Quantitative Methods for Economics and Finance

This book is a collection of papers for the Special Issue “Quantitative Methods for Economics and Finance” of the journal Mathematics. This Special Issue reflects on the latest developments in different fields of economics and finance where mathematics plays a significant role. The book gathers 19 papers on topics such as volatility clusters and volatility dynamic, forecasting, stocks, indexes, cryptocurrencies and commodities, trade agreements, the relationship between volume and price, trading strategies, efficiency, regression, utility models, fraud prediction, or intertemporal choice

Essays in empirical asset pricing with machine learning

This thesis consists of four papers on topics in empirical asset pricing with a particular focus on applications of machine learning. The first paper investigates the interplay of predictable trading behaviour and asset prices. We show that predictable order ow is associated with improved liquidity and market efficiency. In addition, we find evidence for a priced factor constructed from order ow predictability, contributing to the literature that connects market microstructure features and asset prices. The second paper evaluates the efficacy of machine learning based forecasts of bond excess returns and contributes to a better understanding of the formation of bond risk premia. We show that machine learning techniques outperform the principal components benchmarks used in extant literature and deliver substantial economic gains to investors. The third paper investigates the risk-reward trade-off in index options through the lens of a factor modelling approach. We show that a factor model with five factors and time-varying loadings instrumented with option characteristics, explains the vast majority of variation in delta-hedged option returns. The recovered factors point to jump, volatility and term structure spread risks. Finally, the fourth paper studies the systematic drivers of asset holdings in a novel factor modelling approach. I document the existence of a factor structure in holdings changes that points to distinct, well-understood economic channels as drivers of asset holdings. Using investor-specific factor loadings I find evidence for pro-cyclical trading of banks and mutual funds as well as counter-cyclical trading of investment advisors and pension funds. Furthermore, I document that changes to institutional investor holdings driven by systematic factors are negatively associated with future returns, suggesting a price pressure channel as a driver for return reversals

An assessment of UK banking liquidity regulation and supervision

This thesis assesses UK banking liquidity regulation and supervision and the Basel liquidity requirements, and models banks' liquidity risk. The study reveals that the FSA's risk-assessment framework before 2008 was too general without specifically considering banks' liquidity risk (as well as its failures on Northern Rock). The study also lists the limitations of the FSA's banking liquidity regimes before 2008. The thesis reviews whether the FSA's new liquidity regimes after 2008 would have coped with UK banks' liquidity risks if they have been applied properly. The fundamental changes in the FSA's liquidity supervision reflect three considerations. First, it introduces a systemic control requirement by measuring individual fifirm's liquidity risk with a market-wide stress or combination of idiosyncratic and market-wide stresses. Second, it emphasizes the monitoring of business model risks and the capability of senior managers. Third, it allows both internal and external managers to access more information by increasing the liquidity reporting frequencies. The thesis also comments on the Basel Liquidity Principles of 2008 and the two Liquidity Standards. The Principles of 2008 represents a substantial revision of the Principles of 2000 and reflect the lessons of the fifinancial market turmoil since 2007. The study argues that the implementation of the sound principles by banks and supervisors should be fexible, but also need to be consistent to make sure they understand banks' liquidity positions quite well. The study also explains the composition of the Basel liquidity ratios as well as the side effect of Basel liquidity standards; for example, it will reshape interbank deposit markets and bond markets as a result of the increase in demand for `liquid assets' and `stable funding'. This thesis uses quantitative balance sheet liquidity analysis, based upon modified versions of the BCBS (2010b) and Moody's (2001) models, to estimate eight UK banks' short and long-term liquidity positions from 2005 to 2010 respectively. The study shows that only Barclays Bank remained liquid on a short-term basis throughout the sample period (2005-2010); while the HSBC Bank also proved liquid on a short-term basis, although not in 2008 and 2010. On a long-term basis, RBS has remained liquid since 2008 after receiving government support; while Santander UK also proved liquid, except in 2009. The other banks,especially Natwest, are shown to have faced challenging conditions, on both a short-term and long-term basis, over the sample period. This thesis also uses the Exposure-Based Cash-Flow-at-Risk (CFaR) model to forecast UK banks' liquidity risk. Based on annual data over the period 1997 to 2010, the study predicts that by the end of 2011, the (102) UK banks' average CFaR at the 95% confidence level will be -£5.76 billion, Barclays Bank's (Barclays') CFaR will be -£0.34 billion, the Royal Bank of Scotland's (RBS's) CFaR will be -£40.29 billion, HSBC Bank's (HSBC's) CFaR will be £0.67 billion, Lloyds TSB Bank's (Lloyds TSB's) CFaR will be -£4.90 billion, National Westminister Bank's (Natwest's) CFaR will be -£10.38 billion, and Nationwide Building Society's (Nationwide's) CFaR will be -£0.72 billion. Moreover, it is clear that Lloyds TSB and Natwest are associated with the largest risk, according to the biggest percentage difference between downside cash flow and expected cash flow (3600% and 816% respectively). Since I summarize a bank's liquidity risk exposure in a single number (CFaR), which is the maximum shortfall given the targeted probability level, it can be directly compared to the bank's risk tolerance and used to guide corporate risk management decisions. Finally, this thesis estimates the long-term United Kingdom economic impact of the Basel III capital and liquidity requirements. Using quarterly data over the period 1997:q1 to 2010:q2, the study employs a non-linear-in-factor probit model to show increases in bank capital and liquidity would reduce the probability of a bank crisis significantly. The study estimates the long-run cost of the Basel III requirements with a Vector Error Correction Model (VECM), which shows holding higher capital and liquidity would reduce output by a small amount but increase bank profitability in the long run. The maximum temporary net benefit and permanent net benefit is shown to be 1.284% and 35.484% of pre-crisis GDP respectively when the tangible common equity ratio stays at 10%. Assuming all UK banks also meet the Basel III long-term liquidity requirements, the temporary net benefit and permanent net benefit will be 0.347% and 14.318% of pre-crisis GDP respectively. Therefore, the results suggest that, in terms of the impact on output, there is considerable room to further tighten capital and liquidity requirements, while still providing positive effects for the United Kingdom economy

Sunshine trading and its impact on market transparency

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The drivers of Corporate Social Responsibility in the supply chain. A case study.

Purpose: The paper studies the way in which a SME integrates CSR into its corporate strategy, the practices it puts in place and how its CSR strategies reflect on its suppliers and customers relations. Methodology/Research limitations: A qualitative case study methodology is used. The use of a single case study limits the generalizing capacity of these findings. Findings: The entrepreneur’s ethical beliefs and value system play a fundamental role in shaping sustainable corporate strategy. Furthermore, the type of competitive strategy selected based on innovation, quality and responsibility clearly emerges both in terms of well defined management procedures and supply chain relations as a whole aimed at involving partners in the process of sustainable innovation. Originality/value: The paper presents a SME that has devised an original innovative business model. The study pivots on the issues of innovation and eco-sustainability in a context of drivers for CRS and business ethics. These values are considered fundamental at International level; the United Nations has declared 2011 the “International Year of Forestry”

Social contagion and asset prices: Reddit’s self-organised bull runs

This paper develops an empirical and theoretical case for how 'hype' among retail investors can drive large asset price fluctuations. We use text data from discussions on WallStreetBets (WSB), an online investor forum with over eleven million followers as of February 2022, as a case study to demonstrate how retail investors influence each other, and how social behaviours impact financial markets. We document that WSB users adopt price predictions about assets (bullish or bearish) in part due to the sentiments expressed by their peers. Discussions about stocks are also self-perpetuating: narratives about specific assets spread at an increasing rate before peaking, and eventually diminishing in importance - a pattern reminiscent of an epidemiological setting. To consolidate these findings, we develop a model for the impact of social dynamics among retail investors on asset prices. We find that the interplay between 'trend following' and `consensus formation' determines the stability of price returns, with socially-driven investing potentially causing oscillations and cycles. Our framework helps identify components of asset demand stemming from social dynamics, which we predict using WSB data. Our predictions explain significant variation in stock market activity. These findings emphasise the role that social dynamics play in financial markets, amplified by online social media

Animal Spirits and Extreme Confidence: No Guts, No Glory?

This study investigates to what extent extreme confidence of either management or security analysts may impact financial or operating performance. We construct a multidimensional degree of company confidence measure from a wide range of corporate decisions. We empirically test this measure for large US companies from 1980 -2008 and find significantly different company and performance characteristics between confidence extremes. Diffident firms tend to be smaller, more distressed, less conservatively financed and, except for the new millennium, yield a lower return on invested capital with higher variability. When adjusting stock returns for risk, the performance differences prior to moving to extreme confidence become even more pronounced. Extreme confidence could also distort earnings forecasts as analyst may overly rely on an anchor or make insufficient adjustments. Innate bias, anchoring to prior year earnings, risk attitude and responses to recent news are conditional on the level of analysis. Innate optimism prevails on the industry and analyst level. We find no support for anchoring by analysts with a long track record or across industries, which suggests a bottom-up approach. Long-term risk is considered as upside and short-term risk as downside potential. There is also a tendency to underreact to news, the extent of which seems conditional on the direction

Trading in chaos : analysis of active management in a fractal market.

Doctor of Philosophy in Finance. University of KwaZulu-Natal, Durban 2017.Many Nobel Laureates and thousands of academic papers have espoused the concept that risk is compensated by return. However, the low volatility anomaly - the phenomenon where low-risk stocks display markedly higher returns than the market portfolio on a risk-adjusted basis and vice versa - contradicts this basic finance principle of risk-return trade-off and is possibly one of the greatest anomalies in finance. Among the explanations for this anomaly are, the behavioural bias of overconfidence, agency problems and the type of manager compensation. This study investigates and confirms the low volatility anomaly on the Johannesburg Stock Exchange (JSE) using the risk-adjusted return measure of the Sharpe ratio. According to the Efficient Market Hypothesis, this is not expected to happen and consequently offers no explanation for this phenomenon. This study applies the Fractal Market Hypothesis (FMH) formalised within the framework of Chaos Theory, to explain the existence of the low volatility anomaly on the JSE. Building upon the Fractal Market Hypothesis to provide evidence on the behaviour of returns time series of selected indices of the JSE, the BDS test is applied to test for non-random chaotic dynamics and further applies the rescaled range analysis to ascertain mean reversion, persistence or randomness on the JSE. The BDS test confirms that all the indices considered in this study are not independent and identically distributed. Applying the re-scaled range analysis, the FTSE/JSE Top 40 and the FTSE/JSE All Share Index appear relatively efficient and riskier than the FTSE/JSE Small Cap Index, which exhibits significant persistence and appears to be less risky and less efficient contrary to the popular assertion that small cap indices are riskier than large cap indices. The study further analyses the three fundamentals of the FMH namely, the impact of information, the role of liquidity and time horizon on the top 40 and small cap indices. Information is not uniformly distributed among the two indices as the FTSE/JSE Top 40 index receives more publications form sources such as newspapers, online publications and journals as well as JSE issued news and historical company news. The FTSE/JSE Top 40 also receives more analyst coverage than the FTSE/JSE Small Cap Index. Using the absolute and normalised volume of trade as a proxy for liquidity, the FTSE/JSE Top 40 index exhibits a relatively higher level of liquidity than the FTSE/JSE Small Cap index. The study finds that domestic equity fund managers in South Africa hold in their portfolios, a disproportionately greater percentage of FTSE/JSE Top 40 companies relative to other companies on the JSE and concludes that these managers contribute to the low volatility anomaly on the JSE. The study further concludes that in line with the FMH, lack of information and the illiquidity of the FTSE/JSE Small Cap attracts long-term investors who become the dominant class of investors on the index and are compensated for taking on the risk of illiquidity in the form of illiquidity premium and low volatility. The highly liquid FTSE/JSE Top 40, which has relatively high availability of information on the other hand attracts different classes of investors with differing horizons who take opposite sides of each trade as different classes of investors interpret the same set of information differently. The high liquidity and information leads to high volatility as investors continually adjust their holdings with the emergence of new information. The high volatility and subsequent underperformance of the FTSE/JSE Top 40 therefore is a cost of efficiency and liquidity (liquidity discount). Studies on the FMH are generally focused on market crashes. This study provides a novel approach by using the FMH to explain the low-volatility anomaly. This synthesis of the FMH and the low volatility anomaly provides an alternative technique of evaluating risk and also provides insights into the efficiency of financial markets and contributes to the literature on the FMH as well as the low volatility anomaly

Trois essais en finance empirique

This dissertation is made of three distinct chapters. In the first chapter, we introduce a new measure of herding that allows for tracking dynamics of individual herding. Using a database of nearly 8 million trades executed between 1999 and 2006 by 87,373 individual investors, we show that individual herding is persistent over time and that past performance and the level of sophistication influence this behavior. We are also able to answer a question that was previously unaddressed in the literature: is herding profitable for investors? Our unique dataset reveals that the investors trading against the crowd tend to exhibit more extreme returns and poorer risk-adjusted performance than the herders. In the second chapter, we show that measuring the accuracy of a target price is not sufficient to assess its quality, because the forecast predictability (which depends on the stock return volatility and on the forecast horizon) is likely to vary across stocks and over time. We argue that the evidence of time persistent differences in analysts' target price accuracy, obtained in previous studies, cannot be interpreted as a proof of persistent differential abilities. Our analysis indicates that the persistence in accuracy is driven by persistence in stock return volatility. We introduce a measure of target price quality that considers both the forecast inaccuracy and the forecast predictability. Using elements from option-pricing theory, we provide a simple solution to the issue of estimating target price predictability. Our empirical analysis reveals that, when forecast predictability is taken into account, financial analysts do not exhibit significant persistent differential abilities to forecast future stock prices. In the third chapter, we show that experienced financial analysts tend to cover different firms than inexperienced analysts. Experienced analysts tend to follow blue chips (i.e., large, international, mature firms) while inexperienced analysts focus on small, young, growth-oriented firms. These differences in coverage decisions imply that inexperienced analysts issue target prices on firms for which stock returns are more volatile, and thus less predictable. As a consequence, the accuracy measure of target prices fails to evaluate differences in ability between experienced and inexperienced analysts. When taking into account these differences in coverage decisions, we still find that experienced analysts do a better job at forecasting stock prices. Our results on the influence of analysts' characteristics on target price quality are statistically significant but economically weak.Cette thèse de doctorat comporte trois chapitres distincts. Dans le premier chapitre, nous étudions le comportement moutonnier d'investisseurs individuels français. Notre analyse empirique repose sur une base de données de presque 8 millions de transactions réalisées entre 1999 et 2006 par 87 373 investisseurs individuels français. Nous montrons que le comportement moutonnier persiste dans le temps et que la performance passée ainsi que le niveau de sophistication influencent ce comportement. Nous tentons également d'apporter une réponse à une question très peu abordée dans la littérature : adopter un comportement moutonnier est-il profitable pour l'investisseur individuel ? Notre analyse empirique indique que les investisseurs contrariants obtiennent des rendements plus extrêmes (positifs ou négatifs) que les investisseurs moutonniers. Dans le second chapitre, nous montrons que mesurer la précision d'une prévision du prix futur d'une action n'est pas suffisant pour évaluer la qualité de cette prévision car la prévisibilité des prix est susceptible d'évoluer dans le temps et dépend du titre considéré. Nous montrons que la persistance dans les différences individuelles de précision des prévisions d'analystes, mis en avant dans la littérature, ne constitue pas une preuve de différences de compétences entre analystes. Cette persistance est, en réalité, causée par une persistance de la volatilité de la rentabilité des titres. Nous introduisons une mesure de qualité des prévisions qui incorpore à la fois l'erreur de prévision et la prévisibilité du prix. La théorie des options nous fournit les éléments nécessaires à l'estimation de cette prévisibilité. Lorsque celle-ci est prise en compte, il n'y a plus de différences de compétences entre analystes. Dans le troisième chapitre, nous montrons que les analystes expérimentés et inexpérimentés ne couvrent pas le même type d'entreprises. Les analystes expérimentés couvrent des entreprises de type « blue chips » tandis que les analystes inexpérimentés couvrent des entreprises petites, jeunes et en croissance. Ces différences de couvertures impliquent que les analystes inexpérimentés émettent des prévisions de prix sur des entreprises dont les rendements sont plus volatils et donc moins prévisibles. En conséquence, la précision des prévisions n'est pas une bonne mesure pour évaluer si les analystes expérimentés sont meilleurs ou moins compétents que les analystes inexpérimentés. Lorsque ces différences de couvertures sont prises en compte, nous obtenons que les analystes expérimentés émettent néanmoins de meilleures prévisions. Bien que statistiquement significatif, l'impact économique de l'expérience des analystes est faible