Free lesson · Math & notation
Powers, square roots, exponentials and logarithms
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Start with the idea
Compounding repeats a growth factor. Roots and logarithms let you solve backwards from ending wealth to the growth rate or elapsed time.
Symbols, units & horizon
- V₀, V_T: initial and final positive wealth
- T: positive number of years in this example
- g: annual decimal compound growth
- a, b: positive numbers
- ln: natural logarithm, inverse of exp
- e: exponential base ≈2.71828
- Superscript: power, with 1/T meaning the T-th root
When and why to use this
Use roots for CAGR and logarithms for time-series returns, reversion half-life and implied carry rates.
A power repeats multiplication: 1.05² means 1.05×1.05. A square root reverses squaring for a nonnegative result. An exponential eˣ uses the constant e≈2.71828; the natural logarithm ln reverses that exponential.
Reverse a repeated growth factor
- Divide by V₀. Raise both sides to 1/T and subtract 1.
- Taking logs instead gives . The identity ln(ab)=ln a+ln b follows because .
100 growing to 121 over two years has g=√1.21−1=.1. Its log growth per year is ln1.1≈.09531.
The logarithm identity requires positive a and b. It explains why log returns add across time while wealth factors multiply. A calculator supplies logarithms, exponentials and roots; doing a derivation by hand means understanding the sequence of operations rather than memorising a decimal constant.
Python implementation
Self-contained teaching example. Python 3.10+; dependencies and input conventions are shown in the code and notation. Run in your own Python environment.
from math import exp, log
def compound(start, growth, years):
return start * (1 + growth)**years
def cagr(start, end, years):
if min(start, end, years) <= 0:
raise ValueError("Positive wealth and years required")
return exp(log(end / start) / years) - 1
print(compound(100, .1, 2), cagr(100, 121, 2))Continue learning
Math & Notation Essentials — all lessons- Start with numbers, variables and an equals sign
- Percentages, basis points and units
- Rearrange an equation without changing its meaning
- Powers, square roots, exponentials and logarithms
- Read sums, indices, averages and squared deviations
- Probability, expectation and conditioning
- Vectors, matrices and transpose notation
- Derivatives, integrals and approximations
Quantitative finance and development glossary · Python resources and libraries · Research sources and limitations