Skip to main content
SpringerLink
Log in
Book cover

Equity Markets in India pp 145–160Cite as

Volatility in Stock Returns

  • Chapter
  • First Online:

  • 348 Accesses

Part of the book series: India Studies in Business and Economics ((ISBE))

Abstract

Although volatility in returns on equity stocks/shares is inherent, the presence of excessive volatility may not be preferred by a large number of equity investors (in particular, genuine long-term investors).

This is a preview of subscription content, log in via an institution.

Chapter
USD   29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD   84.99
Price excludes VAT (USA)
  • Available as EPUB and PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD   109.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info
Hardcover Book
USD   109.99
Price excludes VAT (USA)
  • Durable hardcover edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Learn about institutional subscriptions

References

  • Alagidede P (2011) Return behavior in Africa’s emerging equity markets. Q Rev Econ Financ 51(2):133–140

    Article  Google Scholar 

  • Barberis N, Shleifer A (2003) Style investing. J Financ Econ 68(2):161–199

    Article  Google Scholar 

  • Belter K, Engsted T, Tanggaard C (2005) A new daily dividend-adjusted index for the danish stock market, 1985–2002: construction, statistical properties, and return predictability. Res Int Bus Financ 19(1):53–70

    Article  Google Scholar 

  • Berger PG (2003) Discussion of ‘anomalous stock returns around internet firms earnings announcements’. J Acc Econ 34(3):273–281

    Article  Google Scholar 

  • Black F (1976) The pricing of commodity contracts. J Financ Econ 3(4):167–179

    Article  Google Scholar 

  • Campbell JY, Hentschel L (1992) No news is good news: an asymmetric model of changing volatility in stock returns. J Financ Econ 31(3):281–318

    Article  Google Scholar 

  • Chordia T, Roll R, Subrahmanyam A (2011) Recent trends in trading activity and market quality. J Financ Econ 101(2):243–263

    Article  Google Scholar 

  • Christie AA (1982) The stochastic behavior of common stock variances value, leverage and interest rate effects. J Financ Econ 10(4):407–432

    Article  Google Scholar 

  • Coutts JA (2010) Trading rules and stock returns: some further short run evidence from the Hang Seng 1997–2008. Appl Financ Econ 20(21):1667–1672

    Article  Google Scholar 

  • Coutts A, Cheung KC (2000) Trading rules and stock returns: some preliminary short run evidence from the Hang Seng 1985-1997. Appl Financ Econ 10:579–686

    Article  Google Scholar 

  • Dicle MF, Beyhan A, Yao LJ (2010) Market efficiency and international diversification. Int Rev Econ Financ 19(2):313–339

    Article  Google Scholar 

  • Ding Z, Granger CWJ, Engle RF (1993) A long memory property of stock market returns and a new model. J Empir Financ 1(1):83–106

    Article  Google Scholar 

  • Engle RF (1982) Autoregressive conditional heteroscedasticity with estimates of the variance of United Kingdom inflation. Econometrica 50(4):987–1007

    Article  Google Scholar 

  • Engle RF, Bollerslev T (1986) Modelling the persistence of conditional variances. Econometr Rev 5(1):1–50

    Article  Google Scholar 

  • Engle RF, Ng VK (1993) Measuring and testing the impact of news on volatility. NBER Working Paper Series No. 3681, pp 1–31

    Google Scholar 

  • Engle RF, Lilien D, Robins R (1987) Estimating time varying risk premia in the term structure: the ARCH-M model. Econometrica 55(2):391–407

    Article  Google Scholar 

  • Fama EF (1965) The behavior of stock market prices. J Bus 38(1):34–105

    Article  Google Scholar 

  • Francis J, Olsson P, Oswald D (2000) Comparing the accuracy and explainability of dividend, free cash flow, and abnormal earnings equity value estimates. J Acc Res 38(1):45–70

    Article  Google Scholar 

  • Frankel R, Lee CMC (1998) Accounting valuation, market expectation, and cross-sectional stock returns. J Acc Econ 25:283–320

    Article  Google Scholar 

  • Gahlot R, Datta SK (2011) Impact of future trading on efficiency and volatility of indian stock market: a case of CNX 100. J Trans Manag 16(1):43–57

    Google Scholar 

  • Glosten LR, Jagannathan R, Runkle D (1993) On the relation between the expected value and the volatility of the nominal excess return on stocks. J Financ 48(5):1779–1801

    Article  Google Scholar 

  • Golez B (2012) Expected returns and dividend growth rates implied by derivative markets. Rev Financ Stud 27(3):790–822

    Article  Google Scholar 

  • Gordon MJ (1959) Dividends, earnings and stock prices. Rev Econ Stat 41(2, Part 1):99–105

    Google Scholar 

  • Goyal A, Welch I (2003) Predicting the equity premium with dividend ratios. Manage Sci 49(5):639–654

    Article  Google Scholar 

  • Granger CWJ, Morgenstern O (1963) Spectral analysis of new york stock market prices. Kyklos 16(1):1–27

    Article  Google Scholar 

  • Handa P, Kothari SP, Wasley C (1989) The relation between the return intervals and betas: implications for the size effect. J Financ Econ 23(1):79–100

    Article  Google Scholar 

  • Jeyanthi BJ (2010) Weak-form market efficiency in india and its emerging asian counterparts. IUP J Public Financ 8(10):58–70

    Google Scholar 

  • Johnson TL, So EC (2012) The option to stock volume ratio and future returns. J Financ Econ 106(1):262–286

    Article  Google Scholar 

  • Kendall MG (1953) The analysis of economic time-series part I: prices. J Roy Stat Soc 116(1):11–34

    Article  Google Scholar 

  • Lai D, Bai A, Chang K, Wei H, Luo L (2012) Nonparametric analysis of the shenzhen stock market: the day of the week effect. Math Comput Model 55(3–4):1186–1192

    Google Scholar 

  • Liu L, Wang Y, Wan J (2010) Analysis of efficiency for Shenzhen stock market: evidence from the source of multifractality. Int Rev Financ Anal 19(4):237–241

    Article  Google Scholar 

  • Lynch AW, Mendenhall RR (1997) New evidence on stock price effects associated with changes in the S&P 500 index. J Bus 70(3):351–383

    Article  Google Scholar 

  • Maher D, Parikh A (2011) Short-term under/over-reaction, anticipation or uncertainty avoidance? evidence from India. J Int Financ Markets, Instit Money 21(4):560–584

    Article  Google Scholar 

  • Majumder D (2011) Asset pricing when market sentiments regulate asset-returns: evidences from emerging markets. J Quant Econ Indian Econometr Soc 9(1):89–117

    Google Scholar 

  • Majumder D (2012) When the market becomes inefficient: comparing BRIC markets with markets in the USA. Int Rev Financ Anal 24(C):84–92

    Google Scholar 

  • Mandelbrot B (1963) The variation of certain speculative prices. J Bus 36(4):394–419

    Article  Google Scholar 

  • Mishra RK, Sehgal S, Bhanumurthy NR (2011) A search for long-range dependence and chaotic structure in Indian stock market. Rev Financ Econ 20(2):96–104

    Article  Google Scholar 

  • National Stock Exchange (NSE) Website (2013). http://www.nseindia.com/products/content/equities/indices/cnx_500.htm). Accessed on 31 Dec 2013

  • Nelson DB (1991) Conditional heteroscedasticity in asset returns: a new approach. Econometrica 59(2):347–370

    Article  Google Scholar 

  • Parisi F, Vasquez A (2000) Simple technical trading rules of stock returns: evidence from 1987 to 1998 in Chile. Emerg Markets Rev 1(2):152–164

    Article  Google Scholar 

  • Praetz PD (1972) The distribution of share price changes. J Bus 45(1):49–55

    Article  Google Scholar 

  • Rabemananjara R, Zakoian JM (1993) Threshold ARCH models and asymmetries in volatility. J Appl Econometr 8(1):31–49

    Article  Google Scholar 

  • Roberts HV (1959) Stock-market “patterns” and financial analysis: methodological suggestions. J Financ 14(1):1–10

    Google Scholar 

  • Saatcioglu K, Starks L (1998) The stock price-volume relationship in emerging stock markets: the case of Latin America. Int J Forecast 14(2):215–225

    Article  Google Scholar 

  • Savor P (2012) Stock returns after major price shocks: the impact of information. J Financ Econ 106(3):635–659

    Article  Google Scholar 

  • Sharma JL, Kennedy RA (1977) A comparative analysis of stock price behavior on Bombay, London and New York Stock exchange. J Financ Quant Anal 31(3):391–413

    Article  Google Scholar 

  • Taylor J (1993) Discretion versus policy rules in practice. Carnegie-Rochester Conf Ser Public Policy 39:6195–6214

    Google Scholar 

  • Trueman B, Wong M, Zhang X (2003) Anomalous stock returns around internet firms’ earnings announcements. J Acc Econ 34(1–3):249–271

    Article  Google Scholar 

  • Wahal S, Yavuz D (2013) Style investing, co-movement, and return predictability. J Financ Econ 107(1):146–154

    Article  Google Scholar 

  • Wikipedia Website (2013). http://en.wikipedia.org/wiki/S%26P_CNX_500. Accessed on 31 Dec 2013

  • Xinga X, Howe JS (2003) The empirical relationship between risk and return: evidence from the U.K. stock market. Int Rev Financ Anal 12:329–346

    Article  Google Scholar 

  • Zakoian JM (1994) Threshold heteroscedastic models. J Econ Dyn Contr 18(5):931–955

    Article  Google Scholar 

Download references

Author information

Authors and Affiliations

  1. Department of Management Studies, Indian Institute of Technology Delhi, New Delhi, India

    Shveta Singh, P. K. Jain & Surendra Singh Yadav

Authors
  1. Shveta Singh
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. P. K. Jain
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Surendra Singh Yadav
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Shveta Singh .

Appendices

Annexure 7.1: Glossary of Terms

S. no.

Terms

Meaning

1

Heteroscedasticity

A collection of random variables is heteroscedastic if there are subpopulations that have different variabilities from others

2

Leptokurtosis

Leptokurtosis deals with distributions having fatter tails and narrower and higher ‘peakedness’ at the mean compared to a normal distribution

3

Leverage effect

The condition where the impact of negative shocks is much greater than the positive shocks in driving the departure from normality or vice versa

4

Mean-reverting

‘Mean-reverting’ behaviour of volatility suggests there is a normal level of volatility and deviations from that level are eventually cleared

5

Stationarity

The overall condition wherein the time series appears to have been drawn from a ‘stationary’ process, that is, a stochastic process where the joint probability distribution does not change when shifted in time and space

6

Volatility

A statistical measure of the dispersion of returns for a given security or a market index

7

Volatility clustering

The phrase ‘volatility clustering’ implies that periods of high (low) volatility are followed by periods of high (low) volatility, suggesting the presence of strong clustering of high and low fluctuations of the variable concerned

Annexure 7.2: Ljung-Box Q2 Statistics

Ljung-box statistics

Test statistic

p-value

Q, 12

209.02

0.000

Q, 24

248.64

0.000

Q, 36

260.42

0.000

Q, 48

296.31

0.000

Q, 72

332.09

0.000

Q, 96

352.51

0.000

Q, 120

382.83

0.000

Q, 144

433.08

0.000

Q, 168

483.08

0.000

Q, 192

483.08

0.000

Q, 200

500.59

0.000

Annexure 7.3: Lagrange Multiplier Test

Lagrange multiplier test

Test statistic

p-value

LM, 5

40.51826

0.000

LM, 10

23.10503

0.000

LM, 20

13.26816

0.000

LM, 30

9.091963

0.000

LM, 40

7.006252

0.000

LM, 50

5.976162

0.000

LM, 60

5.184236

0.000

LM, 70

4.73443

0.000

LM, 80

4.238505

0.000

LM, 90

3.867223

0.000

LM, 100

3.627176

0.000

Annexure 7.4: Stationarity Test Statistics

Tests

Statistic value

ADF test for 1 lag (intercept and trend)

−39.04482

Philips–Perron (PP) test (intercept and trend)

−47.04032

Kwiatkowski–Phillips–Schmidt–Shin (KPSS) test statistics

0.076364

Rights and permissions

Reprints and permissions

Copyright information

© 2016 Springer Science+Business Media Singapore

About this chapter

Cite this chapter

Singh, S., Jain, P.K., Yadav, S.S. (2016). Volatility in Stock Returns. In: Equity Markets in India. India Studies in Business and Economics. Springer, Singapore. https://doi.org/10.1007/978-981-10-0868-9_7

Download citation

Publish with us

Policies and ethics

Search

Navigation