New evidence for the inflation hedging potential of US stock returns

AbstractThis paper theoretically and empirically investigates how debt structure and strategic interaction among shareholders and debt holders in the event of default affect expected stock returns. The model predicts that expected stock returns are higher for firms that face high debt renegotiation difficulties and that have a large fraction of secured or convertible debt. Using a large sample of publicly traded U.S. firms for the period 1985–2012, the paper presents new evidence on the link between debt structure and stock returns that is supportive of the model’s predictions.

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Asset pricing with a reference level of consumption: New evidence from the cross-section of stock returns

Review of Financial Economics ◽

10.1016/j.rfe.2009.04.004 ◽

2009 ◽

Vol 18 (3) ◽

pp. 113-123 ◽

Cited By ~ 1

Author(s):

Joachim Grammig ◽

Andreas Schrimpf

Keyword(s):

Asset Pricing ◽

Stock Returns ◽

Cross Section ◽

Reference Level ◽

The Cross ◽

New Evidence

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Semi-monthly effect in stock returns: new evidence from Bombay Stock Exchange

Investment Management and Financial Innovations ◽

10.21511/imfi.14(3-1).2017.01 ◽

2017 ◽

Vol 14 (3) ◽

pp. 160-172 ◽

Cited By ~ 2

Author(s):

Shakila B. ◽

Prakash Pinto ◽

Iqbal Thonse Hawaldar

Keyword(s):

Health Care ◽

Stock Returns ◽

Stock Exchange ◽

Consumer Durables ◽

Empirical Results ◽

Significant Difference ◽

The Mean ◽

Daily Stock Returns ◽

New Evidence ◽

Care Index

Semi-monthly effect is a kind of calendar anomalies which is less explored in the financial literature. The main objective of this paper to investigate the presence of semi-monthly effect in selected sectoral indices of Bombay Stock Exchange (BSE). The study uses the daily stock returns of five sectoral indices viz S&amp;P BSE Auto Index, S&amp;P BSE Bankex, S&amp;P BSE Consumer Durables Index, S&amp;P BSE FMCG Index and S&amp;P BSE Health Care Index for the period of 10 years starting from 1st April 2007 to 31st March 2017. The data were analyzed using two approaches namely calendar days approach and trading days approach. To test the equality of mean returns for the two halves of the month, Mann-Whitney U test is used. The empirical results of the study did not provide any evidence for the presence of semi-monthly effect in the selected sectoral indices. Nevertheless, BSE Auto Index showed significant difference in the mean returns of first half and second half of trading month during the study period.

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Inflation Hedging and Industry Stock Returns

The BRC Academy Journal of Business ◽

10.15239/j.brcacadjb.2017.07.01.ja01 ◽

2017 ◽

Vol 7 (1) ◽

pp. 1-22

Author(s):

Tai David Yi

Keyword(s):

Stock Returns ◽

Inflation Hedging

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MARGIN-TRADING ACTIVITIES AND FUTURE STOCK RETURNS: NEW EVIDENCE FROM NONLINEAR ANALYSIS

Fractals ◽

10.1142/s0218348x20501261 ◽

2020 ◽

Vol 28 (06) ◽

pp. 2050126

Author(s):

QINGSONG RUAN ◽

JIARUI ZHANG ◽

YAPING ZHOU ◽

DAYONG LV

Keyword(s):

Stock Returns ◽

Cross Correlation ◽

Predictive Power ◽

Granger Causality Test ◽

Return Predictability ◽

Positive Information ◽

Causality Test ◽

Cross Correlation Analysis ◽

Trading Activities ◽

New Evidence

Using multifractal detrended cross-correlation analysis (MF-DCCA) and nonlinear Granger causality test, this paper examines the return predictability of margin-trading activities. Results show that the predictive power of margin-trading activities on subsequent stock returns varies with respect to the different aspects of margin trading. In line with previous studies, we find no significant correlation between margin-buying amount and subsequent stock returns. However, the margin-covering amount is negatively associated with subsequent stock returns; and margin debt is positively associated with the future stock returns. In general, our findings suggest that margin traders may have no positive information when they conduct a margin-buying position, but may possess negative information when covering their positions.

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New Evidence on the Role of Size Effect in Determining the Pricing of Risk, Volatility Dynamics, and Economic Exposure of Firm Returns

International Journal of Applied Behavioral Economics ◽

10.4018/ijabe.2020070101 ◽

2020 ◽

Vol 9 (3) ◽

pp. 1-25

Author(s):

Faisal Khan ◽

Sharif Ullah Jan

Keyword(s):

Size Effect ◽

Stock Returns ◽

Firm Size ◽

Research Study ◽

Leverage Effect ◽

Conditional Heteroskedasticity ◽

Economic Factors ◽

Monthly Data ◽

New Evidence

This research study analyses the role of size effect in detecting the pricing of risk, various volatility dynamics, and economic exposure of firm returns on the Pakistani stock market by employing monthly data for the period from 1998 to 2018. Three generalized autoregressive conditional heteroskedasticity models were applied: GARCH(1,1) for capturing different volatility dynamics, GARCH-M for pricing of risk, and EGARCH for asymmetric and leverage effect. The findings of the study are as follows: Firstly, the authors untie that pricing of risk is subject to considerable variations with respect to firm size. Secondly, in the process of detecting whether the firm size matters in the case of asymmetry and leverage effect, they find that it is indeed the case. Thirdly, size effect plays a substantial role in determining various volatility dynamics. Finally, they uncover that economic factors affect stock returns differently based on firm size, signifying the role of size effect.

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