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Finance and Credit
 

Investment risk assessment using the relative range of asset price fluctuations

Vol. 21, Iss. 29, AUGUST 2015

PDF  Article PDF Version

Received: 13 April 2015

Accepted: 28 April 2015

Available online: 27 August 2015

Subject Heading: Securities market

JEL Classification: 

Pages: 13-28

Rossokhin V.V. National Research University Higher School of Economics - Nizhny Novgorod, Nizhny Novgorod, Russian Federation
vrossohin@hse.ru

Chaprak N.V. National Research University Higher School of Economics - Nizhny Novgorod, Nizhny Novgorod, Russian Federation
nchaprak@hse.ru

Subject The concept of risk and return is a cornerstone of the modern theory of finance. This fact gives rise to developing the methods for risk assessment, building the models that link risk and return, and using them in applications. The concept is of utmost importance while investing in financial markets.
     Objectives The study aims at developing the investment risk assessment techniques on the basis of the indicator other than those employed at the current stage.
     Methods In the study, we simulated trading based on historical information on price behavior of different assets. Further, we analyzed the effectiveness of the intraday trading in the securities market, simultaneously with the assessment of the daily range, using statistical methods.
     Results The result of this research is the development of the indicator based on relative fluctuations of asset price. The indicator directly relates to the assessment of probability of losses as a result of investment activities, as well as the possibility of loss forecasting. We present recommendations for improving the profitability of investment using the specified techniques. The findings may be useful for assessing the likelihood of unfavorable periods in the investment process and for increasing the efficiency of marketplace trading in financial assets in organized markets.
     Conclusions The obtained result has applied relevance. It is necessary to further develop the risk assessment techniques based on the findings of the study.

Keywords: risk, risk assessment, investment, securities

References:

  1. Sharpe W.F., Aleksander G.J., Bailey J.V. Investitsii [Investments]. Moscow, INFRA-M Publ., 2001, 1028 p.
  2. Damodaran A. Investitsionnaya otsenka: instrumenty i metody otsenki lyubykh aktivov [Investment Valuation: Tools and Techniques for Determining the Value of Any Asset]. Moscow, Al'pina Pablisher Publ., 2007, 1340 p.
  3. Shapkin A.S., Shapkin V.A. Ekonomicheskie i finansovye riski. Otsenka, upravlenie, portfel' investitsii [Economic and financial risks. Assessment, management, investment portfolio]. Moscow, Dashkov i Ko Publ., 2009, 544 p.
  4. Drury C. Upravlencheskii uchet dlya biznes-reshenii [Management Accounting for Business]. Moscow, YUNITI-DANA Publ., 2012, 655 p.
  5. Lobanov A.A., Kainova E.I. Sravnitel'nyi analiz metodov rascheta VaR-limitov s uchetom model'nogo riska na primere rossiiskogo rynka aktsii [A comparative analysis of methods for VaR limit calculation based on model risk: the case of the Russian equity market]. Upravlenie finansovymi riskami = Financial Risk Management, 2005, no. 1, pp. 44–55.
  6. Mandelbrot B., Hudson R.L. (Ne)poslushnye rynki: fraktal'naya revolyutsiya v finansakh [The (Mis)Behaviour of Markets: A Fractal View of Risk, Ruin and Reward]. Moscow, Vil'yams Publ., 2006, 400 p.
  7. Entsiklopediya finansovogo risk-menedzhmenta [Encyclopedia of financial risk management]. Moscow, Al'pina Pablisher Publ., 2003, 786 p.
  8. Cont R. Empirical Properties of Asset Returns: Stylized Facts and Statistical Issues. Quantitative Finance, 2001, no. 1, pp. 223–236.
  9. Hull J.C. Optsiony, f'yuchersy drugie proizvodnye finansovye instrument [Options, Futures, and Other Derivatives]. Moscow, Vil'yams Publ., 2007, 1056 p.
  10. Engle R. Autoregressive Conditional Heteroscedasticity with Estimates of the Variance of United Kingdom Inflation. Econometrica, 1982, vol. 50, iss. 4, pp. 987–1008.
  11. Bollerslev T. Generalized Autoregressive Conditional Heteroskedasticity. Journal of Econometrics, 1986, no. 31, pp. 307–327.
  12. Figlewski S. Forecasting Volatility. Financial Markets, Institutions, and Instruments, 1997, vol. 6, iss. 1, pp. 1–88.
  13. Poon S-H., Granger C.W.J. Forecasting volatility in financial markets: a review. Journal of Economic Literature, 2003, no. 41, pp. 478–539.
  14. LeBeau Ch., Lucas D.W. Komp'yuternyi analiz f'yuchersnykh rynkov [Computer Analysis of the Futures Market]. Moscow, Al'pina Publ., 2006, 264 p.

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