This study investigates volatility pattern of Kenyan stock market based on time series data which consists of daily closing prices of NSE Index for the period 2ndJanuary 2001 to 31st December 2014. The analysis has been done using both symmetric and asymmetric Generalized Autoregressive Conditional Heteroscedastic (GARCH) models. The study provides evidence for the existence of a positive and significant risk premium. Moreover, volatility shocks on daily returns at the stock market are transitory. We do not find any significant leverage effect. Introduction of the new regulations on foreign investors with a 25% minimum reserve of the issued share capital going to local investors (in 2002), introduction of live trading, cross listing in Uganda and Tanzania stock exchange (in 2006) and change in equity settlement cycle from T+4 to T+3 (in 2011) significantly reduce volatility clustering. The onset of US tapering increase the daily mean returns significantly while reducing conditional volatility.

The aim of this study was to explain the relative effectiveness of monetary and fiscal policies in explaining output in Rwanda. The study used a sample of quarterly data for the period 1996-2014. Applying a recursive VAR, the study used 12 variables, including 5 endogenous and 7exogenous variables to the benchmark model and other two specifications were attempted to capture the true contribution of monetary and fiscal policies to variations in nominal output. Obtained results using impulse responses and variance decomposition provide evidence that monetary policy is more effective than fiscal policy in explaining changes in nominal output in Rwanda. In addition, monetary policy explains better output when the VAR model contains domestic exogenous variables than when they are not included, suggesting the relevance of including domestic exogenous variables in VAR specification of monetary and fiscal policies effectiveness on economic variables. Another suggestion is that in order to achieve higher growth, the government of Rwanda should rely more on monetary policy as compared to fiscal policy.

Purpose This paper aims to establish the effect of bank regulations on financial stability in Kenya. Specifically, the study seeks to uncover the effect of micro and macro prudential regulations on financial stability and their trade-offs or complementarities. Design/methodology/approach Using annual time series data over the period 1990–2017, the study uses structural equation model (SEM) estimation technique. This solves the problem of approximating measurement errors, using both latent constructs and indicator constructs. Findings Study findings reveal that macro and micro prudential regulations are significant drivers of financial stability. Further, prudential regulations are more effective when they complement each other. Research limitations/implications This study centers on how bank regulations affect financial stability. Future research could be carried out on the effect of Non-Bank Financial Institutions regulations on financial system stability. Practical implications Complementing macro and micro prudential regulation is more effective and efficient in ensuring stability of the financial system other than letting the two policy objectives operate independently. Social implications Regulatory authorities should introduce prudential regulations that would encourage innovations in the banking sector. This ensures easy deposit mobilization that enhances financial inclusion. Prudential regulations that ensure financial stability will be effective when low income earners are included in the financial system. Originality/value To the best of the authors’ knowledge, this study is the first to investigate the role of banking regulations on financial stability. This study is also pioneering in the use of SEM estimation technique, in examining how prudential regulations affect financial stability. Previous cross-country studies have focused on macro prudential regulations ignoring the importance of micro prudential regulations.

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PurposeThe purpose of this paper is to investigate the effects of macroeconomic factors on secured and unsecured household loans from UK banks.Design/methodology/approachThe approach uses Vector auto‐regression models to test the relationship between macroeconomic factors such as interest rates, house prices, unemployment rates, disposable income and bank write‐offs to discern the main factors which could impact on banks' losses.FindingsThis paper identifies several macroeconomic factors that influence loan losses. The influence however depends on the type of arrears. Changes in house prices, interest rates and unemployment rates have a significant impact on secured loans. There is however, minimal impact on unsecured loans. Unemployment stands out as the major factor that influences both mortgage and credit card arrears. The estimated results show that the main factors impacting on credit cards are disposable income and unemployment rates, while changes in interest rates have no impact on credit card write‐offs.Originality/valueThis paper's value lies in providing methods by which commercial banks could manage household loans better by reducing the effects of macroeconomic factors.