission driving styles by providing immediate corrective actions. As opposed to that, the information system stores and analyses the driving data that have been gathered to generate a post-driving dashboard for the authorities to monitor overall the driving behaviour and vehicle emissions. The tool has been tested thoroughly and the results indicate a robust performance.European Commission [815189]Research supported by MODALES project [20] that is funded by the European Com-mission under the Grant Agreement 815189
Essays on Banking Efficiency and Shadow Pricing
No full textThe Chinese banking sector has faced more challenges since the economic growth slowed down, threatening the stability of the financial system. The amount of non-performing loans surged from 428 billion to 2.03 trillion yuan between 2011 and 2018. At the same time, many small rural and city banks have encountered liquidity issues. Therefore, Chinese regulators have encouraged banks to resolve bad loans and to increase equity capital. This research investigates the bad loans problems and the cost of complying with stricter capital requirements in the Chinese banking industry. There are three chapters in this thesis. The first chapter estimates the shadow price (opportunity cost) of non-performing loans of Chinese commercial banks from 2011 to 2017 by applying a directional distance function and the duality theory. This approach mainly uses information on input and output quantities without the need to obtain the market price of non-performing loans. The results show that the average shadow price of non-performing loans of Chinese banks is 2.45% in terms of foregone lending, and government-controlled banks have the lowest cost of reducing bad loans. The second chapter advances the study of bad loans by investigating the determinants of the shadow price of non-performing loans from both macroeconomic and bank-specific aspects. It uses a fixed-effects estimation model, and the results demonstrate that the shadow price of non-performing loans of Chinese commercial banks is mainly affected by the growth rate of GDP, interest rates, bank size and the lagged cost of equity. Finally, the third chapter estimates the cost of equity of Chinese banks from 2013 to 2019. I employ a similar method used in the first chapter because this approach does not require the market price of equity. This is important because only 1.5% Chinese banks are listed. The results show that the shadow cost of equity is 2.19% at the sample mean. I also find that most banks in my sample have been deleveraging, and politically connected banks have lower costs of equity than their non-politically connected counterparts
Mutual Fund Herding, Customer Satisfaction and Firm Risk
No full textThis thesis comprises three empirical studies on mutual fund herding and the impact of customer satisfaction on firm risk. The first chapter introduces mutual fund contrarian behaviour - going against the market trend - as a broader measure of skill or anti-herding behaviour that is going against peer mutual funds. The results show that mutual fund managers are skilful in contrarian-buy practice but fail to add value through contrarian-sell. The asymmetric effect weakens during recessions and disappears when market sentiment is low.
With the increasing interest in corporate social responsibility, firms, investors, and financial intermediaries have switched their attention to Environmental, Social, and Governance (ESG-related) investing approaches. As mutual funds tend to herd into ‘hot’ investment styles, the second and third chapters shift the focus toward social factors in the product market and examine how they influence firm risk and mutual fund herding behaviour. In particular, the second chapter takes a closer look at customer satisfaction with companies’ products and examines how this product market value transfers to the financial market. This study shows that firms with higher customer satisfaction are associated with lower future stock crash risk, and that two possible channels contribute to this negative relationship. One is through lowering the stock price's volatility feedback effect, and the other is through reducing the differences of opinion among investors.
Finally, the third chapter combines the first and second studies by looking at how customer satisfaction influences mutual funds herding behaviour. The results show that a higher level of customer satisfaction is associated with less mutual fund herding. The results further indicate that customer satisfaction reduces mutual fund herding by increasing the firm’s information transparency and thus decreasing investor search costs. This finding is consistent with the information cascade theory that mutual funds will reduce herding if their private search
costs are lower than the cost of following the herd. However, the findings do not support the view that customer satisfaction reduces mutual fund herding through mitigating managers’ career concerns
Essays on Bank Spatial Competition, Stability and Resolution
No full textThis thesis empirically examines bank spatial competition, stability, and resolution. It is comprised of three empirical studies that investigate risk-return dynamics from three different aspects within the rural banking setting of Indonesia from 2014 to 2018. The specific focus is on bank performance, regional finance, shadow prices of equity capital, and cost efficiency. The first chapter presents a new competition measure based on two spatial variables: physical distances and Thiessen polygon market boundaries. The results show that spatial competition significantly affects profitability. I also find bank efficiency is higher for shorter distances between banks and larger boundaries. Further evidence using the Lerner index suggests that banks exert some pricing power, which is consistent with the monopolistically competitive structure of the industry. The second chapter investigates spatial competition and bank stability, using a spatial autoregressive model (SAR) with spatial spillover (contagion) constructed by weight matrices based on the inverse distance between a bank and its neighbouring banks. The results show a positive relationship between bank stability and market power, which supports the competition-fragility hypothesis. These results are robust following the use of GMM and 2SLS estimation of the SAR model to overcome endogeneity issues. In conclusion, the evidence supports the hypothesis that rural bank stability depends on the level of the spatial lag and competition from neighbouring banks. The final essay explores bank resolution and the shadow price of bank equity capital. The novel result of the study is that the shadow cost of capital serves as an indicator of the recovery rate. This is based on the presumption that deterioration of the quality of the bank’s assets portfolio will raise the cost of capital, effectively raising its shadow price. I also find that more efficient banks are associated with higher recovery rates, and that higher capital adequacy ratios are associated with less risk-taking. Furthermore, I examine the role of the shadow price of deposits and bank efficiency on deposit insurance. I conduct principal components analysis (PCA) to combine four types of risks to calculate the risk-based deposit premium. The rate varies from 0.146 percent to 0.423 percent. Thus, the results suggest that the deposit premium charged by the Indonesia Deposit Insurance Corporation (IDIC) does not reflect the cost to the IDIC. I also find that banks exploit an implicit deposit insurance subsidy
Bank Pricing Behaviour, Market Structure and Financial Stability
No full textThis thesis is an investigation into ‘size’ as an industry specific risk factor for bank stock returns, and ‘scale’ as in economies of scale and market structure, and their implications therein for government regulation and financial stability. The focus is on the "too big to fail" phenomenon which suggests that larger banks benefit from an implicit "too big to fail" subsidy rendering them seemingly less risky than their smaller counterparts. Attention is paid to the effects of regulatory responses, like the Dodd-Frank Act, imposing more stringent restrictions on larger systemically important banks. Similar dynamics played out in Europe are reflecting macroprudential policymaker concerns towards "too big to fail" banks.
First, I construct an industry specific size factor for bank stock returns through principal component analysis (PCA), utilising the residuals from size-sorted decile portfolio regressions. The second principal component closely resembles a size factor, mirroring the pattern observed in expected risk adjusted returns. The empirical findings suggest that the newly constructed factor captures most of the size anomaly observed in bank returns. These findings are robust for both samples of US and European banks.
Second, I examine whether the observed stock returns size anomaly can be attributed to economies of scale rather than an implicit "too big to fail" subsidy. To address this point, I introduce a new measure of scale elasticity based on proximity to the most productive scale size frontier. I argue that a most-productive-scale benchmark is consistent with a notion of optimal regulatory size. I find that a long-short position that goes long in a portfolio of the largest market capitalisation banks in decile 10 and short in a portfolio of the smallest market capitalisation banks in decile 1 results in significant risk-adjusted losses. Such differences no longer appear after portfolio returns are adjusted for a bank-specific risk factor. Further evidence indicates that controlling for scale economies does not fully address the size anomaly.
Third, I investigate potential bias in the estimated risk premia for stock returns in the presence of omitted factors utilising the three-pass approach of Giglio and Xiu (2021). The idea here is to reassess evidence for an implicit "too big to fail" subsidy that is robust irrespective of whether all relevant factors that span the stock returns space are specified or observed. I use PCA to span the entire factor space of bank returns in a way that controls for arbitrarily rotated factors, and additional regressions to obtain the ‘bias corrected’ risk premium of the observed factors. In essence, the proposed procedure is a factor-augmented version of the more familiar Fama-Macbeth two-pass procedure for the estimation of asset risk premia. The evidence indicates that adjusting for potential bias in the estimation of the risk premium does not reconcile the size anomaly.
Fourth, I explore the underlying causes of the changes in industry concentration applying dynamic power laws distributions in which the distribution of bank assets is modelled by two industry specific measures: mean reversion and idiosyncratic volatility for different size-ranked banks. I pay particular attention to the effects of regulatory responses to the Global Financial Crisis by assessing rank-dependent changes in idiosyncratic asset volatility and cross-sectional mean reversion.
Fifth, I construct two measures of industry specific market power capturing deviations from competitive behaviour in the market for inputs (customer deposits) and outputs (loans). Specifically, I adopt a theoretical framework for the study of market power encompassing complete characterisations of technology in the form of distance functions in the quantity space and their value duals, the cost, revenue, and profit functions. I rely on the duality between the output distance function and the revenue function to derive the monopsony version of the Lerner index, and the duality between the cost function and the input distance function to derive the monopoly version of the Lerner Index. I find that riskier banks and those that rely more on deposits to fund their assets exert less monopsony power for deposits. Bank profitability on the other hand is positively associated with monopsony power. The evidence from the monopoly power model suggests that increasing competitive pressures force banks to improve their cost efficiency, improve asset quality, and improve profitability with more reliance on interest income. Overall, the results on either side of the market provide prima facie support for the Hicksian ‘quite life’ hypothesis
Financial Event Prediction using Machine Learning
No full textFinancial machine learning (FinML) has in recent years developed into a subdiscipline in
its own right with enthusiastic experimenters at its helm. Since investigating the subject five years
ago, there has been an almost exponential progress in academic interest. When I first started
thinking about machine learning in finance, formal research was sparse, to say the least. As a
result, I have had the luxury to pick from a broad range of topics and decided to investigate
financial event prediction using machine learning, giving rise to the eponymous title.
FinML research can loosely be divided into four streams. The first concerns asset price
prediction where researchers attempt to predict the future value of securities using machine
learning methodologies. The second stream involves predicting hard or soft financial events like
earnings surprises, corporate defaults, and mergers and acquisitions. The third stream entails the
prediction and or estimation of values not directly related to the price of a security, such as future
revenue, firm valuation, credit ratings, etc. The fourth and last stream comprises the use of
machine learning techniques to solve traditional optimisation problems in finance like optimal
execution and the optimal construction of portfolios.
This thesis, in particular, focuses on the use of machine learning in financial event
prediction. In the past, finance academics had to be content with mostly linear models that could
only ingest a small number of variables of a particular type. Now we can use non-linear models
with a larger number of variables and more versatile data types. In this thesis, I show how machine
learning can lead to significant improvements in financial event prediction, more specifically, in
earnings surprise, bankruptcy and facility closure predictions, all of which have significant
financial implications for the businesses and stakeholders alike
Financial Globalization, Shadow Banking and Interest Rate Transmission: Evidence from China
No full textMany long-held views about the global financial system and the effectiveness of monetary policy have been questioned since the Global Financial Crisis (GFC) of 2007/2009. At stake is the capacity of monetary authorities to isolate international monetary policy shocks under financial globalization coupled with the rapid development of shadow banking and its impact on the banking system and monetary policy transmission. This thesis comprises three empirical studies to examine these issues by providing evidence from China. The first study investigates the international transmission of monetary policy from the U.S. to China. The results show that the spillover effects of U.S. monetary policy are significant and strong on China's short-term interest rates after the GFC. The spillover at the long-end of the yield curve even holds before the GFC, but only for positive changes in U.S. long-term interest rates. By comparing the results with countries under flexible exchange rates such as New Zealand, I find a fixed exchange rate regime with capital controls helps to mitigate more effectively external monetary shocks especially during a turmoil period. The second study shifts the focus on the driving forces of the rise of shadow banking in China. Aside from micro arbitrage factors suggested by previous literature, I paid specific attention to a wide range of macro-finance factors. To reflect the unique institutional features that shape macroeconomic policy making in China, I introduce a novel identification strategy to isolate pure monetary policy shocks from the influence of other macroeconomic policy variations. The empirical results show robustly that China’s shadow banking is essentially driven by macro-policy factors including credit scale tightening, strengthened risky-loan regulation, and intensified interest-rate repression. In contrast, the effect of a pure monetary contraction is to reduce shadow banking, due to an economy-wide tightening of liquidity. The third essay investigates how shadow banking impacts loan pricing and the pass-through from policy rates to retail lending rates. The results show that the yield of shadow banking products impacts the lending rates positively, in which 20 percent of the impact takes effect through the deposit channel. The scale of shadow banking wealth management products (WMPs) does not significantly impact lending rates. Furthermore, the rise in shadow banking appears to have decreased the pass-through from benchmark policy rates to lending rates after 2013 by providing alternative credit options to bank loans, supporting the loan-demand side view. On the other hand, I find the effect of shadow banking on the pass-through from market-based short-term policy rates to lending rates became insignificant after 2013 as the arbitrage model shifted from the WMP-channel-shadow credit to interbank-entrustment-securities. However, China’s shadow banking appears to have significantly decreased net interest margins of banks after 2013 as the average return on financial securities invested by shadow banking is lower than on-balance loan yields
Going Beyond Counting First Authors in Author Co-citation Analysis
Full text linkThe present study examines one of the fundamental aspects of author co-citation analysis (ACA) - the way co-citation
counts are defined. Co-citation counting provides the data on which all subsequent statistical analyses and mappings
are based, and we compare ACA results based on two different types of co-citation counting - the traditional type that
only counts the first one among a cited work's authors on the one hand and a non-traditional type that takes into
account the first 5 authors of a cited work on the other hand. Results indicate that the picture produced through this non-traditional author co-citation counting contains more coherent author groups and is therefore considerably clearer. However, this picture represents fewer specialties in the research field being studied than that produced through the traditional first-author co-citation counting when the same number of top-ranked authors is selected and analyzed. Reasons for these effects are discussed
Variations on the Author
Full text link“Variations on the Author” discusses two of Eduardo Coutinho’s recent films (Um Dia na Vida, from 2010, and Últimas Conversas, posthumously released in 2015) and their contribution to the general question of documentary authorship. The director’s filmography is characterized by a consistent yet self-effacing form of authorial self-inscription: Coutinho often features as an interviewer that rather than express opinions propels discourses; an interviewer that is good at listening. This mode of self-inscription characterizes him as an author who is not expressive but who is nonetheless markedly present on the screen. In Um Dia na Vida, however, Coutinho is completely absent form the image, while Últimas Conversas, on the contrary, includes a confessional prologue that moves the director from the margins to the center of his films. This article examines the ways in which these works stand out in the filmography of a director who offers new insights into the notion of cinematic authorship
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