Empirical Finance

The following working document summarizes our work on the clustering of financial time series. It was written for a workshop on information geometry and its application for image and signal processing. This workshop brought several experts in pure and applied mathematics together with applied researchers from medical imaging, radar signal processing and finance. The authors belong to the latter group. This document was written as a long introduction to further development of geometric tools in financial applications such as risk or portfolio analysis. Indeed, risk and portfolio analysis essentially rely on covariance matrices. Besides that the Gaussian assumption is known to be inaccurate , covariance matrices are difficult to estimate from empirical data. To filter noise from the empirical estimate, Mantegna proposed using hierarchical clustering. In this work, we first show that this procedure is statistically consistent. Then, we propose to use clustering with a much broader application than the filtering of empirical covariance matrices from the estimate correlation coefficients. To be able to do that, we need to obtain distances between the financial time series that incorporate all the available information in these cross-dependent random processes.

Study of the impact of additive outliers on the calculation of risk measures.Comparison of 6 proposals to reduce outlier effects in GARCH-type model estimation.The presence of outliers affects seriously risk measure estimates.Our proposal almost eliminates the biases on risk measure estimates.In this paper we focus on the impact of additive outliers (level and volatility) on the calculation of risk measures, such as minimum capital risk requirements. Through simulation and empirical studies, we compare six alternative proposals that are used in the literature to reduce the effects of outliers in the estimation of risk measures when using GARCH-type models. The methods are based on [1] correcting for significant outliers, [2] accommodating outliers using complex (e.g. fat-tail) distributions and [3] accounting for outlier effects by robust estimation. The main conclusions of the simulation study are that the presence of outliers bias these risk measures, being the proposal by Grané and Veiga (2010) that providing the highest bias reduction. From the out-of-sample results for four international stock market indexes we found weak evidence that more complex models (specification and error distribution) perform better in estimating the minimum capital risk requirements during the last global financial crisis.

This study examines the impact of macroeconomic factors on the capital structures of Nigerian quoted firms. The two-stage least squares (2SLS), GMM and GARCH estimation techniques reveal that corporate borrowing is a declining function of macroeconomic conditions in Nigeria and macro-effects are significant across the 17 selected industries. Specifically, market leverage increases with debt market access and economic growth (measured by growth in GDP) but book leverage behaves counter-cyclically as it declines with equity market conditions, term spread and expected inflation. Unemployment rate, monetary policy, government borrowing have no significant impact on the borrowing behavior of firms. Taken together, the macroeconomic conditions rationalize conservative debt usage of Nigerian quoted firms and low leverage puzzle for some firms. The study recommends prudent use of debt in order to manage the overall risk of firms and preserve long-term stability.
Keywords: Capital structure, macroeconomic conditions, unemployment risk, monetary policy, fiscal policy.
JEL Classification: G30, G32, G33, E20, E30, E40, E50, E60.

This paper reports evidence to support a relationship between risk propensity, risk perception,
and risk-taking behaviour of investors in an emerging market. Primary data were gathered using
a validated structured questionnaire, which was self-administered by respondents: there were 162
investors from 8 stockbroking companies. A multiple regression was used to test the direct and
indirect effects of the identified behavioural characteristics on investment decision. Risk
propensity was found to be positively related to risk-taking behaviour whereas risk perception
was negatively related to risk-taking behaviour. It was further found that risk perception partially
mediates the effect of propensity to take risk. This suggests that the perceptual framing of a
situational context in the investors’ thought processes reduces but it does not totally overwhelm
the innate personality traits with respect to either the investor’s risk-seeking or risk-averseness.
The tendency to engage in risky behaviour is more psychological in nature. The implications of
the research are further explored.

The development of the interaction of monetary indicators, foreign stocks, and the stock price index in the context of the dynamics of the relationship are discussed short and long term. The analysis technique used is cointegration analysis and error correction mechanisms for the period 2003-2010. From the research results that: a) in the short term, rising inflation will lead to decline in the stock price index, but in the long run, instead of rising inflation, ceteris paribus, it will increase the stock price index. Partially, the inflation rate did not significantly influence the stock price index in both the short-and long-term, b) 3-month SBI rate negative, but not significant effect on the stock price index in both the short and long term, c) increase in the number of money supply in the short term, will increase the stock price index, both in short and long term; d) the exchange value of rupiah against the U.S. dollar has significant negative effect on stock price index, both short and long term; e) reserves countries have positive and significant impact on the stock price index in both the short-and long-term; f) for foreign exchange, short-term period, the increase in the composite index of stock markets of Malaysia and Singapore ceteris paribus, it will reduce Indonesia's stock index, while for two other exchanges, PSEI and Shanghai, have positive implications of IDX fluctuations. Fluctuations in both the exchange of each will improve the IDX Composite Index. In the long term, unless the Singapore stock market, fluctuations in the three stock exchanges will improve IDX; g) simultaneously, the monetary indicators and the foreign exchanges have positive and significant impact on the stock price index, both short term and long term.