Fortune Favors the Bold: Evidence from an Emerging Market Bank Merger

This study analyses one of the largest and controversial mergers from the Philippine Banking sector and links it to M&A theories: Firstly, this study survey prior M&A literature to identify merger motivations, synergies and factors affecting merger outcomes. Secondly, this study conducts a case study to link prior literature to a merger in an emerging economy. This merger provides an ideal setting for a case study, subsequent links to M&A theories and generalizable lessons for future bank mergers in emerging markets. Furthermore, this study identifies key factors and steps taken by the acquiring bank management to obtain success such as doubling net income, assets and becoming the number one bank in Philippines post-merger

Big Data Analytics using Small Datasets: Machine Learning for Early Breast Cancer Detection

In US breast cancer happens to possess the highest death rate apart from lung cancer. As of 2019, on average, 1 in 8 US women (approx. 12%) would develop invasive breast cancer at some point during her life. These statistics highlight the importance of early detection for increasing the mortality of patients. In recent years, machine learning (ML) techniques begin to play a key role in healthcare, especially as a diagnostic aid. In the case of breast cancer, ML techniques can be used to distinguish between malignant and benign tumours for enabling early detection. Moreover, accurate classification can assist physicians to guide patients and prescribe relevant treatment. Given this background, the objective of this paper is to apply ML algorithms to classify breast cancer outcomes. In this study, we build a platform using Ridge, AdaBoost, Gradient Boost, Random Forest, Principle Component Analysis (PCA) plus Ridge, and Neural Network ML algorithms for early breast cancer outcome detection. As a traditional benchmark technique, we use logistic regression model to compare against our chosen ML algorithms. We utilise the Wisconsin Breast Cancer Database (WBCD) dataset (Dua and Graff 2019). Although ML is generally deployed with large datasets, we highlight their usefulness and feasibility for small datasets in this study of only 30 features. We contribute to literature by providing a platform that will enable (a) big data analytics using small datasets and (b) high accuracy breast cancer outcome classifications. Specifically, we identify most important features in breast cancer outcome classification from a wide range of ML algorithms with a small dataset. This would enable health practitioners and patients to focus on these key features in their decision making for future breast cancer tests and subsequent early detection thus reducing analysis and decision latencies. In our ML based breast cancer classification platform, the user is required to make three function calls: data pre-processor, model generator and a single test. The pre-processor cleans the raw dataset from the user by removing \u27NaN\u27 and empty values, and it follows further instructions from a configuration file. After the pre-processing, the platform can train ML models from model generator based on two inputs, a cleaned dataset and a configuration file. Model generator creates different models from different ML algorithms specified in the study and generates corresponding evaluations. As such, the user can call single test to use the generated models in making predictions

Realized volatility, GARCH models & chaos theory

This study applies the BDS test to identify whether financial market data are driven by chaos theory and identified finacial time series for modelling that display non-random behavior. Subsequently, an empirical analysis of univariate and multivariate garch models are implemented for several financial time series. Finally, the expanding literature on realized volatility is reviewed. After presenting a general univariate framework for estimating realized volatilities, a simple discrete time model is presented. Cases with and without microstructure noise are considered, and it is shown that microstructure noise cause severe problems in terms of consistent estimation of the daily realized volatility. The most important methods for providing consistent estimators are presented, and a critical exposition of different techniques is given. The main empirical findings using univariate and multivariate methods are summarized. Our paper gives evidence for the presence of low complexity chaotic behavior in stock returns

Bank competition, ownership, governance & risk

This paper provides a review of the recent literature in banking around several primary themes of competition, ownership, governance and risk. We present this review against the backdrop of the 2008 financial crisis and the revolution it caused to banking sectors in across the globe. Several themes emerge from this review, but the overarching issue relates to the need to better understand bank risk taking incentives and the implications for banking stability. There is a need for more work on the role of safety net subsidies and how these are linked to systemic risk. There is also a need to better understand the relationship between competition and risk, and understand the interconnections between capital, profitability, and risk

Tell-tale signs & the helping hand: Early warning ratios & government guarantees

Using a unique data set of 2236 banks in 78 countries, this study examines how long and short term government guarantees for private, state and foreign owned banks relate to key ratios on bank management and soundness such as capital, liquidity, asset quality and operations risk. Given short & long term government guarantees, private owned banks increase liquidity levels by around 4.01% and 0.17% respectively compared to foreign owned banks. The opposite result is true for better governed banks owning less liquid assets by around 0.13% and 0.1% respectively, relative to foreign owned banks. Short and long term government guarantees to local banks, increase tier 1 capital by around 0.6% to 0.7%. Short and long term government guarantees, result in private banks having loan portfolios with better quality, by around 0.25% and 1.9% respectively, compared to foreign owned banks. Private and state owned banks in general have a higher amount of fees and other income of around 0.24% and 0.54% as a percentage of its earnings. We provide an explanation for our results based on asset encumbrance and profit maximisation purposes and our results support the liquidity shortage hypothesis. Policy wise, we suggest improving the credibility, transparency, and strength of bank balance sheets, at the same time avoiding undue pressure on banks from un-coordinated national and international regulatory initiatives and uncertainty

Blockholders & government guarantees

This study examines how the existence of a blockholder in bank ownership effects the relationship between government guarantees and banking stability. We assemble annual database consisting of bank ownership concentration, government guarantees and accounting information for banks in 78 countries during 2001 to 2011. We find that long and short term government guarantees result in a reduction in risk and lending by 0.33% and 0.34% of state banks, reduction in lending by 0.45 % and 79% of private bank relative to foreign banks respectively. Our results contradict the risk shifting theory for banks with state and private block holders. Long and short term government guarantees result in an increment in capital ratios by around 1.7% and 8.39% of state banks relative to foreign banks. Our results suggest that blockholder ownership, contrary to popular belief does not help to alleviate instability and weakened balance sheets for local banks

ESSAYS ON GOVERNMENT GUARANTEES & BANKING STABILITY

Ph.DDOCTOR OF PHILOSOPH

Stock Market & the Economy: Evidence from Philippines

This study reviews prior literature on the relationship between the stock market and the economy and conducts a simple analysis on the same empirically for Philippines. The study utilizes quarterly data from 2003 to 2015. Results show that increases in past quarter real GDP growth causes a 0.56 increase in the present quarter real GDP growth. In addition, increases in past quarter PSI index returns cause a 0.04 increase in real GDP growth in the present quarter. Moreover, the study identifies an inflation-GDP growth puzzle for Philippines. Results support the permanent income and the financial accelerator views

Banking stability across income, legal origin, supervisory regimes & geographies

We examine the effects of government guarantees on banking stability of private, state and foreign owned banks for several heterogeneities such as income level, legal origin, supervisory control and geography. We find that state owned banks in high income countries are observed to be in a more stable condition compared to counterparts in low income countries. Private owned banks in common legal origin countries emerge to be more stable than private owned banks in other legal origins. State banks in countries where the Central Bank is the sole supervisor are observed to be more stable compared to their counterparts in other supervisory regimes. However, foreign banks are in a better position in countries with multiple supervisory regimes. In general, foreign banks in Asia and Africa are observed to be performing considerably better compared to their American and European counterparts. The diverse results we observe for each geographic region, stress the importance of region specific tailoring of banking regulations, especially given the recent financial crisis