The United States dominates global investment banking: does it matter for Europe? Bruegel Policy Contribution 2016/06, March 2016

In the aftermath of the global financial crisis, the market share of US investment banks is increasing, while that of their European counterparts is declining. We present evidence that US investment banks are on the verge of taking over pole position in European investment banking. Meanwhile, since 2015, Chinese investment banks have overtaken American and European investment banks in the Asia-Pacific market. Credit rating agencies and investment banks are the gatekeepers of the capital markets. The European supervisory institutions can effectively supervise the European operations of these US-managed players. On the political side, we suggest that the European Commission should continue to view its, albeit declining, banking industry as a strategic sector. The Commission, the European Central Bank and the Bank of England should jointly develop a strategic agenda for the EU-US Regulatory Dialogue. Finally, corporates rely on investment banks to issue new securities. We recommend that the big European corporates should cherish the (few) remaining European investment banks, by giving them at least one place in otherwise US- dominated banking syndicates. That could help to avoid complete dependence on US investment banks.

Is there a need for additional monetary stimulus? Insights from the original Taylor Rule. CEPS Policy Brief No. 342, April 2016

Central banks in the developed world are being misled into fighting the perceived dangers of a ‘deflationary spiral’ because they are looking at only one indicator: consumer prices. This Policy Brief finds that while consumer prices are flat, broader price indices do not show any sign of impending deflation: the GDP deflator is increasing in the US, Japan and the euro area by about 1.2-1.5%. Nor is the real economy sending any deflationary signals either: unemployment is at record lows in the US and Japan, and is declining in the euro area while GDP growth is at, or above potential. Thus, the overall macroeconomic situation does not give any indication of an imminent deflationary spiral. In today’s high-debt environment, the authors argue that central banks should be looking at the GDP deflator and the growth of nominal GDP, instead of CPI inflation. Nominal GDP growth, as forecasted by the major official institutions, remains robust and is in excess of nominal interest rates. They conclude that if the ECB were to set the interest rate according to the standard rules of thumb for monetary policy, which take into account both the real economy and price developments of broader price indicators, it would start normalising its policy now, instead of pondering over additional measures to fight deflation, which does not exist. In short, economic conditions are slowly normalising; so should monetary policy.

European Union Bailouts and Credibility. Jean Monnet/Robert Schuman Paper Series Vol. 15 No. 4, October 2015

Since the Great Recession started, there have been eight bailouts to EU Member States, which approximate cost to the EU has been of around 380 billion euros. The aim of this paper is to analyze the legal-constitutional issues that this major bailing out operation has brought about. The conclusion is that the EU was not only ill-prepared from an economic perspective to make bailouts; it was also ill-prepared from a constitutional perspective as well, above all if one understands law, as this paper does, as a credibility device. Absent further reforms and clarifications, the current EU system of bailout governance may be prone to generate important credibility problems in the future.

The Business Models and Economics of Peer-to-Peer lending. ECRI Research Report No 17, May 2016

This paper reviews peer-to-peer (P2P) lending, its development in the UK and other countries, and assesses the business and economic policy issues surrounding this new form of intermediation. P2P platform technology allows direct matching of borrowers’ and lenders’ diversification over a large number of borrowers without the loans having to be held on an intermediary balance sheet. P2P lending has developed rapidly in both the US and the UK, but it still represents a small fraction, less than 1%, of the stock of bank lending. In the UK – but not elsewhere – it is an important source of loans for smaller companies. We argue that P2P lending is fundamentally complementary to, and not competitive with, conventional banking. We therefore expect banks to adapt to the emergence of P2P lending, either by cooperating closely with third-party P2P lending platforms or offering their own proprietary platforms. We also argue that the full development of the sector requires much further work addressing the risks and business and regulatory issues in P2P lending, including risk communication, orderly resolution of platform failure, control of liquidity risks and minimisation of fraud, security and operational risks. This will depend on developing reliable business processes, the promotion to the full extent possible of transparency and standardisation and appropriate regulation that serves the needs of customers.

The effectiveness of the European Central Bank’s Asset Purchase Programme. Bruegel Policy Contribution issue 2016 10 June 2016

Since the end of 2014, inflation has been at or very close to zero. With very little ability to move the actual interest rate further into negative territory, the ECB has resorted to unconventional measures. The latest of these includes a programme to purchase corporate bonds, which started on 8 June 2016.

Bubble detection in Brazil’s stock market: application of the generalized superior augmented Dickey-Fuller test

Considering the importance of the proper detection of bubbles in financial markets for policymakers and market agents, we used two techniques described in Diba and Grossman (1988b) and in Phillips, Shi, and Yu (2015) to detect periods of exuberance in the recent history of the Brazillian stock market. First, a simple cointegration test is applied. Secondly, we conducted several augmented, right-tailed Dickey-Fuller tests on rolling windows of data to determine the point in which there’s a structural break and the series loses its stationarity.

Macroeconomic Dynamics of Market Risk Capital Requirements and Credit Supply Interdependence

Thesis (Ph.D.)--University of Washington, 2016-06

Zero-non-zero patterned vector error correction modeling for I(2) cointegrated time series with applications in testing PPP and stock market relationships

Vector error-correction models (VECMs) have become increasingly important in their application to financial markets. Standard full-order VECM models assume non-zero entries in all their coefficient matrices. However, applications of VECM models to financial market data have revealed that zero entries are often a necessary part of efficient modelling. In such cases, the use of full-order VECM models may lead to incorrect inferences. Specifically, if indirect causality or Granger non-causality exists among the variables, the use of over-parameterised full-order VECM models may weaken the power of statistical inference. In this paper, it is argued that the zero–non-zero (ZNZ) patterned VECM is a more straightforward and effective means of testing for both indirect causality and Granger non-causality. For a ZNZ patterned VECM framework for time series of integrated order two, we provide a new algorithm to select cointegrating and loading vectors that can contain zero entries. Two case studies are used to demonstrate the usefulness of the algorithm in tests of purchasing power parity and a three-variable system involving the stock market.

Using extreme value theory to measure value-at-risk for daily electricity spot prices

The recent deregulation in electricity markets worldwide has heightened the importance of risk management in energy markets. Assessing Value-at-Risk (VaR) in electricity markets is arguably more difficult than in traditional financial markets because the distinctive features of the former result in a highly unusual distribution of returns-electricity returns are highly volatile, display seasonalities in both their mean and volatility, exhibit leverage effects and clustering in volatility, and feature extreme levels of skewness and kurtosis. With electricity applications in mind, this paper proposes a model that accommodates autoregression and weekly seasonals in both the conditional mean and conditional volatility of returns, as well as leverage effects via an EGARCH specification. In addition, extreme value theory (EVT) is adopted to explicitly model the tails of the return distribution. Compared to a number of other parametric models and simple historical simulation based approaches, the proposed EVT-based model performs well in forecasting out-of-sample VaR. In addition, statistical tests show that the proposed model provides appropriate interval coverage in both unconditional and, more importantly, conditional contexts. Overall, the results are encouraging in suggesting that the proposed EVT-based model is a useful technique in forecasting VaR in electricity markets. (c) 2005 International Institute of Forecasters. Published by Elsevier B.V. All rights reserved.

'Seeing the market': Technical analysis in trading styles

Whilst financial markets are not strangers to academic and professional scrutiny, they still remain epistemologically contested. For individuals trying to profit by trading shares, this uncertainty is manifested in the varying trading styles which they are able to utilize. This paper examines one trading style commonly used by non-professional share traders-technical analysis. Using research data obtained from individuals who identify themselves as technical analysts, this paper seeks to explain the ways in which individuals understand and use the technique in an attempt to make trading profits. In particular, four distinct subcategories or ideal types of technical analysis can be identified, each providing an alternative perceptual form for participating in financial markets. Each of these types relies upon a particular method for seeing the market, these visualization techniques highlighting the existence of forms of professional vision (as originally identified by Goodwin (1994)) in the way the trading styles are comprehended and acted upon.

Development of a web-service-agents-based family wealth management system

The roiling financial markets, constantly changing tax law and increasing complexity of planning transaction increase the demand of aggregated family wealth management (FWM) services. However, current trend of developing such advisory systems is mainly focusing on financial or investment side. In addition, these existing systems lack of flexibility and are hard to be integrated with other organizational information systems, such as CRM systems. In this paper, a novel architecture of Web-service-agents-based FWM systems has been proposed. Multiple intelligent agents are wrapped as Web services and can communicate with each other via Web service protocols. On the one hand, these agents can collaborate with each other and provide comprehensive FWM advices. On the other hand, each service can work independently to achieve its own tasks. A prototype system for supporting financial advice is also presented to demonstrate the advances of the proposed Webservice- agents-based FWM system architecture.

UMA ANÁLISE DA RELAÇÃO ENTRE VARIÁVEIS MACROECONÔMICAS E O COMPORTAMENTO DAS AÇÕES DE MAIOR LIQUIDEZ DO ÍNDICE IBOVESPA

As ações de maior liquidez do índice IBOVESPA, refletem o comportamento das ações de um modo geral, bem como a relação das variáveis macroeconômicas em seu comportamento e estão entre as mais negociadas no mercado de capitais brasileiro. Desta forma, pode-se entender que há reflexos de fatores que impactam as empresas de maior liquidez que definem o comportamento das variáveis macroeconômicas e que o inverso também é uma verdade, oscilações nos fatores macroeconômicos também afetam as ações de maior liquidez, como IPCA, PIB, SELIC e Taxa de Câmbio. O estudo propõe uma análise da relação existente entre variáveis macroeconômicas e o comportamento das ações de maior liquidez do índice IBOVESPA, corroborando com estudos que buscam entender a influência de fatores macroeconômicos sobre o preço de ações e contribuindo empiricamente com a formação de portfólios de investimento. O trabalho abrangeu o período de 2008 a 2014. Os resultados concluíram que a formação de carteiras, visando a proteção do capital investido, deve conter ativos com correlação negativa em relação às variáveis estudadas, o que torna possível a composição de uma carteira com risco reduzido.

Estimating conditional volatility with neural networks

It is well known that one of the obstacles to effective forecasting of exchange rates is heteroscedasticity (non-stationary conditional variance). The autoregressive conditional heteroscedastic (ARCH) model and its variants have been used to estimate a time dependent variance for many financial time series. However, such models are essentially linear in form and we can ask whether a non-linear model for variance can improve results just as non-linear models (such as neural networks) for the mean have done. In this paper we consider two neural network models for variance estimation. Mixture Density Networks (Bishop 1994, Nix and Weigend 1994) combine a Multi-Layer Perceptron (MLP) and a mixture model to estimate the conditional data density. They are trained using a maximum likelihood approach. However, it is known that maximum likelihood estimates are biased and lead to a systematic under-estimate of variance. More recently, a Bayesian approach to parameter estimation has been developed (Bishop and Qazaz 1996) that shows promise in removing the maximum likelihood bias. However, up to now, this model has not been used for time series prediction. Here we compare these algorithms with two other models to provide benchmark results: a linear model (from the ARIMA family), and a conventional neural network trained with a sum-of-squares error function (which estimates the conditional mean of the time series with a constant variance noise model). This comparison is carried out on daily exchange rate data for five currencies.

The trading mechanism, cross listed stocks:A comparison of the Paris Bourse and SEAQ-International

This paper studies the behaviour of returns for a sample of cross-listed stocks, listed on both the Paris Bourse and SEAQ-International in London. The aim of the paper is to discover which market adjusts to fundamental news more quickly, the home market of Paris or SEAQ-International. We find that prices in London adjust to changes in their fundamental value more slowly than Paris prices, despite the ability to quickly arbitrage between the two markets. We suggest that this finding may reflect the type of trading, which takes place in the two markets and differences associated with the reporting of large trades. We also estimate the amount of noise present in the two markets and show that the Paris market is more noisy than London. © 2003 Published by Elsevier B.V.