Return of Equity Issues in the Spanish Stock Market from the Investor’s Perspective, during the 1997-2012 Period

Is it profitable for an investor, from a risk-return perspective, to acquire a stake in a quoted company when a capital increase is announced? This paper analyses the return obtained from the investment in equity issues with cash contribution and pre-emptive rights, aimed at funding corporate activities: acquisitions, investments in new facilities and/or strengthening the balance sheet of the companies undertaking the equity issue. During the 16 years covered by the study, the results show a negative average excess risk-adjusted return of almost 5%, from the moment that the equity offer is announced until the completion of the preferential subscription period. To obtain this excess return, the difference between the nominal Internal Rate of Return (IRR) and the expected return, using the CAPM, is computed for each equity issue. The intention behind this method is to eliminate the effects of time and any other possible effect on the stock price during the period of the analysis.The results from this article are consistent with the Pecking Order theory for the Spanish Stock Market also six months after the preferential subscription period. However, there is a positive return after three months.

Explanation of changes in real estate stock market

The aim of this study is to explain the changes in the real estate prices as well as in the real estate stock market prices, using some macro-economic explanatory variables, such as the gross domestic product (GDP), the real interest rate and the unemployment rate. Several regressions have been carried out in order to express some types of incremental and absolute deflated real estate lock market indexes in terms of the macro-economic variables. The analyses are applied to the Swedish economy. The period under study is 1984-1994. Time series on monthly data are used. i.e. the number of data-points is 132. If time leads/lags are introduced in the e regressions, significant improvements in the already high correlations are achieved. The signs of the coefficients for IR, UE and GDP are all what one would expect to see from an economic point of view: those for GDP are all positive, those for both IR and UE are negative. All the regressions have high R2 values. Both markets anticipate change in the unemployment rate by 6 to 9 months, which seems reasonable because such change can be forecast quite reliably. But, on the contrary, there is no reason why they should anticipate by 3-6 months changes in the interest rate that can hardly be reliably forecast so far in advance.

The debt, the stock market and the state-owned enterprises. The sources of chaos on the Chinese financial markets. OSW Commentary NUMBER 201/16.03.2016

The government’s extensive programme for stimulating the economy has enabled China to maintain high economic growth after the global financial crisis in 2008. However, this success has come at the price of a number of negative economic phenomena and the consequences they have had are the major challenge for the government today. The vast programme of investments in infrastructure, construction and fixed assets, which has been the main source of economic growth over the past few years, has caused a rapid increase in China’s debt from 158% of GDP in 2007 to 282% in 2014. Along with the local governments in charge of implementing the programme, the Chinese sector of state-owned enterprises (SOEs) has been heavily burdened by the stimulation policy. The sector’s profitability has fallen, its indebtedness has increased and management problems have been revealed.

The influence of corporate governance characteristics on changes in risk following the global financial crisis evidence from companies listed in the portuguese stock market

Apesar da crescente regulação da atividade empresarial e do estabelecimento de normas e recomendações relativamente ao governo das sociedades verificados desde o início da década passada, as empresas de grande parte dos sectores de atividade económica foram seriamente afetadas durante a crise financeira global. Este estudo permite concluir que houve aumentos significativos no risco total e idiossincrático das empresas não financeiras cotadas na Euronext Lisboa após a falência do banco Lehman Bothers, a 15 de Setembro de 2008. Estes resultados são coerentes com o aumento da incerteza dos investidores verificado durante o período de crise, resultante do colapso de alguns dos maiores bancos do último século, que se traduziu numa falta de confiança generalizada nas instituições financeiras que resultou em maiores dificuldades na obtenção de créditos bancários e num aumentos dos custos de capital, durante este período. Os resultados sugerem que as alterações verificadas nas medidas do risco variaram de acordo com as características de governação e características específicas das empresas, quer num horizonte temporal mais curto, quer num horizonte temporal mais alargado. O mercado de capitais premiou as empresas com um número relativamente maior de administradores não-executivos e com administradores que exercem (em média) cargos de gestão num maior número de empresas ou instituições. Por outro lado, o mercado de capitais penalizou as empresas com um número relativamente maior de administradores independentes, maior concentração de capital, maiores oportunidades de crescimento, maior alavancagem financeira e maior liquidez corrente.

Stock market study : regulation of unlisted securities : hearings before a subcommittee of the Committee on Banking and Currency, United States Senate, Eighty-fourth Congress first session, on S. 2054, a bill to amend the Securities Exchange Act of 1934, as amended.

Hearings held June 27, 1955-July 6, 1956.

How I made $2,000,000 in the stock market.

Mode of access: Internet.

Making money in the stock market,

Mode of access: Internet.

The stock market barometer : a study of its forecast value based on Charles H. Dow's theory of the price movement. With an analysis of the market and its history since 1897 /

Reprint of 1922 ed. with a new introduction.

New levels in the stock market,

Mode of access: Internet.

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.

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.

Rule extraction from technology IPOs in the US stock market

Machine learning techniques for prediction and rule extraction from artificial neural network methods are used. The hypothesis that market sentiment and IPO specific attributes are equally responsible for first-day IPO returns in the US stock market is tested. Machine learning methods used are Bayesian classifications, support vector machines, decision tree techniques, rule learners and artificial neural networks. The outcomes of the research are predictions and rules associated With first-day returns of technology IPOs. The hypothesis that first-day returns of technology IPOs are equally determined by IPO specific and market sentiment is rejected. Instead lower yielding IPOs are determined by IPO specific and market sentiment attributes, while higher yielding IPOs are largely dependent on IPO specific attributes.