Forecasting Multivariate Time Series under Present-Value-Model Short- and Long-run Co-movement Restrictions

This paper has two original contributions. First, we show that the present value model (PVM hereafter), which has a wide application in macroeconomics and fi nance, entails common cyclical feature restrictions in the dynamics of the vector error-correction representation (Vahid and Engle, 1993); something that has been already investigated in that VECM context by Johansen and Swensen (1999, 2011) but has not been discussed before with this new emphasis. We also provide the present value reduced rank constraints to be tested within the log-linear model. Our second contribution relates to forecasting time series that are subject to those long and short-run reduced rank restrictions. The reason why appropriate common cyclical feature restrictions might improve forecasting is because it finds natural exclusion restrictions preventing the estimation of useless parameters, which would otherwise contribute to the increase of forecast variance with no expected reduction in bias. We applied the techniques discussed in this paper to data known to be subject to present value restrictions, i.e. the online series maintained and up-dated by Shiller. We focus on three different data sets. The fi rst includes the levels of interest rates with long and short maturities, the second includes the level of real price and dividend for the S&P composite index, and the third includes the logarithmic transformation of prices and dividends. Our exhaustive investigation of several different multivariate models reveals that better forecasts can be achieved when restrictions are applied to them. Moreover, imposing short-run restrictions produce forecast winners 70% of the time for target variables of PVMs and 63.33% of the time when all variables in the system are considered.

Eficiência da magic formula de value investing no mercado brasileiro

O objetivo deste trabalho é realizar procedimento de back-test da Magic Formula na Bovespa, reunindo evidências sobre violações da Hipótese do Mercado Eficiente no mercado brasileiro. Desenvolvida por Joel Greenblatt, a Magic Formula é uma metodologia de formação de carteiras que consiste em escolher ações com altos ROICs e Earnings Yields, seguindo a filosofia de Value Investing. Diversas carteiras foram montadas no período de dezembro de 2002 a maio de 2014 utilizando diferentes combinações de número de ativos por carteira e períodos de permanência. Todas as carteiras, independentemente do número de ativos ou período de permanência, apresentaram retornos superiores ao Ibovespa. As diferenças entre os CAGRs das carteiras e o do Ibovespa foram significativas, sendo que a carteira com pior desempenho apresentou CAGR de 27,7% contra 14,1% do Ibovespa. As carteiras também obtiveram resultados positivos após serem ajustadas pelo risco. A pior razão retorno-volatilidade foi de 1,2, comparado a 0,6 do Ibovespa. As carteiras com pior pontuação também apresentaram bons resultados na maioria dos cenários, contrariando as expectativas iniciais e os resultados observados em outros trabalhos. Adicionalmente foram realizadas simulações para diversos períodos de 5 anos com objetivo de analisar a robustez dos resultados. Todas as carteiras apresentaram CAGR maior que o do Ibovespa em todos os períodos simulados, independentemente do número de ativos incluídos ou dos períodos de permanência. Estes resultados indicam ser possível alcançar retornos acima do mercado no Brasil utilizando apenas dados públicos históricos. Esta é uma violação da forma fraca da Hipótese do Mercado Eficiente.

Mitigating high ‘equity capital’ risk exposure to ‘small cap’ sector in India: analysing ‘key factors of success’ for ‘Institutional Investors’ whilst Investing in small cap sector in India

This paper deals with the subject of mitigating high ‘Equity Capital’ Risk Exposure to ‘Small Cap’ Sector in India. Institutional investors in India are prone to be risk averse when it comes to investing in the small cap sector in India as they find the companies risky and volatile. This paper will help analyse ‘Key Factors of success’ for ‘Institutional Investors’ whilst investing in Small Cap sector in India as some of these Indian small cap stocks offer handsome returns despite economic downturn. This paper has been harnessed carefully under the influence of expert investors, which includes Benjamin Graham (Security Analysis); Warren Buffet; Philip Fisher (Common Stocks and Uncommon Profits); and Aswath Damodaran.

Forecasting multivariate time series under present-value-model short- and long-run co-movement restrictions

Using a sequence of nested multivariate models that are VAR-based, we discuss different layers of restrictions imposed by present-value models (PVM hereafter) on the VAR in levels for series that are subject to present-value restrictions. Our focus is novel - we are interested in the short-run restrictions entailed by PVMs (Vahid and Engle, 1993, 1997) and their implications for forecasting. Using a well-known database, kept by Robert Shiller, we implement a forecasting competition that imposes different layers of PVM restrictions. Our exhaustive investigation of several different multivariate models reveals that better forecasts can be achieved when restrictions are applied to the unrestricted VAR. Moreover, imposing short-run restrictions produces forecast winners 70% of the time for the target variables of PVMs and 63.33% of the time when all variables in the system are considered.

Mecanismo LPVR - Least Present Value of Revenues como mitigador de riscos em concessões rodoviárias: uma aplicação a um caso brasileiro

Nos últimos anos o governo brasileiro tem adotado a postura de incentivo a projetos de infraestrutura, sendo as concessões rodoviárias um dos principais mecanismos. Muito se discute sobre a melhor forma de remuneração das concessionárias, sem que, ao mesmo tempo, os usuários não tenham um custo elevado e possam usufruir de bons serviçoes prestados.Essa discussão passa, principalmente, por uma análise de risco de tráfego, que hoje é inteiramente alocado as cconcessionárias. A metodologia utilizada nos últimos leilões segue uma exigência de Taxa Interna de Retorno ( TIR ) máxima, pelo Poder Concedente ( ANTT ), em termos reais e um prazo de concessão fixo. A partir de custos e investimentos estimados em determinada concessão, a ANTT define uma tarifa-teto a ser cobrada pela concessionária aos usuários através da TIR máxima exigida no projeto. Esta TIR é calculada com base no custo médio ponderado de capital ( WACC ) de empresas do setor, que tem ações negociadas na BM&F Bovespa, utilizando-se apenas dados domésticos. Neste trabalho é proposto um modelo alternativo, baseado no menor valor presente das receitas ( LPVR - Least Present Value of Revenues ). Neste modelo observamos que o risco de tráfego é bem menor para a concessionária, pois a concessão só se expira quando determinado nível de receitas exigido pela concessionária é atingido. Ou seja, para tal, é necessário um modelo de prazo flexível. Neste mecanismo, entretanto, com menor risco de tráfego, o upside e o downside, em termos de retorno, são menores em comparação com o modelo vigente. Utilizando este modelo, o Poder Concedente pode também definir um vencedor para o leilão ( a concessionária que ofertar o menor valor presente das receitas ) e também se utilizar da proposta de simulação de tráfegos para a definição de um prazo máximo para a concessão, em caso de implementação do mecanismo proposto.

Valuing emerging markets companies : new approaches to determine the effective exposure to country risk

The aim of this paper is to propose new methods to measure the effective exposure to country risk of emerging-market companies. Starting from Damodaran (2003), we propose seven new approaches and a revised CAPM for emerging markets companies. The “Prospective Lambda” represents the effective exposure according to analysts’ estimates of growth. The “Relative Lambda” relies on the firm value estimated through a relative valuation. The “Retrospective Lambda” represents the ex-post effective exposure to country risk. The “Company Effective Risk Premium” is a generalization of the Retrospective Lambda, and expresses the premium effectively requested by investors to invest in that specific company in the past year. “The Actual Lambda” and the “Company Actual Risk Premium” represent, respectively, the actual exposure to country risk of a company and the actual premium requested by investors to invest in that specific company. The “Industry Lambda” reflects the median exposure to country risk of the industry in which the company belongs. We tested our new measures of exposure to country risk on the Latin American emerging markets companies according to the classification of the MSCI Emerging Markets Latin America Index. The results confirm that the new approaches can be effectively applied by financial analysts to stable-growth companies that operate in emerging markets and to mature markets companies that operate in emerging markets, providing with a more reliable estimate of both the premium effectively requested by investors in the past and the actual premium. Applying the new approaches, the cost of equity reflects the effective exposure of a company to country risk without being over- or underestimated, as is the case with other existing approaches.

The influence of the tag-along rights in the value of companies: an event study of the effects on the market and service companies

The aim of this work is to check the effect of granting tag-along rights to stockholders by analyzing the behavior of the return of the stock. To do so we carried out event studies for a group of 21 company stocks, divided into service provider companies and others, who granted this right to their stockholders after Law 10,303 was passed in October, 2001. In the test we used two models for estimating abnormal returns: adjusted to the market and adjusted to the risk and market. The results of the tests we carried out based on these models did not capture abnormal returns (surpluses), telling us that the tag-along rights did not affect the pattern of daily returns of the stocks of companies traded on BOVESPA (The Sao Paulo Stock Exchange). We did not expect this result because of the new corporate governance practices adopted by companies in Brazil.

Business Plan, financial and risk analysis from the start-up mathrix

Mathrix is an e-learning math website that will be launched in March 2016. This master thesis offered a unique chance to interact with experienced supervisors in venture capitalism and project investment. It could serve as guidelines for entrepreneurs who intend to raise funds. Starting with the company’s business plan, the thesis focuses on estimating the company’s value with its return on investment using three scenarios and taking into consideration the risks evolved.

Multistep stochastic mirror descent for risk-averse convex stochastic programs based on extended polyhedral risk measures

We consider risk-averse convex stochastic programs expressed in terms of extended polyhedral risk measures. We derive computable con dence intervals on the optimal value of such stochastic programs using the Robust Stochastic Approximation and the Stochastic Mirror Descent (SMD) algorithms. When the objective functions are uniformly convex, we also propose a multistep extension of the Stochastic Mirror Descent algorithm and obtain con dence intervals on both the optimal values and optimal solutions. Numerical simulations show that our con dence intervals are much less conservative and are quicker to compute than previously obtained con dence intervals for SMD and that the multistep Stochastic Mirror Descent algorithm can obtain a good approximate solution much quicker than its nonmultistep counterpart. Our con dence intervals are also more reliable than asymptotic con dence intervals when the sample size is not much larger than the problem size.