Empirical Evidence of Conditional Heteroskedasticity in Vietnam’s Stock Returns Time Series

This paper confirms presence of GARCH(1,1) effect on stock return time series of Vietnam’s newborn stock market. We performed tests on four different time series, namely market returns (VN-Index), and return series of the first four individual stocks listed on the Vietnamese exchange (the Ho Chi Minh City Securities Trading Center) since August 2000. The results have been quite relevant to previously reported empirical studies on different markets.

Predicting stock index volatility: can market volume help?

This paper explores a number of statistical models for predicting the daily stock return volatility of an aggregate of all stocks traded on the NYSE. An application of linear and non-linear Granger causality tests highlights evidence of bidirectional causality, although the relationship is stronger from volatility to volume than the other way around. The out-of-sample forecasting performance of various linear, GARCH, EGARCH, GJR and neural network models of volatility are evaluated and compared. The models are also augmented by the addition of a measure of lagged volume to form more general ex-ante forecasting models. The results indicate that augmenting models of volatility with measures of lagged volume leads only to very modest improvements, if any, in forecasting performance.

Estilo, comovimento e previsibilidade de retorno: uma análise do mercado brasileiro entre 2000-2011

Wahal e Yavuz (2009) divulgaram trabalho ampliando a literatura da teoria de finanças comportamentais, unindo os conceitos de momento, estilo e comovimento como ferramentas de previsibilidade de retorno em investimentos. Eles descobriram que ativos com maior comovimento apresentam retornos mais elevados que os de baixo comovimento. Buscamos replicar a sua metodologia ao mercado brasileiro de maneira aplicável a realidade de baixa liquidez e quantidade reduzida de ativos do nosso mercado de ações. Nossos resultados não apresentaram a mesma tendência do trabalho original, porém verificamos, ainda que de forma limitada, a possibilidade de explorar estratégias lucrativas usando este arcabouço.

Automatic model selection for forecasting brazilian stock returns

This study aims to contribute on the forecasting literature in stock return for emerging markets. We use Autometrics to select relevant predictors among macroeconomic, microeconomic and technical variables. We develop predictive models for the Brazilian market premium, measured as the excess return over Selic interest rate, Itaú SA, Itaú-Unibanco and Bradesco stock returns. We nd that for the market premium, an ADL with error correction is able to outperform the benchmarks in terms of economic performance. For individual stock returns, there is a trade o between statistical properties and out-of-sample performance of the model.

Consumption-wealth ratio and expected stock returns: evidence from panel data

This paper investigates the role of consumption-wealth ratio on predicting future stock returns through a panel approach. We follow the theoretical framework proposed by Lettau and Ludvigson (2001), in which a model derived from a nonlinear consumer’s budget constraint is used to settle the link between consumption-wealth ratio and stock returns. Using G7’s quarterly aggregate and financial data ranging from the first quarter of 1981 to the first quarter of 2014, we set an unbalanced panel that we use for both estimating the parameters of the cointegrating residual from the shared trend among consumption, asset wealth and labor income, cay, and performing in and out-of-sample forecasting regressions. Due to the panel structure, we propose different methodologies of estimating cay and making forecasts from the one applied by Lettau and Ludvigson (2001). The results indicate that cay is in fact a strong and robust predictor of future stock return at intermediate and long horizons, but presents a poor performance on predicting one or two-quarter-ahead stock returns.

Automatic model selection for forecasting Brazilian stock returns

This study aims to contribute on the forecasting literature in stock return for emerging markets. We use Autometrics to select relevant predictors among macroeconomic, microeconomic and technical variables. We develop predictive models for the Brazilian market premium, measured as the excess return over Selic interest rate, Itaú SA, Itaú-Unibanco and Bradesco stock returns. We find that for the market premium, an ADL with error correction is able to outperform the benchmarks in terms of economic performance. For individual stock returns, there is a trade o between statistical properties and out-of-sample performance of the model.

Exchange controls and European stock market integration

This paper examines the impact on stock price predictability that the removal of exchange controls had on major European countries during the late 1970s and 1980s. It is found that for Germany, Switzerland and France, the removal of exchange controls led to an increase in the interdependence between these and other markets. In contrast, there is little evidence of an increase in interdependence for the UK and Italy.

Essays in asset price bubbles

This thesis studies the field of asset price bubbles. It is comprised of three independent chapters. Each of these chapters either directly or indirectly analyse the existence or implications of asset price bubbles. The type of bubbles assumed in each of these chapters is consistent with rational expectations. Thus, the kind of price bubbles investigated here are known as rational bubbles in the literature. The following describes the three chapters. Chapter 1: This chapter attempts to explain the recent US housing price bubble by developing a heterogeneous agent endowment economy asset pricing model with risky housing, endogenous collateral and defaults. Investment in housing is subject to an idiosyncratic risk and some mortgages are defaulted in equilibrium. We analytically derive the leverage or the endogenous loan to value ratio. This variable comes from a limited participation constraint in a one period mortgage contract with monitoring costs. Our results show that low values of housing investment risk produces a credit easing effect encouraging excess leverage and generates credit driven rational price bubbles in the housing good. Conversely, high values of housing investment risk produces a credit crunch characterized by tight borrowing constraints, low leverage and low house prices. Furthermore, the leverage ratio was found to be procyclical and the rate of defaults countercyclical consistent with empirical evidence. Chapter 2: It is widely believed that financial assets have considerable persistence and are susceptible to bubbles. However, identification of this persistence and potential bubbles is not straightforward. This chapter tests for price bubbles in the United States housing market accounting for long memory and structural breaks. The intuition is that the presence of long memory negates price bubbles while the presence of breaks could artificially induce bubble behaviour. Hence, we use procedures namely semi-parametric Whittle and parametric ARFIMA procedures that are consistent for a variety of residual biases to estimate the value of the long memory parameter, d, of the log rent-price ratio. We find that the semi-parametric estimation procedures robust to non-normality and heteroskedasticity errors found far more bubble regions than parametric ones. A structural break was identified in the mean and trend of all the series which when accounted for removed bubble behaviour in a number of regions. Importantly, the United States housing market showed evidence for rational bubbles at both the aggregate and regional levels. In the third and final chapter, we attempt to answer the following question: To what extend should individuals participate in the stock market and hold risky assets over their lifecycle? We answer this question by employing a lifecycle consumption-portfolio choice model with housing, labour income and time varying predictable returns where the agents are constrained in the level of their borrowing. We first analytically characterize and then numerically solve for the optimal asset allocation on the risky asset comparing the return predictability case with that of IID returns. We successfully resolve the puzzles and find equity holding and participation rates close to the data. We also find that return predictability substantially alter both the level of risky portfolio allocation and the rate of stock market participation. High factor (dividend-price ratio) realization and high persistence of factor process indicative of stock market bubbles raise the amount of wealth invested in risky assets and the level of stock market participation, respectively. Conversely, rare disasters were found to bring down these rates, the change being severe for investors in the later years of the life-cycle. Furthermore, investors following time varying returns (return predictability) hedged background risks significantly better than the IID ones.

G7 Stock Markets: Who is The First to Defeat The DCCA Correlation?

Following the methodology of Ferreira and Dionísio (2016), the objective of this paper is to analyze the behavior stock markets in the G7 countries and find which of those countries is the first to reach levels of long-range correlations that are not significant. We carry out this analysis using detrended cross-correlation analysis and its correlation coefficient, to check for the existence of long-range dependence in time series. The existence of long-range dependence could be understood as a possibility of EMH violation. This analysis remains interesting because studies are not conclusive about the existence or not of long memory in stock return rates.

A comparison of alternative bankruptcy prediction models

Early models of bankruptcy prediction employed financial ratios drawn from pre-bankruptcy financial statements and performed well both in-sample and out-of-sample. Since then there has been an ongoing effort in the literature to develop models with even greater predictive performance. A significant innovation in the literature was the introduction into bankruptcy prediction models of capital market data such as excess stock returns and stock return volatility, along with the application of the Black–Scholes–Merton option-pricing model. In this note, we test five key bankruptcy models from the literature using an upto- date data set and find that they each contain unique information regarding the probability of bankruptcy but that their performance varies over time. We build a new model comprising key variables from each of the five models and add a new variable that proxies for the degree of diversification within the firm. The degree of diversification is shown to be negatively associated with the risk of bankruptcy. This more general model outperforms the existing models in a variety of in-sample and out-of-sample tests.

Jackknife for bias reduction in predictive regressions

One of the fundamental econometric models in finance is predictive regression. The standard least squares method produces biased coefficient estimates when the regressor is persistent and its innovations are correlated with those of the dependent variable. This article proposes a general and convenient method based on the jackknife technique to tackle the estimation problem. The proposed method reduces the bias for both single- and multiple-regressor models and for both short- and long-horizon regressions. The effectiveness of the proposed method is demonstrated by simulations. An empirical application to equity premium prediction using the dividend yield and the short rate highlights the differences between the results by the standard approach and those by the bias-reduced estimator. The significant predictive variables under the ordinary least squares become insignificant after adjusting for the finite-sample bias. These discrepancies suggest that bias reduction in predictive regressions is important in practical applications.

Does Uncertainty Affect Investment and Labor Demand?

This paper analyzes the effect of uncertainty on investment and labor demand for Finnish firms during the time period 1987 – 2000. Utilizing a stock return based measure of uncertainty decomposed into systematic and idiosyncratic components, the results reveal that idiosyncratic uncertainty significantly reduces both investment and labor demand. Idiosyncratic uncertainty seems to influence investment in the current period, whereas the depressing effect on labor demand appears with a one-year lag. The results provide support that the depressing effect of idiosyncratic uncertainty on investment is stronger for small firms in comparison to large firms. Some evidence is reported regarding differential effects of uncertainty on labor demand conditional on firm characteristics. Most importantly, the depressing effect of lagged idiosyncratic uncertainty on labor demand tends to be stronger for diversified firms compared with focused firms.

Canadian investors and the discount on closed-end funds

Small investors' sentiment has been proposed by behaviouralists to explain the existence and behavior of discount on closed-end funds (CEFD). The empirical tests of this sentiment hypothesis so far provide equivocal results. Besides, most of out-of-sample tests outside U.S. are not robust in the sense that they fail to well control other firm characteristics and risk factors that may explain stock return and to provide a formal cross-sectional test of the link between CEFD and stock return. This thesis explores the role of CEFD in asset pricing and further validates CEFD as a sentiment proxy in Canadian context and augments the extant studies by examining the redemption feature inherent in Canadian closed-end funds and by enhancing the robustness of the empirical tests. Our empirical results document differential behaviors in discounts between redeemable funds and non-redeemable funds. However, we don't find supportive evidence of CEFD as a priced factor. Specifically, the stocks with different exposures to CEFD fail to provide significantly different average return. Nor does CEFD provide significant incremental explanatory power, after controlling other well-known firm characteristics and risk factors, in cross-sectional as well as time-series variation of stock return. This evidence, together with the findings from our direct test of CEFD as a sentiment index, suggests that CEFD, even the discount on traditional non-redeemable closed-end funds, is unlikely to be driven by elusive sentiment in Canada.

Margin requirements and volatility : evidence from Canadian stocks

Margin policy is used by regulators for the purpose of inhibiting exceSSIve volatility and stabilizing the stock market in the long run. The effect of this policy on the stock market is widely tested empirically. However, most prior studies are limited in the sense that they investigate the margin requirement for the overall stock market rather than for individual stocks, and the time periods examined are confined to the pre-1974 period as no change in the margin requirement occurred post-1974 in the U.S. This thesis intends to address the above limitations by providing a direct examination of the effect of margin requirement on return, volume, and volatility of individual companies and by using more recent data in the Canadian stock market. Using the methodologies of variance ratio test and event study with conditional volatility (EGARCH) model, we find no convincing evidence that change in margin requirement affects subsequent stock return volatility. We also find similar results for returns and trading volume. These empirical findings lead us to conclude that the use of margin policy by regulators fails to achieve the goal of inhibiting speculating activities and stabilizing volatility.

Profitable opportunities around macroeconomic announcements in the U.S. Treasury market

This thesis studies the impact of macroeconomic announcements on the U.S. Treasury market and investigates profitable opportunities around macroeconomic announcements using data from the eSpeed electronic trading platform. We investigate how macroeconomic announcements affect the return predictability of trade imbalance for the 2-year, 5-year, IO-year U.S. Treasury notes and 30-year U.S. Treasury bonds. The goal of this thesis is to develop a methodology to identify informed trades and estimate the trade imbalance based on informed trades. We use the daily order book slope as a proxy for dispersion of beliefs among investors. Regression results in this thesis indicate that, on announcement days with a high dispersion of beliefs, daily trade imbalance estimated by informed trades significantly predicts returns on the following day. In addition, we develop a trade-imbalance based trading strategy conditional on dispersion of beliefs, informed trades, and announcement days. The trading strategy yields significantly positive net returns for the 2-year T-notes.