Giulio Palomba

Investors' Behaviour in the Chinese Stock Exchanges: Empirical Evidence in a Systemic Approach

This paper investigates the Chinese mainland Stock Exchanges and their following interconnecting features: savers’ attitude towards stock investments, investors’ trading behaviour and stock returns explanations. We evaluate the effectiveness of the recent efforts made by the Chinese authorities to improve the level of legal protections for shareholders and the opening-up of the Chinese Stock Markets to foreign investors. The whole analysis is carried out through a system of simultaneous equations. The main results are that Chinese shareholders and stock markets are mostly driven by emotional behaviour. Stock market returns are barely influenced by the overall Chinese economic booming, but reveal the presence of speculative influences. Investors’ behaviour, as well as general trading activities, hardly seems to be affected by the legal framework introduced by the national Authorities.

Nonlinear adjustment in US bond yields: An empirical model with conditional heteroskedasticity

Starting from the work by Campbell and Shiller (Campbell, J.Y. and Shiller, R.J. (1987). Cointegration and tests of present value models. Journal of Political Economy, 95(5):1062-1088.), empirical analysis of interest rates has been conducted in the framework of cointegration. However, parts of this approach have been questioned recently, as the adjustment mechanism may not follow a simple linear rule; another line of criticism points out that stationarity of the spreads is difficult to maintain empirically. In this paper, we analyse data on US bond yields by means of an augmented VAR specification which approximates a generic nonlinear adjustment model. We argue that nonlinearity captures macro information via the shape of the yield curve and thus provides an alternative explanation for some findings that recently appeared in the literature. Moreover, we show how conditional heteroskedasticity can be taken into account via GARCH specifications for the conditional variance, either univariate or multivariate.

A Cross-Country Model for the Influence of the Pre-Trade Transparency on Market Liquidity and Price Volatility

In this article, we examine how the pre-trade transparency (PTT), a specific market microstructure feature, affects the liquidity and the price volatility of a stock exchange. In particular, we estimate a system of simultaneous equations for a set of liquidity and volatility indicators as a function of the PTT, given a series of control variables. Our main finding is that transparency increases liquidity and reduces volatility, and this is coherent with part of the existing literature. Moreover, the analysis provides empirical evidence of a series of liquidity—volatility interconnections.

The Indicators of Risk

Theoretically, financial risk tolerance depends upon different dimensions of risk. Some commentators (Cordell, 2002) have defined the term ‘risk tolerance’ to mean a combination of both ‘risk attitude’ (how much risk I choose to take) and ‘risk capacity’ (how much risk I can afford to take) (Roszkowski et al.). The first empirical goal of this study is to compare levels of financial risk tolerance which are obtained through alternative measurements: a traditional financial risk tolerance test, a psychophysiological test and the analysis of real life financial decisions. When using the financial risk tolerance test, we rely upon the self-evaluation of individuals; the computation from this test returns a biased risk tolerance level (BR). The second tool should provide a more objective evaluation of risk tolerance, given the fact that it relies on risky choices influenced by spontaneous somatic responses; it should return an unbiased risk tolerance level (UR). Finally, we considered the real life financial decisions of individuals obtaining a measure of the risk tolerance effectively assumed (the real life risk, RLR). Therefore we have the chance to compare how coherent RLR is in relation to both BR and UR.