3 edition of Stock return nonlinearities found in the catalog.
Stock return nonlinearities
Blake Dean LeBaron
Written in English
|Statement||by Blake Dean LeBaron.|
|LC Classifications||Microfilm 88/2074 (H)|
|The Physical Object|
|Pagination||vi, 71 leaves.|
|Number of Pages||71|
|LC Control Number||88890974|
Nonlinearities in the volume-volatility relationship are tested using short sales information so that it is possible to identify the activity of short sellers on a daily basis to predict share price returns. One of the clues that led them down this path was a common finding in the literature on stock market volatility that negative shocks cause. Modeling and analysis for stock return movements along with exchange rates and interest rates in Markov regime-switching models 29 December | Cluster Computing, Vol. 22, No. S1 An Extension of Markowitz' Modern Portfolio Theory for Long-Term Equity InvestorsCited by:
Conference on the cross section of returns. like size and book/market ratio. The expected return and covariance of an individual stock seems to vary a lot over time. So we need to build ER(characteristics) and then see if it lines up with covariance(R, factors | characteristics), where factors are also portfolios formed on the basis of. Composition of Wealth, Conditioning Information, and the Cross-Section of Stock Returns Abstract Value stocks covary with aggregate consumption more than growth stocks during periods when financial wealth is low relative to consumption. However, the conditional value premium does not exhibit such countercyclical by:
Frank M., Stengos T. () Nearest Neighbor Forecasts of Precious Metal Rates of Return. In: Gori F., Geronazzo L., Galeotti M. (eds) Nonlinear Dynamics in Economics and Social Sciences. Lecture Notes in Economics and Mathematical Systems, vol Cited by: 2. the book-to-market ratio, and a measure for the volatility of each bank’s stock return. All specifications include country and year fixed effects, are estimated using weighted least squares, and their standard errors are clustered by country and event.
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PDF | Our prior research indicates that there are periods within which nonlinear stock selection models outperform their linear counterparts in the | Find, read and cite all the research you. Nonlinearities In Stock Return Prediction: Evidence From South Africa Article (PDF Available) in Journal of Applied Business Research 28(6) October with 50 Reads.
Downloadable. Numerous empirical studies have shown evidence of nonlinearities in financial time series, which can be of both a deterministic and a stochastic nature. Chaos is an example of the former, and heteroscedasticity in the conditional variance an example of the latter.
We apply a test, the BDS test, to Swedish Stock Index returns and detect large deviations from the IID-hypothesis. Since the return and hazard Stock return nonlinearities book fashions use the variance as a key variable for hazard, and since the typical common model disregards the nonlinearities present in stock markets, the author has improved the match of the volatility in the German equity market using nonlinear ARCH fashions.
If you're looking for a free download. portfolio return in month 1 is per cent ($/$ 1). While this month-1 portfolio return is identical to the return calculated above by averaging the returns on each stock, this is where the similarities end.
At the end of month 2, the portfolio is worth $, so the portfolio return is per cent ($/$ 1).Cited by: () surveys 50 earnings-based return predictive signals, McLean and Pontiff () docum and Harvey et al. () and Green et al. () both extend the list to around These variables range from classic accounting-based variables, such as book-to-market, to return-based variables, such as the stock return over the previous by: Corrections.
All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:eee:jfinec:vyipSee general information about how to correct material Stock return nonlinearities book RePEc.
For technical questions regarding this item, or to correct its authors, title. Sustainability11, 4 of 15 equity return dispersion (RDt) for day t as the cross-sectional standard deviation of daily stock returns calculated as: RD t= v u u tw i, N å i=1 (r rm,t) 2, (1) where ri,t and rm,t are the return for stock i and the market for day t, respectively; wi,t = 1/N for the equally-weighted cross-sectional dispersion of equity returns; and N is the number of by: 2.
Expected return, time-varying risk, and hedging demand in the US REITs market 1 May | Journal of Management Analytics, Vol.
1, No. 1 A comparative examination of currency risk pricing and market integration in the stock markets of Nigeria and South AfricaCited by: Get this from a library.
Alternative Models For Conditional Stock Volatility. [G William Schwert; Adrian R Pagan; National Bureau of Economic Research.;] -- This paper compares several statistical models for monthly stock return volatility.
The focus is on U.S. data from because the post data have been analyzed in more detail by others. The overall result is that the book loses coherence, and it is difﬁcult to predict where to ﬁnd any particular topic. For example, one might expect to ﬁnd the discussion of ARCH models of stock returns in one of the chapters on stock return predictability.
Instead, it is found just prior to kernel regression in the chapter on nonlinearities. Book-to-market is calculated in December of year t as Australia has a June end of financial year, thereby effectively achieving a similar time ‘buffer’ to that of the counterpart US studies.
3 Our proxy for liquidity, the share turnover variable for each stock, is computed as the average of the monthly trading volume divided by the number Cited by: The utility from investing in this portfolio is: (8) U t r t = E t w t r t + r t, f − 1 2 γ v a r t (w t r t + r t, f), where w t is the weight of stock in this portfolio, r t is the stock return in excess of risk-free rate, and γ denotes the risk aversion by: FIRM CHARACTERISTICS, CROSS-SECTIONAL REGRESSION ESTIMATES, AND INTERTEMPORAL ASSET PRICING TESTS the rejections are driven in part by the presence of nonlinearities in the data.
Keywords: stochastic discount factor, size e ect, book-to-market ratio, gross because an excess stock return is also the payo to a self- nancing strategy. CAPITAL EXPENDITURES AND FIRM PERFORMANCE: EVIDENCE FROM A CROSS-SECTIONAL ANALYSIS OF STOCK RETURNS the expected stock return for a rm depends on its net investment its book-to-market ratio, a return-based measure of momentum, and the gross pro tability of the rm relative to its total assets.
A speci cation that includes all of these. This book is required reading, for academics and practitioners alike. --Francis X. Diebold, J.M. Cohen Professor of Economics, University of Pennsylvania "Calvet and Fisher have fashioned the definitive treatment of multi-fractal models of return by: Investment Dynamics and Earnings-Return Properties: A Structural Approach Matthias Breuer* stock (through this period’s investment) to maximize the present value of future cash flows.
These real options introduce notable nonlinearities in the predicted earnings and return patterns. The estimated coefficient on the cross-product term is statistically significant and negative, as theory suggests in the presence of important nonlinearities. Further, there is increased nonlinearity in the data subsequent to IFRS adoption, with the increase being most Cited by: Technical Stock Valuation of a Company: The Bangladesh Perspective Imam Abu Sayeed, PhD1 Md.
Waheduzzaman Sarder Md. Shamim Mondal Alok Roy Abstract The paper describes the relationship between risk and expected return and determination of risk free rate in valuation of a stock.
stage for the rest of the book and for the research contributions of the authors. The remainder of the book is mainly focused on testing for parameter stability of various models, examining nonlinearities in the data, and the role that volatility plays in bond and stock markets.
The authors do a good job of challenging the standard. The stock market can display varying characteristics for various stock.
So it is necessary to develop model for predicting daily stock return of NIFTY. The data for the analysis comprises the daily stock returns of NIFTY, Exchange Rate Rupee/US Dollar, FII Purchase, FII Sales (on a .Abstract: This study uses the Bayesian approach to examine the incremental contribution of stock characteristics to the investment opportunity set in U.K.
stock returns. The paper ﬁnds that size, book-to-market (BM) ratio, and momentum characteristics all make a signiﬁcant incrementalCited by: 2.On average, stock price movements during earning days generate about 8 business days worth of non-earning day return variance.
We use the Earnings day Variance Ratio (EDR), the ratio of earnings day stock return squared to the return variance of the previous month, to capture the time-series and cross-sectional variation of fundamentals.