Stock Market Predictability And Industrial Metal Returns
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| Author | : Ben Jacobsen |
| Publisher | : |
| Total Pages | : 50 |
| Release | : 2016 |
| Genre | : |
| ISBN | : |
Price movements in industrial metals such as copper and aluminum predict stock returns. Increasing industrial metal prices are good news for equity markets in recessions and bad news in expansions. A one standard deviation increase in industrial metal returns predicts a price drop of one and a half percent in monthly stock market returns in expansions and an increase of around a half percent during recessions. The predictability is distinct to and compares favorably with that from more established predictors, with monthly out-of-sample R2's of 3% to 8%.
| Author | : Ben Jacobsen |
| Publisher | : |
| Total Pages | : 73 |
| Release | : 2009 |
| Genre | : |
| ISBN | : |
Monthly stock market returns are predictable when we refine the observation intervals of the variables used to predict these returns. Contrary to other predictability studies we find high out-of-sample adjusted R2s of up to 7% using economically important commodity returns. Shorter intervals reveal predictability consistent with near efficient markets based on price changes in industrial metals. More historical intervals expose predictability consistent with gradual information diffusion based on energy series. This predictability is robust to data mining adjustment, the inclusion of control (including economic) variables, and unrelated to time-varying risk. Inflation explains part of this predictability, but not all.
| Author | : Walter N. Torous |
| Publisher | : |
| Total Pages | : 42 |
| Release | : 2009 |
| Genre | : |
| ISBN | : |
We test the hypothesis that the gradual diffusion of information across asset markets leads to cross-asset return predictability. Using thirty-four industry portfolios and the broad market index as our test assets, we establish several key results. A number of industries such as retail, services, commercial real estate, metal, and petroleum lead the stock market by up to two months. Importantly, an industry's ability to lead the market is correlated with its propensity to forecast various indicators of economic activity such as industrial production growth. Consistent with our hypothesis, these findings indicate that the market reacts with a delay to information in industry returns about its fundamentals because information diffuses only gradually across asset markets.
| Author | : Zhong-guo Zhou |
| Publisher | : |
| Total Pages | : 252 |
| Release | : 1993 |
| Genre | : Capital assets pricing model |
| ISBN | : |
| Author | : Radek Silhavy |
| Publisher | : Springer Nature |
| Total Pages | : 550 |
| Release | : |
| Genre | : |
| ISBN | : 3031548205 |
| Author | : Rohit Tayal |
| Publisher | : |
| Total Pages | : 120 |
| Release | : 2006 |
| Genre | : Metal trade |
| ISBN | : |
The metals and mining sector is driving the world economy like never before. Concentration of industry at a particular level of the global value chain decides how an economy will be affected by rising metal prices seen recently. Stock markets are bound to reflect the broader effect on an economy. This leads to the question-are stock markets and metal markets correlated, and can metal markets be used to predict stock markets? Taking the LME as a proxy for metal markets and the S&P 500 as a representative stock market, stock market returns are regressed onto notional returns on metal markets and convenience yields in metal prices. Metal markets are only found to be able to predict the Metals and Mining sub-index of the S&P 500 very weakly. Overall, no conclusions may be drawn pending more rigorous testing and/or use of other explanatory variables, possibly across markets and commodities.
| Author | : David G McMillan |
| Publisher | : Springer |
| Total Pages | : 141 |
| Release | : 2017-11-30 |
| Genre | : Business & Economics |
| ISBN | : 3319690086 |
This book provides a comprehensive analysis of asset price movement. It examines different aspects of stock return predictability, the interaction between stock return and dividend growth predictability, the relationship between stocks and bonds, and the resulting implications for asset price movement. By contributing to our understanding of the factors that cause price movement, this book will be of benefit to researchers, practitioners and policy makers alike.
| Author | : M. Hashem Pesaran |
| Publisher | : |
| Total Pages | : |
| Release | : 1998 |
| Genre | : |
| ISBN | : |
This paper examines the robustness of the evidence on predictability of US stock returns, and addresses the issue of whether this predictability could have been historically exploited by investors to earn profits in excess of a buy-and-hold strategy in the market index. We find that the predictive power of various economic factors over stock returns changes through time and tends to vary with the volatility of returns. The degree to which stock returns were predictable seemed quite low during the relatively calm markets in the 1960's, but increased to a level where, net of transaction costs, it could have been exploited by investors in the volatile markets of the 1970's.
| Author | : Gökhan Silahtaroğlu |
| Publisher | : Springer Nature |
| Total Pages | : 183 |
| Release | : 2021-05-29 |
| Genre | : Business & Economics |
| ISBN | : 3030741761 |
This book considers and assesses essential financial issues by utilizing data science and fuzzy multiple criteria decision making (MCDM) methods. It introduces readers to a range of data science methods, and demonstrates their application in the fields of business, health, economics, finance and engineering. In addition, it provides suggestions based on the assessment results on each topic, which can help to enhance the efficiency of the financial system and the sustainability of economic development. Given its scope, the book will help readers broaden their perspective on the assessment and evaluation of financial issues using data science and MCDM approaches.
| Author | : Andrew Urquhart |
| Publisher | : |
| Total Pages | : 28 |
| Release | : 2016 |
| Genre | : |
| ISBN | : |
This paper provides strong evidence of time-varying return predictability of three precious metals from January 1987 to September 2014. We use three variations of the variance ratio test, the nonlinear BDS test as well as the Hurst exponent to evaluate the time-varying return predictability of precious metals to reduce the risk of spurious results. We show that even when the full sample period indicates no significant predictability, each market goes through periods of significant predictability as well as periods of unpredictability, according to all of the testing procedures used in this study. Our findings suggest that return predictability in precious metals does vary over time and that market efficiency is not an all-or-nothing condition, which is consistent with the Adaptive Market Hypothesis. We also show that platinum is the most predictable of the three precious metals and silver the least predictable, which may be of great to investors who include precious metals in their investment portfolios.
