diff --git a/fincal/statistics.py b/fincal/statistics.py
index 16b642c..f4bc59f 100644
--- a/fincal/statistics.py
+++ b/fincal/statistics.py
@@ -1,15 +1,44 @@
+import datetime
+from typing import Literal
+
+from fincal.core import date_parser
+
 from .fincal import TimeSeries
 
 
+@date_parser(3, 4)
 def sharpe_ratio(
-    time_series_data: TimeSeries, risk_free_data: TimeSeries = None, risk_free_rate: float = None, **kwargs
+    time_series_data: TimeSeries,
+    risk_free_data: TimeSeries = None,
+    risk_free_rate: float = None,
+    from_date: str | datetime.datetime = None,
+    to_date: str | datetime.datetime = None,
+    frequency: Literal["D", "W", "M", "Q", "H", "Y"] = None,
+    return_period_unit: Literal["years", "months", "days"] = "years",
+    return_period_value: int = 1,
+    as_on_match: str = "closest",
+    prior_match: str = "closest",
+    closest: Literal["previous", "next"] = "previous",
+    date_format: str = None,
 ):
     pass
 
     if risk_free_data is None and risk_free_rate is None:
         raise ValueError("At least one of risk_free_data or risk_free rate is required")
 
-    returns_ts = time_series_data.calculate_rolling_returns(**kwargs)
+    common_params = {
+        "from_date": from_date,
+        "to_date": to_date,
+        "frequency": frequency,
+        "annual_compounded_returns": True,
+        "return_period_unit": return_period_unit,
+        "return_period_value": return_period_value,
+        "as_on_match": as_on_match,
+        "prior_match": prior_match,
+        "closest": closest,
+        "date_format": date_format,
+    }
+    returns_ts = time_series_data.calculate_rolling_returns(**common_params)
 
     if risk_free_data is not None:
         risk_free_data = returns_ts.sync(risk_free_data)
@@ -17,6 +46,10 @@ def sharpe_ratio(
         risk_free_data = risk_free_rate
 
     excess_returns = returns_ts - risk_free_data
-    sd = time_series_data.volatility(**kwargs)
+    sd = time_series_data.volatility(
+        **common_params,
+        annualize_volatility=True,
+    )
+
     sharpe_ratio = excess_returns.mean() / sd
     return sharpe_ratio