Risk-based supervision of pension funds : a review of international experience and preliminary assessment of the first outcomes

This paper provides a review of the design and experience of risk-based pension fund supervision in several countries that have been leaders in the development of these methods. The utilization of risk-based methods originates primarily in the supervision of banks. In recent years it has increasingly been extended to other types of financial intermediaries including pension funds and insurers. The trend toward risk-based supervision of pensions is closely associated with movement toward the integration of pension supervision with that of banking and other financial services into a single national authority. Although similar in concept to the techniques developed in banking, the application to pension funds has required modifications, particularly for defined contribution funds that transfer investment risk to fund members. The countries examined provide a range of experiences that illustrate both the diversity of pension systems and approaches to risk-based supervision, but also a commonality of the focus on sound risk management and effective supervisory outcomes. The paper provides a description of pension supervision in Australia, Denmark, Mexico and the Netherlands, and an initial evaluation of the results achieved in relation to the underlying objectives.Debt Markets,,Insurance&Risk Mitigation,Emerging Markets,Banks&Banking Reform

Global and Domestic Factors of Financial Crises in Emerging Economies: Lessons from the East Asian Episodes (1997-1999)

This paper suggests that a new approach is needed in order to identify the causes of the East Asian financial crises and that this new approach might be fruitful in reassessing the analyses and theories of financial crises in emerging economies. The first part of the paper presents a new empirical analysis of the state of fundamentals in East Asia before the crises. It suggests that the relevant fundamentals were both non-conventional and "intermediate" (or not "bad" enough to trigger the crises by themselves). Fundamentals were also different from those preceding previous turmoils in the 1990s, such as the ERM crisis in 1992-1993 and the Mexican crisis in 1994-1995. The second part highlights that existing theoretical models of currency crises miss some important points. Even second generation models, which stress self-fulfilling expectations and which acknowledge that crises might appear against the backdrop of non-conventional and intermediate fundamentals, explain only the role of fundamentals in relation to private expectations. But they do not explain how can it be that a shift in private agents' expectations turns out into a financial crisis. The third part suggests that the current process of globalization exacerbates failures in international capital markets and impinges upon capital flows and the pace and order of financial liberalization in emerging economies, increasing therefore uncertainty and rendering large domestic vulnerabilities. It also highlights how financial globalization was related to the East Asian crises. The main conclusion is that intermediate non-conventional fundamentals, shifts in private agents' expectations and financial globalization were arguably the main factors of the East Asian crisis. Therefore, in order to prevent future financial crises, governments in emerging economies should try to exit crises zones through improving their fundamentals, to proceed carefully with financial liberalization, to implement some kind of capital controls and to urge for the establishment of a new global financial architecture.

Monetary Policy in an Equilibrium Portfolio Balance Model

Portfolio balance, sterilized foreign exchange intervention

Market Dynamics When Agents Anticipate Correlation Breakdown

The aim of this paper is to analyse the effect introduced in the dynamics of a financial market when agents anticipate the occurrence of a correlation breakdown. What emerges is that correlation breakdowns can act both as a consequence and as a triggering factor in the emergence of financial crises rational bubbles. We propose a market with two kinds of agents: speculators and rational investors. Rational agents use excess demand information to estimate the variance-covariance structure of assets returns, and their investment decisions are represented as a Markowitz optimal portfolio allocation. Speculators are uninformed agents and form their expectations by imitative behavior, depending on market excess demand. Several market equilibria result, depending on the prevalence of one of the two types of agents. Differing from previous results in the literature on the interaction between market dynamics and speculative behavior, rational agents can generate financial crises, even without the speculator contribution

Can the impact of contagion effects on global equities be reduced through a dynamic asset allocation strategy based on capital flows data?

The literature supports evidence of a contagion effect, where an increase in correlations and price movements is observed across assets during a market downturn. This contagion effect can diminish the diversification expected from a portfolio’s asset allocation. There is research showing a connection between capital flows and contagion. This thesis considers this connection through a dynamic allocation strategy with allocation decisions based on capital flow movements. This strategy is applied to an equity-only portfolio with the objective of maintaining some benefits of diversification while preserving capital. In an out of sample test, a regime switching model is used to predict market downturns for the period from January 1998 to December 2018. For the predicted downturns, portfolios’ geographical allocation is altered with allocation changes based on the countries’ capital flows. Results from historical back tests show weak evidence of higher returns and similar Sharpe ratios for a dynamic strategy versus a static strategy for portfolios of developed market equities. The implications for portfolios of emerging market equities are less obvious

FRM Financial Risk Meter

Der Risikobegriff bezieht sich auf die Wahrscheinlichkeit eines Schadens aufgrund einer Gefährdungsexposition, in der Finanzwelt meist finanzielle Verluste. Viele Risiken der globalen Finanzwirtschaft sind unbekannt. „Wir wissen es, wenn wir es sehen“, um Potter Stewart (1964) zu paraphrasieren. Der Financial Risk Meter (FRM) soll Aufschluss über die Entstehung systemischer Risiken geben. Durch Verwendung von Quantilregressionstechniken ist der FRM nicht nur ein Maß für finanzielle Risiken. Er bietet durch seine Netzwerktopologie einen tiefen Einblick in die Spill-over-Effekte, die sich als systemische Risikoereignisse manifestieren können. Das FRM-Framework wird in verschiedenen Märkten und Regionen entwickelt. Die FRM-Daten werden für Risiko-Prognose sowie für Portfoliooptimierung genutzt. In Kapitel 1 wird der FRM vorgestellt und auf die Aktienmärkte in den USA und Europa, sowie auch auf die Zinsmärkte und Credit-Default-Swaps angewendet. Der FRM wird dann verwendet, um wirtschaftliche Rezessionen zu prognostizieren. In Kapitel 2 wird der FRM auf den Markt der Kryptowährungen angewendet, um das erste Risikomaß für diese neue Anlageklasse zu generieren. Die errechneten FRM-Daten zu Abhängigkeiten, Spillover-Effekten und Netzwerkaufbau werden dann verwendet, um Tail-Risk-optimierte Portfolios zu erstellen. Der Portfoliooptimierungsansatz wird in Kapitel 3 weitergeführt, in dem der FRM auf die sogenannten Emerging Markets (EM)-Finanzinstitute angewendet wird, mit zwei Zielen. Einerseits gibt der FRM für EM spezifische Spillover-Abhängigkeiten bei Tail-Risk-Ereignissen innerhalb von Sektoren von Finanzinstituten an, zeigt aber auch Abhängigkeiten zwischen den Ländern. Die FRM-Daten werden dann wieder mit Portfoliomanagementansätzen kombiniert. In Kapitel 4 entwickelt den FRM for China ist, eines der ersten systemischen Risikomaße in der Region, zeigt aber auch Methoden zur Erkennung von Spill-Over-Kanälen in Nachbarländer und zwischen Sektoren.The concept of risk deals with the exposure to danger, in the world of finance the danger of financial losses. In a globalised financial economy, many risks are unknown. "We know it when we see it", to paraphrase Justice Potter Stewart (1964). The Financial Risk Meter (FRM) sheds light on the emergence of systemic risk. Using of quantile regression techniques, it is a meter for financial risk, and its network topology offers insight into the spill-over effects risking systemic risk events. In this thesis, the FRM framework in various markets and regions is developed and the FRM data is used for risk now- and forecasting, and for portfolio optimization approaches. In Chapter 1 the FRM is presented and applied to equity markets in the US and Europe, but also interest rate and credit-default swap markets. The FRM is then used to now-cast and predict economic recessions. In Chapter 2 the FRM is applied to cryptocurrencies, to generate the first risk meter in this nascent asset class. The generated FRM data concerning dependencies, spill-over effects and network set-up are then used to create tail-risk optimised portfolios. In Chapter 3 the FRM is applied to the global market Emerging Market (EM) financial institutions. The FRM for EM gives specific spill-over dependencies in tail-risk events within sectors of financial institutions, but also shows inter-country dependencies between the EM regions. The FRM data is then combined with portfolio management approaches to create tail-risk sensitive portfolios of EM Financial institutions with aim to minimize risk clusters in a portfolio context. In Chapter 4 the Financial Risk Meter for China is developed as the first systemic risk meter in the region, but also derives methods to detect spill-over channels to neighbouring countries within and between financial industry sectors

"Trade Liberalization and Poverty Reduction in General Equilibrium: The Role of Labor Market Structure"

The paper uses a dualistic, compact and "generic" (macroeconomic) computable general equilibrium (CGE) model specially constructed for the purpose of investigating the implications of trade liberalization for poverty reduction in South Asia under different labor market specifications. The model is a stylized representation of economies with large populations including large numbers of both urban and rural poor as in India, Pakistan or Bangladesh. The current "generic" model uses CES production functions and Harris-Todaro type migration model together with Indian data to generate economy wide results. The model's general equilibrium results allow us to test a number of hypotheses regarding the role of labor markets in inducing poverty reduction when trade liberalization policies are adopted.