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Non-Linear Predictability of Stock Market Returns

Non-Linear Predictability of Stock Market Returns
Author: Andreas Humpe
Publisher:
Total Pages: 13
Release: 2015
Genre:
ISBN:

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Using smooth transition regression model analysis, we examine the non-linear predictability of Japanese and US stock market returns by a set of macroeconomic variables between 1981 and 2012. The theoretical basis for investigating non-linear behavior in stock returns can be based on the interaction between noise traders and arbitrageurs or behavioral finance theories of non-linear risk aversion. As heterogeneity in investors' beliefs gives reason to suspect a smooth transition between extremes, rather than abrupt, a smooth transition regression model is estimated. Our findings support differences in non-linearity of stock returns in Japan and the US that might be linked to different shareownership of the Japanese stock market compared to the US. In addition, differences in the legal system might have some influence over our findings as well. The US results also suggest greater heterogeneity in the relationship between stock returns and macro variables in the US data relative to the Japanese data. The reasons behind the differences in our results, both between countries and between regimes are probably due to the different economic conditions faced by Japan and the US over our sample, to the possible existence of bubbles in the data and to investor behavior consistent with 'behavioral finance' theories of investor behaviour.


Stock Market Crashes: Predictable And Unpredictable And What To Do About Them

Stock Market Crashes: Predictable And Unpredictable And What To Do About Them
Author: William T Ziemba
Publisher: World Scientific
Total Pages: 309
Release: 2017-08-30
Genre: Business & Economics
ISBN: 9813223863

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'Overall, the book provides an interesting and useful synthesis of the authors’ research on the predictions of stock market crashes. The book can be recommended to anyone interested in the Bond Stock Earnings Yield Differential model, and similar methods to predict crashes.'Quantitative FinanceThis book presents studies of stock market crashes big and small that occur from bubbles bursting or other reasons. By a bubble we mean that prices are rising just because they are rising and that prices exceed fundamental values. A bubble can be a large rise in prices followed by a steep fall. The focus is on determining if a bubble actually exists, on models to predict stock market declines in bubble-like markets and exit strategies from these bubble-like markets. We list historical great bubbles of various markets over hundreds of years.We present four models that have been successful in predicting large stock market declines of ten percent plus that average about minus twenty-five percent. The bond stock earnings yield difference model was based on the 1987 US crash where the S&P 500 futures fell 29% in one day. The model is based on earnings yields relative to interest rates. When interest rates become too high relative to earnings, there almost always is a decline in four to twelve months. The initial out of sample test was on the Japanese stock market from 1948-88. There all twelve danger signals produced correct decline signals. But there were eight other ten percent plus declines that occurred for other reasons. Then the model called the 1990 Japan huge -56% decline. We show various later applications of the model to US stock declines such as in 2000 and 2007 and to the Chinese stock market. We also compare the model with high price earnings decline predictions over a sixty year period in the US. We show that over twenty year periods that have high returns they all start with low price earnings ratios and end with high ratios. High price earnings models have predictive value and the BSEYD models predict even better. Other large decline prediction models are call option prices exceeding put prices, Warren Buffett's value of the stock market to the value of the economy adjusted using BSEYD ideas and the value of Sotheby's stock. Investors expect more declines than actually occur. We present research on the positive effects of FOMC meetings and small cap dominance with Democratic Presidents. Marty Zweig was a wall street legend while he was alive. We discuss his methods for stock market predictability using momentum and FED actions. These helped him become the leading analyst and we show that his ideas still give useful predictions in 2016-2017. We study small declines in the five to fifteen percent range that are either not expected or are expected but when is not clear. For these we present methods to deal with these situations.The last four January-February 2016, Brexit, Trump and French elections are analzyed using simple volatility-S&P 500 graphs. Another very important issue is can you exit bubble-like markets at favorable prices. We use a stopping rule model that gives very good exit results. This is applied successfully to Apple computer stock in 2012, the Nasdaq 100 in 2000, the Japanese stock and golf course membership prices, the US stock market in 1929 and 1987 and other markets. We also show how to incorporate predictive models into stochastic investment models.


Market Underreaction and Predictability in the Cross-Section of Japanese Stock Returns

Market Underreaction and Predictability in the Cross-Section of Japanese Stock Returns
Author: Pascal Nguyen
Publisher:
Total Pages: 30
Release: 2003
Genre:
ISBN:

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In this paper, I analyze the relationship between financial statements information and stock returns for firms listed on the Tokyo Stock Exchange. Firm-specific information is captured by way of score indicative of the firm's cash flow generating potential. The results show that score-based portfolio strategies can produce significant abnormal returns over a 10-year sample period. The excess return of high-score portfolios does not appear to result from a higher exposure to risk factors. The predictability of cross-section returns does not derive either from price momentum. I find that large stocks offer little profits to score-based portfolio strategies. Most of the abnormal returns are concentrated on small firms. The evidence is strongly supportive of a market underreaction to the financial information released by smaller lightly researched firms.


...And Nothing Else Matters? On the Dimensionality and Predictability of International Stock Returns

...And Nothing Else Matters? On the Dimensionality and Predictability of International Stock Returns
Author: Heiko Jacobs
Publisher:
Total Pages: 44
Release: 2018
Genre:
ISBN:

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We explore the dimensionality of stock returns in North America, Europe, Japan, Pacific, and Emerging Markets on the basis of 240 cross-sectional predictors. Our approach allows us to identify those predictors that are most consistently related to nonmicro-cap stock returns (i.e., independent of other predictors, adjusted for data mining, existent in different time periods, and across regions). There is a large geographic heterogeneity in the significance of individual characteristics and in time trends, which leads to substantial out-of-sample diversification gains for global multidimensional hedge portfolios. Our results are most consistent with the mispricing hypothesis for anomalies.


Stock Return Predictability

Stock Return Predictability
Author: Geert Bekaert
Publisher:
Total Pages: 53
Release: 2011
Genre:
ISBN:

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We ask whether stock returns in France, Germany, the UK and the US are predictable by three instruments: the dividend yield, the earnings yield and the short rate. The predictability regression is suggested by a present value model with earnings growth, payout ratios and the short rate as state variables. We use this model imposing a constant risk premium to examine the finite sample evidence on predictability. Not only do we find the short rate to be a relevant state variable theoretically, it is also the only robust short-run predictor of equity returns. The evidence in Lamont (1998) on earnings and dividend yield predictability is not robust to our increased sample period, does not survive finite sample corrections and does not extend to other countries. We find no evidence of long-horizon predictability once we account for finite sample influence. Finally, cross-country predictability appears stronger than predictability using local instruments.