Skip to main content

An Analysis of Risk Treatment in the Field of Finance

  • Reference work entry
  • First Online:
Encyclopedia of Finance

Abstract

This paper studies the way to introduce risk into financial analysis. It suggests and analyzes metrics to improve the classic methods, like the Sharpe and Treynor ratios or the Net Present Value.

In particular, the paper suggests a linear penalization method developed by the authors, applying it to performance indexes and capital budgeting, and considering both total and systematic risk. The method shows obvious advantages in comparison with traditional methods.

JEL classification: G11; G31

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

Access this chapter

Chapter
USD 29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD 679.00
Price excludes VAT (USA)
  • Available as EPUB and PDF
  • Read on any device
  • Instant download
  • Own it forever
Hardcover Book
USD 849.99
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

Institutional subscriptions

Notes

  1. 1.

    Although some exceptions have also been pointed out.

  2. 2.

    It can be seen in Copeland et al. (2005), based on works like Arrow (1964) and Debreu (1959).

  3. 3.

    Markowitz (1952, 1959).

  4. 4.

    Although asset valuation models based on real options are also being increasingly applied for the last years, we are not entering here into their discussion.

  5. 5.

    The NPV is considered, in a classic reference in finance, as is Brealey et al. (2008), as the first one of the seven most important ideas in finance. In order to introduce risk into the NPV, the most widely applied systems are the risk-adjusted rate of return valuation formula and the certainty equivalent valuation formula (Copeland et al., 2005, pp. 156–157). We will use an alternative system, derived from the NPV: the Penalized Present Value (PPV).

  6. 6.

    Although both subjects have been and will be topic of discussion.

  7. 7.

    Expected value.

  8. 8.

    And we will explain later the meaning of the PIRR.

  9. 9.

    It might be argued that somebody could, by borrowing money at the risk-free rate, start from “B” and reach an investment that outperformed “A”, and this is true. However, small investors cannot get themselves into debt at the risk-free rate. Besides, the performance of an investment fund is known ex-post, and by then, it is impossible for any investor to leverage his or her investment.

  10. 10.

    As the market variance will be equal for all the portfolios.

  11. 11.

    The classification obtained is the same as with M2 for beta (Modigliani, 1997).

  12. 12.

    We will explain the PIRR for beta later.

  13. 13.

    Dispensing here with the j subindex.

  14. 14.

    For this reason we are employing the ≈ symbol.

  15. 15.

    This would allow to measure risk with β and the use of Treynor.

  16. 16.

    Out of the components of total risk, the diversifiable risk will disappear, and the market standard deviation is the same for every portfolio. Therefore, the only difference will be β.

  17. 17.

    It could also be reasoned in this way: the market Sharpe, which is the slope of the CML, shows the "price of risk", which is the increase in the expected return that is demanded for a risk increase. Consequently, it is logical to give such a value to t in the formula (60.5).

  18. 18.

    The use of indifference straight lines is a constraint of the system, which can be mitigated by the use of increasing t values as the risk grows. Sharpe also employs indifference straight lines, but instead of being parallels, they form a beam.

    In Figure 60.1, following the Sharpe ratio, all the portfolios located on the same straight line starting from r0 would be indifferent. For example, if we focus on the straight line linking r0 and Ra, and according to the Sharpe ratio, all the portfolios on this straight line are indifferent to Ra, because their Sharpe value is the same: the tangent of αa. At the same time, these portfolios would be worse than those located on the straight line linking r0 and Rb, because the latter ones have a higher Sharpe. This is the consequence of Sharpe using a system of indifference straight lines forming a beam.

    In the case of the PIRR system, indifference straight lines are drawn in parallel to the CML. The crossing point with the vertical axis is the PIRR, and its value is bigger the higher the straight line crosses with the vertical axis.

    If we applied increasing t values, as it was mentioned before, we would get closer to obtain indifference curves and we could reach to a solution quite similar to the standard one.

  19. 19.

    Discounted at the risk-free rate, as the risk penalization is applied afterwards.

  20. 20.

    Use of indifference straight lines, statistical meaning of t… Regarding t value, it should grow with the investment period as well as the market Sharpe tends to do so.

  21. 21.

    Here, as in some other occasions, we dispense with i subindex for NPV, not to make notation more complicated.

  22. 22.

    This is the Jensen α.

  23. 23.

    It can be adapted, for instance, from Copeland et al. (2005, p. 157).

References

  • Arrow, K.J., 1964, The role of securities in the optimal allocation of risk-bearing, Review of Economic Studies, April, 91–96.

    Google Scholar 

  • Benefield, J.D., R.I. Anderson and L.V. Zumpano, 2009, Performance differences in property-type diversified versus specialized real estate investment trusts (REITs), Review of Financial Economics, 18, 70–79.

    Article  Google Scholar 

  • Black, F., 1972, Capital market equilibrium with restricted borrowing, Journal of Business, July, 444–455.

    Google Scholar 

  • Brealey, R.A., S.C. Myers and F. Allen, 2008, Principles of corporate finance (McGraw-Hill, New York) 9th ed.

    Google Scholar 

  • Chu, P.K. and M. McKenzie, 2008, A study on stock-selection and market-timing performance: evidence from Hong Kong Mandatory Provident Funds (MPF), Review of Pacific Basin Financial Markets and Policies, 4, 617–649.

    Article  Google Scholar 

  • Chua, C.T. and W.T.H. Koh, 2007, Measuring investment skills of fund managers, Applied Financial Economics, 17, 1359–1368.

    Article  Google Scholar 

  • Collins, B. and F. Fabozzi, 2000, Equity manager selection and performance, Review of Quantitative Finance and Accounting, 15, 81–97.

    Article  Google Scholar 

  • Copeland, T.E., J.F. Weston and K. Shastri, 2005, Financial theory and corporate policy (Pearson Addison Wesley, Boston) 4th ed.

    Google Scholar 

  • Debreu, G., 1959, The theory of value (Wiley, New York).

    Google Scholar 

  • Fama, E.F. and K.R. French, 2010, Luck versus skill in the cross-section of mutual fund returns, Journal of Finance, 65, 1915–1947.

    Article  Google Scholar 

  • Ferruz, L., F. Gómez-Bezares and M. Vargas, 2009, Performance measures: advantages of linear risk penalization, Applied Financial Economics, 19, 73–85.

    Article  Google Scholar 

  • Ferruz, L., F. Gómez-Bezares and M. Vargas, 2010, Portfolio theory, CAPM and performance measures, in C.-F. Lee, A.C. Lee and J. Lee, eds., Handbook of quantitative finance and risk management (Springer, New York) 267–281.

    Chapter  Google Scholar 

  • Gómez-Bezares, F., 1993, Penalized present value: net present value penalization with normal and beta distributions, in R. Aggarwal, ed., Capital budgeting under uncertainty (Prentice-Hall, Englewood Cliffs, New Jersey) 91–102.

    Google Scholar 

  • Gómez-Bezares, F., J.A. Madariaga and J. Santibáñez, 2004, Performance ajustada al riesgo: índices clásicos y nuevas medidas, Análisis Financiero, 93, 6–16.

    Google Scholar 

  • Ho, L.-C., J. Cadle and M. Theobald, 2011, An analysis of risk-based asset allocation and portfolio insurance strategies, Review of Quantitative Finance and Accounting, 36, 247–267.

    Article  Google Scholar 

  • Hodges, C.W., W.R.L. Taylor and J.A. Yoder, 2003, Beta, the Treynor ratio, and long-run investment horizons, Applied Financial Economics, 13, 503–508.

    Article  Google Scholar 

  • In, F., S. Kim, V. Marisetty and R. Faff, 2008, Analysing the performance of managed funds using the wavelet multiscaling method, Review of Quantitative Finance and Accounting, 31, 55–70.

    Article  Google Scholar 

  • Jensen, M.C., 1968, The performance of mutual funds in the period 1945–1964, Journal of Finance, May, 389–416.

    Google Scholar 

  • Jensen, M.C., 1969, Risk, the pricing of capital assets, and the evaluation of investment portfolios, Journal of Business, April, 167–247.

    Google Scholar 

  • Lee, C.-F., K. Wang and Y.L. Chen, 2009, Hedging and optimal hedge ratios for international index futures markets, Review of Pacific Basin Financial Markets and Policies, 4, 593–610.

    Article  Google Scholar 

  • Lintner, J., 1965, The valuation of risk assets and the selection of risky investments in stock portfolios and capital budgets, Review of Economics and Statistics, February, 13–37.

    Google Scholar 

  • Lipton, A.F. and R.J. Kish, 2010, Robust performance measures for high yield bond funds, Quarterly Review of Economics and Finance, 50, 332–340.

    Article  Google Scholar 

  • Markowitz, H., 1952, Portfolio selection, Journal of Finance, March, 77–91.

    Google Scholar 

  • Markowitz, H., 1959, Portfolio selection: efficient diversification of investments (Wiley, New York).

    Google Scholar 

  • Mazumder, M.I., E.M. Miller and O.A. Varela, 2010, Market timing the trading of international mutual funds: weekend, weekday and serial correlation strategies, Journal of Business Finance and Accounting, 37, 979–1007.

    Article  Google Scholar 

  • Modigliani, L., 1997, Don’t pick your managers by their alphas, U.S. Investment Research, U.S. Strategy, Morgan Stanley Dean Witter, June.

    Google Scholar 

  • Modigliani, F. and L. Modigliani, 1997, Risk-adjusted performance, Journal of Portfolio Management, Winter, 45–54.

    Google Scholar 

  • Sainz, J., P. Grau and L.M. Doncel, 2006, Mutual fund performance and benchmark choice: the Spanish case, Applied Financial Economics Letters, 2, 317–321.

    Article  Google Scholar 

  • Sharpe, W.F., 1964, Capital asset prices: a theory of market equilibrium under conditions of risk, Journal of Finance, September, 425–442.

    Google Scholar 

  • Sharpe, W.F., 1966, Mutual fund performance, Journal of Business, January, 119–138.

    Google Scholar 

  • Treynor, J.L., 1965, How to rate management of investment funds, Harvard Business Review, January-February, 63–75.

    Google Scholar 

  • Yu, S.M. and K.H. Liow, 2009, Do retail firms benefit from real estate ownership?, Journal of Property Research, 26, 25–60.

    Article  Google Scholar 

Download references

Acknowledgements

We want to thank the editor, referees and other colleagues for their comments and suggestions, which have undoubtedly contributed to improve the present paper.

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Fernando R. Gómez-Bezares .

Editor information

Editors and Affiliations

Rights and permissions

Reprints and permissions

Copyright information

© 2013 Springer Science+Business Media New York

About this entry

Cite this entry

Gómez-Bezares, F., Gómez-Bezares, F.R. (2013). An Analysis of Risk Treatment in the Field of Finance. In: Lee, CF., Lee, A. (eds) Encyclopedia of Finance. Springer, Boston, MA. https://doi.org/10.1007/978-1-4614-5360-4_60

Download citation

  • DOI: https://doi.org/10.1007/978-1-4614-5360-4_60

  • Published:

  • Publisher Name: Springer, Boston, MA

  • Print ISBN: 978-1-4614-5359-8

  • Online ISBN: 978-1-4614-5360-4

  • eBook Packages: Business and Economics

Publish with us

Policies and ethics