Download presentation
Presentation is loading. Please wait.
Published byJonathan Green Modified over 6 years ago
1
Learning About Return and Risk from the Historical Record
Chapter 5
6
It is on the class web page, handouts, chapter 5.
Study: A new historical database for the NYSE to 1925: Performance and predictability The previous figure came from a study: “A new historical database for the NYSE 1815 to 1925: Performance and predictability.” It is on the class web page, handouts, chapter 5.
8
Real vs. Nominal Rates How much was a donut in 1970? How much is a donut now? Nominal interest rate (R): Growth rate of your money Real interest rate (r): Growth rate of your purchasing power Fisher effect: Approximation nominal rate = real rate + inflation premium R = r + i or r = R - i Example r = 3%, i = 6% R = 9% = 3% + 6% or 3% = 9% - 6% Fisher effect: Exact r = (R - i) / (1 + i) = ( ) / (1+.06) Empirical Relationship: Inflation and interest rates move closely together
10
Fig. 5.3 Interest and inflation rates
11
Fig 5.2 Nominal and real TW for t-bills
12
Table 5.2 T-Bill Rates, Inflation Rates, and Real Rates, 1926-2012
13
Rates of Return (for any asset): Single Period
HPR = Holding Period Return P0 = Beginning price P1 = Ending price D1 = Dividend during period one
14
Rates of Return: Single Period Example
Ending Price = 48 Beginning Price = 40 Dividend = 2 HPR = ( )/ (40) = 25%
15
Return for Holding Period – Zero Coupon Bonds
Zero coupon Treasury Bond: Par = $100 Price as a function of maturity T= P(T) Total risk free return =
16
Annualized Rates of Return
17
Formulas for equivalent annual rates (EAR) and annual percentage rate (APR)
19
Characteristics of Probability Distributions
1) Mean: most likely value 2) Variance or standard deviation 3) Higher moments: Skewness and kurtosis. Skewness – The degree of asymmetry of a distribution. Kurtosis –The degree of peakedness of a distribution. Stock returns are sometimes said to be “leptokurtotic” that is, peaked in the center with fat tails. * If a distribution is approximately normal, the distribution is described by characteristics 1 and 2.
21
Normality and Risk Measures
What if excess returns are not normally distributed? Standard deviation is no longer a complete measure of risk Sharpe ratio is not a complete measure of portfolio performance Need to consider skewness and kurtosis
26
Recent total large-cap, total market, and small cap performance
Let’s add a little “spice”: VTSMX, IJS
29
vix
30
The Reward-to-Volatility (Sharpe) Ratio
Excess Return The difference in any particular period between the actual rate of return on a risky asset and the actual risk-free rate Risk Premium The difference between the expected HPR on a risky asset and the risk-free rate Sharpe Ratio =
31
Normality and Risk Measures
Value at Risk (VaR) Loss corresponding to a very low percentile of the entire return distribution, such as the fifth or first percentile return VaR normal – 5% point of a normal distribution = mean minus 1.65 s.d. VaR actual – 5% point of a distribution Expected Shortfall (ES) Also called conditional tail expectation (CTE), focuses on the expected loss in the worst-case scenario (left tail of the distribution) More conservative measure of downside risk than VaR
32
Normality and Risk Measures
Lower Partial Standard Deviation (LPSD) and the Sortino Ratio Similar to usual standard deviation, but uses only negative deviations from the risk-free return, thus, addressing the asymmetry in returns issue Sortino Ratio: The ratio of average excess returns to LPSD
34
Mean Scenario or Subjective Returns
p(s) = probability of a state r(s) = return if a state occurs 1 to s states
35
Scenario or Subjective Returns: Example
State Prob. of State r in State E(r) = (.1)(-.05) + (.2)(.05)...+ (.1)(.35) E(r) = .15
37
Variance or Dispersion of Returns
Subjective or Scenario Standard deviation = [variance]1/2 Using Our Example: Var =[(.1)( )2+(.2)( ) ( )2] Var= S.D.= [ ] 1/2 = .1095
38
Mean and Variance of Historical Returns
Arithmetic average Variance
39
Geometric Average Returns
TV = Terminal Value of the Investment (sometimes called “terminal wealth”) g= geometric average rate of return
42
Figure 5.7 Nominal and Real Equity Returns Around the World, 1900-2000
47
Portfolio risk Previous slide return data from Ken French:
You can minimize risks by holding a combination of the assets. It’s all about the three “C’s”…
Similar presentations
© 2025 SlidePlayer.com. Inc.
All rights reserved.