Asset Pricing

Asset Pricing
Author: John H. Cochrane
Publisher: Princeton University Press
Total Pages: 560
Release: 2009-04-11
Genre: Business & Economics
ISBN: 1400829135

Winner of the prestigious Paul A. Samuelson Award for scholarly writing on lifelong financial security, John Cochrane's Asset Pricing now appears in a revised edition that unifies and brings the science of asset pricing up to date for advanced students and professionals. Cochrane traces the pricing of all assets back to a single idea--price equals expected discounted payoff--that captures the macro-economic risks underlying each security's value. By using a single, stochastic discount factor rather than a separate set of tricks for each asset class, Cochrane builds a unified account of modern asset pricing. He presents applications to stocks, bonds, and options. Each model--consumption based, CAPM, multifactor, term structure, and option pricing--is derived as a different specification of the discounted factor. The discount factor framework also leads to a state-space geometry for mean-variance frontiers and asset pricing models. It puts payoffs in different states of nature on the axes rather than mean and variance of return, leading to a new and conveniently linear geometrical representation of asset pricing ideas. Cochrane approaches empirical work with the Generalized Method of Moments, which studies sample average prices and discounted payoffs to determine whether price does equal expected discounted payoff. He translates between the discount factor, GMM, and state-space language and the beta, mean-variance, and regression language common in empirical work and earlier theory. The book also includes a review of recent empirical work on return predictability, value and other puzzles in the cross section, and equity premium puzzles and their resolution. Written to be a summary for academics and professionals as well as a textbook, this book condenses and advances recent scholarship in financial economics.

Chinese Stock Markets: A Research Handbook

Chinese Stock Markets: A Research Handbook
Author: Dongwei Su
Publisher: World Scientific
Total Pages: 454
Release: 2003-01-07
Genre: Business & Economics
ISBN: 9814491799

The exponential growth of China's stock markets in the past decade has attracted global attention from academics and practitioners. The practitioner's interest in Chinese markets stems from corporations; investors and financial institutions foresee substantial benefits from investing in China in the long run. However, the academic literature on the development of securities markets and reform of state enterprises in China is still in its infancy and fragmented. This handbook aims to bridge that gap by presenting a wide spectrum of research in the forefront of financial applications. It integrates theory and practice with state-of-the-art statistical techniques and provides numerous insights into the main challenges confronting Chinese markets in the new millennium.

Do Industries Lead the Stock Market? Gradual Diffusion of Information and Cross-Asset Return Predictability

Do Industries Lead the Stock Market? Gradual Diffusion of Information and Cross-Asset Return Predictability
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.

Stock Return Predictability

Stock Return Predictability
Author: Arthur Ritter
Publisher: GRIN Verlag
Total Pages: 21
Release: 2015-05-27
Genre: Business & Economics
ISBN: 3656968926

Research Paper (postgraduate) from the year 2015 in the subject Business economics - Banking, Stock Exchanges, Insurance, Accounting, grade: 17 (1,3), University of St Andrews (School of Management), course: Investment and Portfolio Management, language: English, abstract: Empirical evidence of stock return predictability obtained by financial ratios or macroeconomic factors has received substantial attention and remains a controversial topic to date. This is no surprise given that the existence of return predictability is not only of interest to practitioners but also introduces severe implications for financial models of risk and return. Founded on the assumption of efficient capital markets, research on capital asset pricing models has instigated this emergence of stock return predictability factors. Analysing these factors categorically, this paper will provide a balanced discussion of advocates as well as sceptics of stock return predictability. This essay will commence by firstly outlining the fundamental assumptions of an efficient capital market and its implications for return predictability. Subsequently, a thorough focus will be placed on the most significant predictability factors, including fundamental financial ratios and macroeconomic indicators as well as the validity of sampling methods used to attain return forecasts. Lastly this essay will reflect on the findings while proposing areas of further research.

Stock Market Predictability and Industrial Metal Returns

Stock Market Predictability and Industrial Metal Returns
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%.