Abstracts

Josephine Fandrich 

Title: Dynamic coherent risk measures in bond markets with stochastic interest rates

Abstract: In recent years, there has been increasing interest in developing methods for assessing the risk associated with financial positions. The risk of a financial position can be thought of as the amount of money that needs to be added to the position to make it acceptable. Interest rates have traditionally been assumed to be constant in order to construct both model-dependent and model-free risk measures. However, constant interest rates are rather unrealistic. Furthermore, there has been no analysis of risk measures in bond markets. For this reason, we are going to take a look at bond markets with stochastic interest rates. To do this, we consider an arbitrage free financial market model with stochastic interest rates, wherein the bonds are designated as the risky asset. We present an axiomatic approach that extends the definition of a dynamic coherent risk measure to bond markets. We show that a dynamic coherent risk measure can be represented as the worst conditional expectation of present future losses, where the expectations are being taken over a set of probability measures that satisfies a consistency condition. Furthermore, we show that this risk measure is a time consistent sequence of conditional coherent risk measures. 

Fabian Fuchs

Title: A comparison principle based on couplings of partial integro-differential operators

Abstract: This talk is concerned with a comparison principle for viscosity solutions to Hamilton--Jacobi (HJ), -Bellman (HJB), and -Isaacs (HJI) equations for general classes of partial integro-differential operators.

Our approach innovates in three ways: (1) We reinterpret the classical doubling-of-variables method in the context of second-order equations by casting the Ishii-Crandall Lemma into a test function framework. This adaptation allows us to effectively handle non-local integral operators, such as those associated with Lévy processes. (2) We translate the key estimate on the difference of Hamiltonians in terms of an adaptation of the probabilistic notion of couplings, providing a unified approach that applies to differential, difference, and integral operators. (3) We strengthen the sup-norm contractivity resulting from the comparison principle to one that encodes continuity in the strict topology.

We apply our theory to a variety of examples, in particular, to second-order differential operators and, more generally, generators of spatially inhomogeneous Lévy processes. 

Keorapetse Leballo

Title: Systemic Risk and Tail Dependence Dynamics in Financial Markets

Abstract: The aim of this research study is to assess both the right and left tail dependence structure and risk spillovers between Bitcoin and precious metals. This research study applies a copula quantile regression model, where the marginal distribution of each asset is built on the ARFIMA-FIGARCH model. The systemic risk and risk spillovers are computed using multivariate systemic risk measures, namely: the MCVaR; the SCVaR, and the VCVaR model. We further simplify and improve the numerical stability of the estimation process by using the C-Vine and D-Vine copula frameworks. Later in the study, we contrast the performance of these multivariate systemic risk measures against the bivariate CVaR model using various information criteria. Our study reveals that the D-Vine based SCVaR model is the best performing systemic risk measure, with Bitcoin and precious metals displaying different tail-risk dynamics under extreme market conditions. 

Timothy Tafadzwa Makanga

Title: Quantile connectedness  between stock markets and oil price shocks: a cross-country analysis

Abstract: This study integrates spillover dynamics, time-varying connectedness, and network topology to analyse the behaviour of a system comprising 13 global assets, including major stock indices and crude oil, under varying market conditions represented by quantile distributions. Daily data of these assets was reviewed, spanning a 16-year period, from the 1st of July 2008 to the 1st of August 2024. The aim was to assess return spillovers, identify influential markets, and enhance portfolio selection and optimisation. Utilising quantile connectedness analysis, graph theory, and network-based portfolio optimisation, the findings revealed that developed stock markets such as the United States, Germany, and the United Kingdom are dominant transmitters of financial shocks in the system, especially during bear markets. These markets exhibited high Eigenvector centrality, making them critical sources of systemic risk and potential contagion. In contrast, during bull markets, emerging markets such as Mexico and Indonesia became more influential, driven by their role in commodity exports, which significantly shapes global financial dynamics. This indicates that the influence of a market is highly context-dependent, with emerging markets gaining centrality during periods of economic expansion. Additionally, the traditional role of crude oil as a safe-haven asset was brought into question, as it constantly proved to be a net receiver of shocks. The results suggest that crude oil's interconnectedness with other assets, particularly during growth periods, does not translate into defensive characteristics in times of financial stress. The study also demonstrates that portfolios constructed using centrality measures, such as PageRank and Eigenvector to penalise highly central assets, consistently outperform traditional mean-variance portfolios across all market conditions. These findings offer valuable insights for investors and portfolio managers, providing a strategic advantage by focusing on market centrality to optimise risk-adjusted returns and mitigate systemic risks. The research underscores the importance of dynamic, market regime-specific strategies that can adapt to the complexities of global financial markets. The insights gained from this study are essential for financial institutions, policymakers, and global investors aiming to navigate interconnected markets and improve portfolio resilience. 

Nkosinathi Monamodi

Title: The Impact of Current Account Deficit on Economic Growth in South Africa: Implications of Covid-19 Pandemic

Abstract: The study investigates the impact of South African current account balance on its economic growth from Q1 2015 to Q4 2022 using Auto Regressive Distributed Lags (ARDL) technique. The study incorporates the qualitative variable like Covid-19 to understand its effect on the South African current account and economic growth rate. Generally, the results show that the South African current account deficit impacted economic growth in both long and short run. Covid-19 also affected current account significantly in both long and short run, thus causing more deterioration on the South African current account, and subsequently affecting economic growth rate negatively. The study recommends more competitive exports promotion, imports substitution by investing in and developing domestic productivity. The study also recommends an acceleration of the tabled Covid-19 recovery initiatives by alliance between government and private sector. 

Godfrey Mtunzi

Title: Examining Cont's Stylised Facts of Returns on Unstable Financial Markets: Evidence from the Zimbabwe Stock Exchange

Abstract: Understanding the dynamics of financial asset prices, exchange rates, and risk-return profiles has posed a persistent challenge for economists, financial mathematicians, and market practitioners. Traditional models, both stochastic and deterministic such as the plain or geometric random walk, garch and their extensions have proven inadequate, particularly when capturing extreme price movements that occur far more frequently in unstable financial markets exemplified by the Zimbabwe Stock Exchange than predicted by standard Gaussian models. According to Cont (2001), when markets are out of their equilibriums, they are all expected to exhibit stylised facts,  manifesting as significant market returns gains or losses, highlighting the failure of traditional approaches and underscoring the need for more robust modelling techniques that comprehensively explain and accommodate the salient features of real-world financial data. These stylised facts include heavy-tailed distributions, volatility clustering, and extreme correlations, which are critical for understanding the behaviours of financial markets under uncertain conditions. This paper aims to advance the understanding of financial markets' extreme behaviour, focusing on their statistical characteristics and risk-return impacts.  By understanding such behaviours in financial markets, particularly how returns respond to extreme market movements caused by regulatory, economic and natural events, new insights into the mechanics of these events and their effects on market stability will be gained. Robust methodologies that capture the behaviour of financial markets under both normal and extreme conditions will then be formalised in place of classical methodologies. 

Costa Musandipa

Title: The proposed Theoretical framework and exploration of key factors that impact household financial well-being in Botswana and Zimbabwe

Abstract: Alarming global trends in household default rates and continuously deteriorating household financial well-being in many countries have remained a subject of interest for many decades. Despite literature being replete with studies, loan delinquency and macroeconomic variables' (gross domestic product, interest rate, unemployment, and inflation) role in influencing households' financial well-being has remained unexplored. This article presents a perspective that is being proposed for the first time. It is proposed that the combined effect of loan delinquency and the macroeconomic variables determine the rationality of households' financial well-being decisions in an economy. The literature identifies a myriad of macroeconomic factors that influence the optimality of a household’s quality of life albeit in isolation of loan delinquency. Understanding the influence that these factors play in different financial environments and their impact on households' financial well-being remains an empirical question. First, the paper proposes a consolidated approach that considers relationships and interrelations among various macroeconomic factors, loan delinquency, and household financial well-being as a measure towards the development of a higher-order theory of the efficiency of household credit markets. Second, the paper takes the first step towards exploring the mechanics of households' default behavior in the context of a developing African economy by investigating factors that determine households' credit behavior and quality of life. In particular, the paper explores the key factors related to household’s financial well-being and default decisions by Botswana and Zimbabwe households using exploratory factor analysis. The implications of the research findings to policy point to a need for a paradigm shift in regulation through 'truth-in-lending' laws for the developing economy. This perspective of analyzing household financial well-being is instrumental to policymakers, consumer lobbyists, and marketers. 

Nokulinda Ngwinya

Title: Financial contagion in emerging markets: Pathways and impact of shock transmissions

Abstract: This paper investigates the cross-transmission of shocks from the US and China to key emerging market regions – Latin America, Asia, the Middle East, Europe and Africa – to identify patterns of contagion, interdependence and decoupling using the Extreme Value Theory-Generalized Autoregressive Conditional Heteroskedasticity (EVT-GARCH) copula approach. Only a limited number of studies differentiate between the origins of shock transmission and their impacts on various emerging markets in the context of contagion analysis. The results show strong interdependence between the US and emerging markets in Latin America, the Middle East, Europe and Africa, with Latin America exhibiting the highest degree of interdependence. In contrast, the findings indicate contagion effects from the US to emerging Asian markets. Additionally, the study uncovers interdependence between China and the emerging markets of Asia, the Middle East, Europe and Africa, while revealing contagion effects from China to Latin America, where Latin America also demonstrates a high level of interdependence. Consequently, the analysis reveals no evidence of decoupling between the US, China and all emerging market regions. These results highlight that the impact of crises on emerging markets varies based on their specific relationship with the source market. Policymakers and investors can leverage these insights to better understand how shocks from different global markets affect emerging economies, allowing for more informed economic strategies and investment decisions. 

Prince Osei

Title: Fat-tailed distribution under Smooth Ambiguity Model

Abstract: We present the smooth ambiguity model, which permits the separation of risk attitude, ambiguity attitude, and ambiguity. We apply the exponential-power utility framework to model the asset return. The notion that asset returns are normally distributed has been increasingly questioned. Our model provides an alternative explanation for fat tails in asset returns observed in the stock data based on the smooth ambiguity model. We take a standard probability distribution for asset return, the normal distribution with a known mean and an unknown variance. To account for the error in estimating the variance, we introduce the gamma distribution. Our model proposes the variance-gamma distribution for the unconditional law of asset return. 

Anthony Owusu-Ansah

Title: Mispricing and risk premia in real estate markets

Abstract: The extensive development of asset pricing models has received most applications to financial assets. Unlike stocks and bonds, property valuations are prone to human manipulation, particularly in the presence of weak regulation, lack of reliable data, and poor valuation methods. This paper applies the behavioural finance theory to housing markets and seeks to explore behavioural biases affecting real estate investment decision and returns. Besides the limited market participation, the study considers the role of appraisal bias and investor sentiments in driving systematic mispricing of real estate assets. Using data for selected African countries, we show that real estate excess return predictability is in part due to mispricing. First, the risk-adjusted profitability decreases after dissemination of the underlying market research, suggesting that market participants learn about mispricing from property valuation uncertainty. Second, the effect of comprehensive risk adjustments on returns is limited. The finding that analysts’ forecasts are inconsistent with housing return predictors implies that real estate intermediaries contribute to mispricing and suggests appraisal uncertainty and investor sentiments as possible explanations. 

Tchuinkam Djemo Charles Raoul

Title: Assessing the interdependence of Exchange rates, Precious Metals, and Energy Resources in the BRICS economies: Vine copulas approach

Abstract: This paper attempts to apply the vine copulas methodology to assess the interdependence between the exchange rates market, equity indices, precious metals and energy resources in the selected BRICS economies. Using the ARFIMA-GJR-GARCH model to filter the residual of the daily returns of the foreign exchange rate, the precious metals, equity indexes, and energy prices of the BRICS economies spanning 1st January 2003 to August 2023. Our empirical findings show the persistence of shocks and the asymmetric response to positive and negative news. Volatility is high across equity, precious metals, and energy markets, with significant risks requiring robust risk management strategies. The findings demonstrate the BRICS economies' high sensitivity to external shocks, such as the Global Financial Crisis and the COVID-19 pandemic, which caused significant market volatility across currencies, stock market returns, and energy prices. The study emphasizes the importance of diversification due to the strong co-movement between asset classes, especially during periods of extreme market movements. Moreover, the vine copulas analysis shows complex co-movements between assets, aiding in better portfolio management. Assets like oil and gold act as hedges, while foreign exchange rates significantly impact investment decisions, highlighting the need for careful risk assessment and diversification strategies. These findings underscore the vulnerability of BRICS economies to external shocks and emphasize the importance of effective risk management and diversification in navigating these markets. 

Marco Spengemann

Title: The Pricing Kernel under Proportional Ambiguity

Abstract: The pricing kernel is an important tool for understanding asset prices, expected returns, and investor preferences. However, empirical findings often reveal deviations from theoretical predictions, leading to the so-called "pricing kernel puzzle". This study explores the pricing kernel under Knightian uncertainty driven by identifiable business cycles.

In a pure exchange economy with a representative consumer exhibiting smooth ambiguity preferences, the pricing kernel is derived from equilibrium asset prices. By linking normal variance-mean mixtures with model uncertainty, we account for agents facing uncertainty across a continuum of economic regimes. Our results show that the pricing kernel can either decrease monotonically or exhibit a U-shape, depending on the level of ambiguity aversion. Additionally, we provide economic insights into the conditions that give rise to a U-shaped pricing kernel. 

Nomathemba Veronica Diseko

Title: The impact of renewable energy risks on real estate market

Abstract: Real estate is a key sector in achieving decarbonized economy as property owners can help reduce CO2 emission by using renewable energy sources to power their properties. However, renewable energy production is subject to several risks; the housing price impact of which remains underexplored. This study investigates the impact of renewable energy price fluctuations on real estate markets in regions with high versus low reliance on renewable energy. The research quantifies the volatility and correlations between renewable energy prices and real estate returns in different geographical contexts. The objective is to assess the differential exposure to energy price risks across these regions and explore hedging strategies to mitigate this risk. Our finding confirms that energy risks fuel uncertainty in the real estate market, with significant consequences on house prices. In addition, regulations and control policies prove to be significant in mitigating these risks. Therefore, sustainability policies and strategies represent an important stability indicator of the real estate market.