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"Guerard, John"
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Introduction to financial forecasting in investment analysis
\"Forecasting--the art and science of predicting future outcomes--has become a crucial skill in business and economic analysis. This volume introduces the reader to the tools, methods, and techniques of forecasting, specifically as they apply to financial and investing decisions.
Book
A further analysis of robust regression modeling and data mining corrections testing in global stocks
In this analysis of the risk and return of stocks in global markets, we build a reasonably large number of stock selection models and create optimized portfolios to outperform a global benchmark. We apply robust regression techniques, LAR regression, and LASSO regression modeling to estimate stock selection models. Markowitz-based optimization techniques is used in portfolio construction within a global stock universe. We apply the Markowitz–Xu data mining corrections test to a global stock universe. We find that (1) robust regression applications are appropriate for modeling stock returns in global markets; (2) weighted latent root regression robust regression techniques work as well as LAR and LASSO-Regressions in building effective stock selection models; (3) mean–variance techniques continue to produce portfolios capable of generating excess returns above transactions costs; and (4) our models pass several data mining tests such that regression models produce statistically significant asset selection for global stocks. Recent Sturdy-Regression modeling technique may offer the greatest potential for further research for statistically based stock selection modeling.
Journal Article
Global portfolio construction with emphasis on conflicting corporate strategies to maximize stockholder wealth
This study addresses stock selection modeling and portfolio construction and implementation in global and U.S. markets in the context of multi-objectives optimization framework. We will show how forecasted earnings acceleration factors can enhance returns in global and U.S. stock markets. We construct Markowitz portfolios for Global and U.S. domestic Markets that offer superior returns-to-risk ratios, relative to domestic portfolios. We show how stock repurchases and corporate exports can be estimated and implemented as the third objective to generate statistically significant excess returns in global and U.S. stock markets. It is particularly interesting to note the conflicting corporate strategies’ impacts on stockholder wealth.
Journal Article
Automatic time series modeling and forecasting: a replication case study of forecasting real GDP, the unemployment rate and the impact of leading economic indicators
We test and report on time series modelling and forecasting using several US. Leading economic indicators (LEI) as an input to forecasting real US. GDP and the unemployment rate. These time series have been addressed before, but our results are more statistically significant using more recently developed time series modelling techniques and software. In this replication case study, we apply the Hendry and Doornik automatic time series PC-Give (AutoMetrics) methodology to the well-studied macroeconomic series, US. real GDP and the unemployment rate. The Autometrics system substantially reduces regression sum of squares measures relative to traditional variations on the random walk with drift model. The LEI are a statistically significant input to real GDP. A similar conclusion is found for the impact of the LEI and weekly unemployment claims series leading the unemployment rate series. We tested the forecasting ability of best univariate and best bivariate models over 60- and 120-period rolling windows and report considerable forecast error reductions. The adaptive averaging autoregressive model forecast ADA-AR and the adaptive learning forecast, ADL, produced the smallest root-mean-square errors and lowest mean absolute errors. Our results are greatly supportive of the significance for modeling and forecasting of the suggested input variables and they imply considerable improvements over all traditional benchmarks.
Journal Article
INVITED EDITORIAL COMMENT: An Introduction to Active Quant
Dimson edited an outstanding volume on stock market anomalies (Dimson [1988]), with much of the volume focused on low price-to-earnings and size factor, value line, and CAPM calendar effects.There is a substantial amount of evidence regarding mutual funds that Mr. Bogle might not be so wrong.[...]Shiller [2017] recently discussed lessons from the 1987 market plunge in theNew York Times .CTEF and GLER work in the three universes to produce highly statistically significant active returns and specific returns, but these returns are higher in emerging market portfolio than in XUS and GL portfolios.[...]emerging markets portfolio active and specific returns and IRs and Sharpe ratios rise as targeted tracking errors rise beyond 6%.[...]emerging market returns and rise relative to corresponding statistics on XUS and GL portfolios as targeted tracking errors rise beyond 6%.
Journal Article
The Development of Mean–Variance-Efficient Portfolios in Japan and the United States: 25 Years After; or, What Has Driven Stock Selection Models in Japan and the United States?
Stock selection models have been, and can be, effectively employed in Japan to deliver excess returns. In 1992, the initial year of this journal's publication, Guerard and Takano reported the effectiveness of mean-variance efficient portfolios for the Japanese and U.S. equity markets. In this update to celebrate 25 years of The Journal of Investing , the author uses a commercially available global database, FactSet, for the 2002 to June 2016 time period to address stock selection composite models and mean-variance efficient portfolios in Japan and the United States. He reports three results: (1) the original stock selection continues to be effective in Japan and the United States in the 2002 to June 2016 period; (2) the mean-variance efficient portfolios outperformed in Japan and the United States in the 2002 to June 2016 period in 67% of years post-publication; and (3) the Guerard and Takano stock selection model is not the result of data mining.
Journal Article
Shortfall Risk and Shortfall Duration for Portfolio Choice in Decumulation
The article studies the portfolio selection problem in the retirement phase by using the habit formation utility function in the context of traditional utility maximization. The habit formation utility can be further simplified to a linear combination of shortfall risk and shortfall duration. A retiree who can easily adapt to a new spending level should emphasize shortfall duration whereas a retiree who is rigid in spending should emphasize shortfall risk. The article provides the conditions in which current practitioners favorite choices of shortfall risk, as a criterion to choose retirement portfolios, are consistent with utility maximization. TOPICS: Retirement, wealth management, long-term/retirement investing
Journal Article
Warning: SRI Need Not Kill Your Sharpe and Information Ratios—Forecasting of Earnings and Efficient SRI and ESG Portfolios
Using an earnings forecasting model is useful and produces statistically significant outperformance in US stock selection. This study finds that the incorporation of environmental, social, and governance (ESG) criteria can potentially enhance stockholder returns, holding risk constant under reasonable assumptions. The novel approach here uses a normalization of ESG strengths and weaknesses ratings, applied in both robust simply weighted and realistic optimized portfolio settings. The study confirms a now-classical no-cost result for the overall ESG criteria and—with human rights and corporate governance criteria—shows that SRI and ESG information can enhance portfolio returns in certain implementations. Thus, SRI and ESG investors may not necessarily have to expect lower portfolio returns and Sharpe ratios under all circumstances. TOPICS: ESG investing, portfolio theory, portfolio construction, performance measurement Key Findings • ESG measures can be used in conjunction with a statistically significant earnings forecasting efficiency tilt so that portfolio standard deviation and tracking errors decrease. • Decreased portfolio standard deviation and tracking error increase portfolio Sharpe and information ratios. Return-to-risk ratios rise with KLD SRI and ESG variables. • The incorporation of KLD human rights factors, including those related to indigenous peoples, and the inclusion of overall KLD concerns increase Sharpe ratios and information ratios. No longer are researchers merely concerned with asking, “Is there a cost to being socially responsible in investing?” across the board.
Journal Article