diff --git a/README.md b/README.md
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--- a/README.md
+++ b/README.md
@@ -11,117 +11,230 @@ Since I took a long break from this and never published it a new package has eme
 
 ## Asset Price and Return Functions
 
-- `AssetPrice(ticker::String, from::TimeType, to::TimeType, freq::String; exchange_local_time=true)`
+- ```julia
+  AssetPrice(ticker::String, from::TimeType, to::TimeType, freq::String; exchange_local_time=true)
+  ```
   - Downloads prices using YFinance.jl
-- `AssetReturn(x::AssetPrice)`
-- `AssetReturn(ticker::String, from::TimeType, to::TimeType, freq::String)`
+- ```julia
+  AssetReturn(x::AssetPrice)
+  ```
+- ```julia
+  AssetReturn(ticker::String, from::TimeType, to::TimeType, freq::String)
+  ```
   - Downloads prices using YFinance.jl and converts them to returns
 
 ### Return Calculation Functions
-- `log_diff(x)`
-- `pct_change(x)`
-- `simple_diff(x)`
+- ```julia
+  log_diff(x)
+  ```
+- ```julia
+  pct_change(x)
+  ```
+- ```julia
+  simple_diff(x)
+  ```
 
 ## Statistical Measures
 
 ### Basic Measures
-- `mean_arith(x)`
-- `mean_geo(returns::Vector{Float64})`
-- `mean_geo_log(returns::Vector{Float64})`
-- `stdvp(x)`
-- `stdvs(x)`
-- `varp(x)`
-- `vars(x)`
+- ```julia
+  mean_arith(x)
+  ```
+- ```julia
+  mean_geo(returns::Vector{Float64})
+  ```
+- ```julia
+  mean_geo_log(returns::Vector{Float64})
+  ```
+- ```julia
+  stdvp(x)
+  ```
+- ```julia
+  stdvs(x)
+  ```
+- ```julia
+  varp(x)
+  ```
+- ```julia
+  vars(x)
+  ```
 
 ### Advanced Measures
-- `skew(R, method="simple")`
+- ```julia
+  skew(R, method="simple")
+  ```
   - Methods: Population, Sample, Fisher
-- `kurt(R, method="simple")`
+- ```julia
+  kurt(R, method="simple")
+  ```
   - Methods: population, excess, sample, sampleexcess, fisher
-- `covariance(Ra::AbstractArray{<:Number}, Rb::AbstractArray{<:Number}; corrected::Bool=false)`
+- ```julia
+  covariance(Ra::AbstractArray{<:Number}, Rb::AbstractArray{<:Number}; corrected::Bool=false)
+  ```
   - Methods:
     - Normal (corrected=false, default)
     - Corrected (corrected=true)
-- `coskew(Ra::AbstractArray{<:Number}, Rb::AbstractArray{<:Number})`
-- `cokurt(Ra::AbstractArray{<:Number}, Rb::AbstractArray{<:Number})`
-- `hurstindex(R::AbstractArray{<:Number})`
+- ```julia
+  coskew(Ra::AbstractArray{<:Number}, Rb::AbstractArray{<:Number})
+  ```
+- ```julia
+  cokurt(Ra::AbstractArray{<:Number}, Rb::AbstractArray{<:Number})
+  ```
+- ```julia
+  hurstindex(R::AbstractArray{<:Number})
+  ```
 
 ## Risk Measures
 
 ### Drawdown Measures
-- `drawdown(x::AbstractArray{<:Number})`
-- `drawdownpeak(x::AbstractArray{<:Number})`
-- `drawdown_table(x::AbstractArray{<:Number}, dates::AbstractArray{<:TimeType})`
-- `avgdrawdown(x::AbstractArray{<:Number})`
-- `maxdrawdown(x::AbstractArray{<:Number})`
+- ```julia
+  drawdown(x::AbstractArray{<:Number})
+  ```
+- ```julia
+  drawdownpeak(x::AbstractArray{<:Number})
+  ```
+- ```julia
+  drawdown_table(x::AbstractArray{<:Number}, dates::AbstractArray{<:TimeType})
+  ```
+- ```julia
+  avgdrawdown(x::AbstractArray{<:Number})
+  ```
+- ```julia
+  maxdrawdown(x::AbstractArray{<:Number})
+  ```
 
 ### Downside Risk Measures
-- `downsidedeviation(R::AbstractArray{<:Number}, MAR::Number = 0)`
-- `downsidepotential(R::AbstractArray{<:Number}, MAR::Number=0)`
-- `semideviation(R::AbstractArray{<:Number})`
-- `semivariance(R::AbstractArray{<:Number})`
+- ```julia
+  downsidedeviation(R::AbstractArray{<:Number}, MAR::Number = 0)
+  ```
+- ```julia
+  downsidepotential(R::AbstractArray{<:Number}, MAR::Number=0)
+  ```
+- ```julia
+  semideviation(R::AbstractArray{<:Number})
+  ```
+- ```julia
+  semivariance(R::AbstractArray{<:Number})
+  ```
 
 ### Value at Risk and Expected Shortfall
-- `valueatrisk(R::AbstractArray{<:Number}, p::Number, method::AbstractString="gaussian")`
+- ```julia
+  valueatrisk(R::AbstractArray{<:Number}, p::Number, method::AbstractString="gaussian")
+  ```
   - Methods: gaussian, historical, cornish_fisher
-- `expectedshortfall(R::AbstractArray{<:Number}, p::Number, method::AbstractString="gaussian")`
+- ```julia
+  expectedshortfall(R::AbstractArray{<:Number}, p::Number, method::AbstractString="gaussian")
+  ```
   - Methods: gaussian, historical, cornish_fisher
 
 ### Other Risk Measures
-- `painindex(R::AbstractArray{<:Number})`
+- ```julia
+  painindex(R::AbstractArray{<:Number})
+  ```
 
 ## Performance Measures
 
 ### Risk-Adjusted Return Measures
-- `sharperatio(R::Number, σ::Number, Rf::Number=0.; scale=1)`
-- `sharperatio(R::AbstractArray{<:Number}, Rf::Number=0.; scale)`
-- `adjustedsharpe(R::AbstractArray{<:Number}, Rf::Number=0.; method::AbstractString="population")`
-- `adjustedsharpe(R::Number, σ::Number, S::Number, K::Number, Rf::Number=0.)`
-- `treynorratio(Ra::AbstractArray{<:Number}, Rb::AbstractArray{<:Number}, Rf::Number=0; modified::Bool=false, scale=1)`
-- `informationratio(Ra::AbstractArray{<:Number}, Rb::AbstractArray{<:Number}, scale::Number=1)`
-- `appraisalratio(Ra::AbstractArray{<:Number}, Rb::AbstractArray{<:Number}, Rf::Number=0, method::AbstractString = "appraisal", scale::Number=1)`
+- ```julia
+  sharperatio(R::Number, σ::Number, Rf::Number=0.; scale=1)
+  ```
+- ```julia
+  sharperatio(R::AbstractArray{<:Number}, Rf::Number=0.; scale)
+  ```
+- ```julia
+  adjustedsharpe(R::AbstractArray{<:Number}, Rf::Number=0.; method::AbstractString="population")
+  ```
+- ```julia
+  adjustedsharpe(R::Number, σ::Number, S::Number, K::Number, Rf::Number=0.)
+  ```
+- ```julia
+  treynorratio(Ra::AbstractArray{<:Number}, Rb::AbstractArray{<:Number}, Rf::Number=0; modified::Bool=false, scale=1)
+  ```
+- ```julia
+  informationratio(Ra::AbstractArray{<:Number}, Rb::AbstractArray{<:Number}, scale::Number=1)
+  ```
+- ```julia
+  appraisalratio(Ra::AbstractArray{<:Number}, Rb::AbstractArray{<:Number}, Rf::Number=0, method::AbstractString = "appraisal", scale::Number=1)
+  ```
   - Methods: 
     - "appraisal" (default)
     - "modified"
     - "alternative"
 
 ### Drawdown-based Performance Measures
-- `calmarratio(R::AbstractArray{<:Number}, scale::Float64=1.)`
-- `burkeratio(R::AbstractArray{<:Number}; Rf::Float64 = 0., modified::Bool = false, scale::Number=1)`
-- `burkeratio(Ra::AbstractArray{<:Number}, Drawdowns::AbstractArray{<:Number}; Rf::Number=0., scale=1)`
+- ```julia
+  calmarratio(R::AbstractArray{<:Number}, scale::Float64=1.)
+  ```
+- ```julia
+  burkeratio(R::AbstractArray{<:Number}; Rf::Float64 = 0., modified::Bool = false, scale::Number=1)
+  ```
+- ```julia
+  burkeratio(Ra::AbstractArray{<:Number}, Drawdowns::AbstractArray{<:Number}; Rf::Number=0., scale=1)
+  ```
 
 ### Relative Performance Measures
-- `activepremium(Ra::Number, Rb::Number; scalea=1, scaleb=1)`
-- `jensensalpha(Y::AbstractArray{<:Number}, X::AbstractArray{<:Number}...; scale::Number=1)`
-- `trackingerror(Ra::AbstractArray{<:Number}, Rb::AbstractArray{<:Number}, scale::Number=1)`
+- ```julia
+  activepremium(Ra::Number, Rb::Number; scalea=1, scaleb=1)
+  ```
+- ```julia
+  jensensalpha(Y::AbstractArray{<:Number}, X::AbstractArray{<:Number}...; scale::Number=1)
+  ```
+- ```julia
+  trackingerror(Ra::AbstractArray{<:Number}, Rb::AbstractArray{<:Number}, scale::Number=1)
+  ```
 
 ### Other Performance Measures
-- `bernardoledoitratio(R::AbstractVector{<:Number})`
-- `kappa(R::AbstractArray{<:Number}, MAR::Number=0., k::Number=2)`
+- ```julia
+  bernardoledoitratio(R::AbstractVector{<:Number})
+  ```
+- ```julia
+  kappa(R::AbstractArray{<:Number}, MAR::Number=0., k::Number=2)
+  ```
   - Notable cases:
     - k=1: returns the Sharpe-Omega Ratio
     - k=2: returns the Sortino Ratio
 
 ## Factor Analysis Functions
 
-- `factor_alpha(Y::AbstractArray{<:Number}, X::AbstractArray{<:Number}...)`
-- `factor_loadings(Y::AbstractArray{<:Number}, X::AbstractArray{<:Number}...; intercept::Bool=true)`
-- `factor_regression(Y::AbstractArray{<:Number}, X::AbstractArray{<:Number}...; intercept::Bool=true)`
-- `factor_resid(Y::AbstractArray{<:Number}, X::AbstractArray{<:Number}...; intercept::Bool=true)`
+- ```julia
+  factor_alpha(Y::AbstractArray{<:Number}, X::AbstractArray{<:Number}...)
+  ```
+- ```julia
+  factor_loadings(Y::AbstractArray{<:Number}, X::AbstractArray{<:Number}...; intercept::Bool=true)
+  ```
+- ```julia
+  factor_regression(Y::AbstractArray{<:Number}, X::AbstractArray{<:Number}...; intercept::Bool=true)
+  ```
+- ```julia
+  factor_resid(Y::AbstractArray{<:Number}, X::AbstractArray{<:Number}...; intercept::Bool=true)
+  ```
 
 ## Risk Decomposition
 
-- `specificrisk(Ra::AbstractArray{<:Number}, Rb::AbstractArray{<:Number}, Rf::Number=0)`
-- `systematicrisk(Ra::AbstractArray{<:Number}, Rb::AbstractArray{<:Number}, Rf::Number=0)`
-- `totalrisk(Ra::AbstractArray{<:Number}, Rb::AbstractArray{<:Number}, Rf::Number=0)`
+- ```julia
+  specificrisk(Ra::AbstractArray{<:Number}, Rb::AbstractArray{<:Number}, Rf::Number=0)
+  ```
+- ```julia
+  systematicrisk(Ra::AbstractArray{<:Number}, Rb::AbstractArray{<:Number}, Rf::Number=0)
+  ```
+- ```julia
+  totalrisk(Ra::AbstractArray{<:Number}, Rb::AbstractArray{<:Number}, Rf::Number=0)
+  ```
 
 ## Utility Functions
 
-- `roll_apply(data::AbstractVector{<:Number}...; fun::Function, window::Int, retain_length::Bool=false, fill_with = NaN, always_return::Bool=false)`
-- `to_annual_return(R::AssetReturn)`
-- `to_monthly_return(R::AssetReturn)`
-- `annualize(R::Number, scale::Float64=252)`
-
+- ```julia
+  roll_apply(data::AbstractVector{<:Number}...; fun::Function, window::Int, retain_length::Bool=false, fill_with = NaN, always_return::Bool=false)
+  ```
+- ```julia
+  to_annual_return(R::AssetReturn)
+  ```
+- ```julia
+  to_monthly_return(R::AssetReturn)
+  ```
+- ```julia
+  annualize(R::Number, scale::Float64=252)
+  ```
 
 A list of all functions and their definitions can be found in the documentation.