remove hit rate/profit factor

Author: rbeeli

src/analytics.jl

@@ -1,7 +1,7 @@
 import DataFrames: DataFrame
 import RiskPerf
 
-@inline function _clean_returns(returns::AbstractVector)
+@inline function _clean_returns(returns)
     out = Float64[]
     sizehint!(out, length(returns))
     @inbounds for r in returns
@@ -13,45 +13,17 @@ import RiskPerf
     out
 end
 
-@inline function _hit_rate(returns::AbstractVector{<:Real})
-    wins = 0
-    losses = 0
-    @inbounds for r in returns
-        if r > 0
-            wins += 1
-        elseif r < 0
-            losses += 1
-        end
-    end
-    total = wins + losses
-    total == 0 ? NaN : wins / total
-end
-
-@inline function _profit_factor(returns::AbstractVector{<:Real})
-    gains = 0.0
-    losses = 0.0
-    @inbounds for r in returns
-        if r > 0
-            gains += r
-        elseif r < 0
-            losses += -r
-        end
-    end
-    losses == 0.0 && return gains == 0.0 ? NaN : Inf
-    gains / losses
-end
-
 """
-    performance_summary_table(returns::AbstractVector; periods_per_year=252, risk_free=0.0, mar=0.0, compound=true)
+    performance_summary_table(returns; periods_per_year=252, risk_free=0.0, mar=0.0, compound=true)
 
 Return a one-row `DataFrame` with summary performance metrics:
-`CAGR`, `vol`, `Sharpe`, `Sortino`, `max DD`, `MAR`, `Calmar`, `hit rate`, and `profit factor`.
+`CAGR`, `vol`, `Sharpe`, `Sortino`, `max DD`, `MAR`, and `Calmar`.
 
 `returns` must be simple periodic returns. `risk_free` and `mar` are per-period inputs.
 `max_dd` is reported as a positive magnitude. `mar` is the minimum acceptable return used for Sortino.
 """
 function performance_summary_table(
-    returns::AbstractVector;
+    returns;
     periods_per_year::Real=252,
     risk_free=0.0,
     mar=0.0,
@@ -68,8 +40,6 @@ function performance_summary_table(
             max_dd=NaN,
             mar=mar,
             calmar=NaN,
-            hit_rate=NaN,
-            profit_factor=NaN,
         )
     end
 
@@ -79,8 +49,6 @@ function performance_summary_table(
     sortino = RiskPerf.sortino_ratio(r; multiplier=periods_per_year, MAR=mar)
     max_dd = RiskPerf.max_drawdown_pct(r; compound=compound)
     calmar = RiskPerf.calmar_ratio(r, periods_per_year; compound=compound)
-    hit_rate = _hit_rate(r)
-    profit_factor = _profit_factor(r)
 
     DataFrame(;
         cagr=cagr,
@@ -90,8 +58,6 @@ function performance_summary_table(
         max_dd=max_dd,
         mar=mar,
         calmar=calmar,
-        hit_rate=hit_rate,
-        profit_factor=profit_factor,
     )
 end
 
@@ -115,5 +81,6 @@ function performance_summary_table(
         periods_per_year=periods_per_year,
         risk_free=risk_free,
         mar=mar,
-        compound=compound)
+        compound=compound,
+    )
 end