Non-linear causality between the stock and real estate markets of Western European countries: Evidence from rank tests

Using the non-parametric rank tests proposed by Breitung (2001), we set out in this study to determine whether any non-linear long-run equilibrium relationship exists between the stock and real estate markets of Western European countries. We go on to adopt the threshold error-correction model (TECM) to determine whether a similar relationship is discernible possibly non-linear functions of the log-price of these two markets. The findings clearly point to the existence of long-run unidirectional and bidirectional causality between the real estate market and the stock market in regions both above and below the threshold level. Finally, we find the existence of both wealth and credit price effects in the real estate markets and stock markets of Western European countries, which thereby offer financial institutions and individual investors in their construction of long-term investment portfolios within these two asset markets.     

Stock exchange mergers and return co-movement: A flexible dynamic component correlations model

The creation of a common cross-border stock trading platform is found, by use of a Flexible Dynamic Component Correlations (FDCC) model, to have increased long-run trends in conditional correlations between foreign and domestic stock market returns.     

South African stock return predictability in the context data mining: The role of financial variables and international stock returns

In this paper, we examine the predictive ability, both in-sample and the out-of-sample, for South African stock returns using a number of financial variables, based on monthly data with an in-sample period covering 1990:01 to 1996:12 and the out-of-sample period of 1997:01 to 2010:04. We use the t-statistic corresponding to the slope coefficient in a predictive regression model for in-sample predictions, while for the out-of-sample, the MSE-F and the ENC-NEW tests statistics with good power properties were utilised. To guard against data mining, a bootstrap procedure was employed for calculating the critical values of both the in-sample and out-of-sample test statistics. Furthermore, we use a procedure that combines in-sample general-to-specific model selection with out-of-sample tests of predictive ability to further analyse the predictive power of each financial variable. Our results show that, for the in-sample test statistic, only the stock returns for our major trading partners have predictive power at certain short and long run horizons. For the out-of-sample tests, the Treasury bill rate and the term spread together with the stock returns for our major trading partners show predictive power both at short and long run horizons. When accounting for data mining, the maximal out-of-sample test statistics become insignificant from 6-months onward suggesting that the evidence of the out-of-sample predictability at longer horizons is due to data mining. The general-to-specific model shows that valuation ratios contain very useful information that explains the behaviour of stock returns, despite their inability to predict stock return at any horizon. The model also highlights the role of multiple variables in predicting stock returns at medium- to long run horizons.     

Estimation of conditional time-homogeneous credit quality transition matrices

This paper presents a methodology for estimating time-homogeneous credit quality transition matrices. Using a unique data set on credit ratings of commercial loans in Colombia, we show that 70% of the time we cannot reject the null hypothesis of time homogeneity of transition matrices estimated this way. We also find that obtaining matrices for different subsamples is not necessary, given the similarities of the survival functions.     

Asset prices in a Huggett economy

This paper explores asset pricing in economies where there is no direct insurance against idiosyncratic risks but other assets can be used for self-insurance, subject to exogenously-imposed borrowing limits. We analyze an endowment economy, based on Huggett (1993) [11], both with and without aggregate risk. Our main innovation is that we obtain full analytical tractability by studying the case with “maximally tight” borrowing constraints. We illustrate by looking at riskless bonds, equity, and the term structure of interest rates, and we show that the model can reproduce many features of observed asset prices when idiosyncratic risks are quantitatively reasonable.     

Modelling the risk–return relation for the S&P 100: The role of VIX

A significantly positive risk–return relation for the S&P 100 market index is detected if the implied volatility index (VIX) is allowed for as an exogenous variable in the conditional variance equation. This result holds for 4 alternative GARCH specifications, irrespective of the conditional distribution, and regardless of whether the conditional mean equation includes a constant term. This finding is robust to sub-samples, and to using VIX innovations to control for dividend yield and trading volume effects. Monte Carlo evidence suggests that if VIX is not included, the risk–return relation is more likely to be negative or weak, in line with several previous studies. If VIX is included, the distribution of the risk–return parameter has more than 99% of its mass in the area of positive values. We conclude that VIX carries important forward-looking information which improves the precision of the conditional variance estimation and, subsequently, reveals a significantly positive relation.     

High yield spreads,real economic activity,and the financial accelerator

We study the leading properties of 30 US high yield spreads for economic growth between 1996 and 2012 and show that they disappeared in the second half of the 2000s. Our empirical findings demonstrate the unreliability of high yield spreads as leading indicators and cast doubts on the existence of a strong and functioning financial accelerator in recent years.     

Stock exchange mergers and weak form of market efficiency: The case of Euronext Lisbon

This exploratory paper is among the first to examine the impact of stock exchange mergers on informational market efficiency. We focus on the merger of Bolsa de Valores de Lisboa e Porto (Portuguese Stock Exchange) with Euronext in 2002 (that created Euronext Lisbon). To investigate this question we perform numerous statistical tests: serial correlation test (ACF test), runs test, unit root test (Kwiatkowski, Philips, Schmidt, & Shin, 1992), multiple variance ratio test (Chow & Denning, 1993) and ranks and signs test (Wright, 2000).The results indicate that the Portuguese Equity Market is inefficient in weak form during pre-merger period implying that investors possessed an opportunity to earn abnormal returns though small in magnitude. The results, sensitive to the methodology used, indicate a mixed evidence of improvement in market efficiency during the post-merger period. Although the findings are mixed, yet most tests show a tendency of improved efficiency.     

Does financial liberalization improve the allocation of investment?: Micro-evidence from developing countries

Using firm level panel data from 12 developing countries we explore whether financial liberalization improves the efficiency with which investment funds are allocated. A summary index of the efficiency of investment allocation that measures whether investment funds are going to firms with a higher marginal return to capital is developed. We examine the relationship between this and various measures of financial liberalization and find that liberalization increases the efficiency with which investment funds are allocated. This holds after various robustness checks and is consistent with firm level evidence of a stronger association between investment and fundamentals after financial liberalization.     

Price manipulation in an experimental asset market

We analyze in the laboratory whether an uninformed trader is able to manipulate the price of a financial asset by comparing the results of two experimental treatments. In the benchmark treatment, 12 subjects trade a common value asset that takes either a high or a low value. Only three subjects know the actual value of the asset while the market is open for trading. The manipulation treatment is identical to the benchmark treatment apart from the fact that we introduce a computer program as an additional uninformed trader. This robot buys a fixed number of shares in the beginning of a trading period and sells them again afterwards. Our main result shows that the last contract price is significantly higher in the manipulation treatment if the asset takes a low value and that private information is very well disseminated by both markets if the value of the asset is high. Finally, even though this simple manipulation program loses money on average, it is profitable in some instances.     

GARCH with omitted persistent covariate

This paper analyzes the effect of omitting a persistent covariate in the GARCH-X model. In particular, we show that if the relevant persistent covariate is omitted and the usual GARCH(1,1) model is fitted, the model will be estimated approximately as an IGARCH model. This may well explain the ubiquitous evidence of the IGARCH in empirical volatility analysis.     

Sunspots and predictable asset returns

This paper uses a stylised asset-pricing model to show that sunspots may cause asset returns to be predictable, a widely documented feature of many speculative markets. This result parallels and extends previous works showing that sunspots render asset prices excessively volatile.