diff --git a/marketsim/marketsim.py b/marketsim/marketsim.py
index 98387a6..50d2c41 100644
--- a/marketsim/marketsim.py
+++ b/marketsim/marketsim.py
@@ -26,10 +26,6 @@ GT ID: 1337 (replace with your GT ID)
 """
 
 import pandas as pd
-import numpy as np
-import datetime as dt
-import os
-import sys
 from util import get_data, plot_data
 from optimize_something.optimization import calculate_stats
 
@@ -76,25 +72,26 @@ def get_portfolio_value(holding, prices):
     return value
 
 
-def handle_orders(orders, holding, adj_closing_prices):
-    """Process the orders."""
-    for date, order in orders.iterrows():
-        symbol, order, shares = order
-        adj_closing_price = adj_closing_prices[symbol]
-        cost = shares * adj_closing_price
-        if order == "BUY":
-            # print(f"Buy  {shares:6} of {symbol:4} on {date}")
-            holding['cash'] -= cost
-            holding[symbol] += shares
-        elif order == "SELL":
-            # print(f"Sell {shares:6} of {symbol:4} on {date}")
-            holding['cash'] += cost
-            holding[symbol] -= shares
-        else:
-            raise Exception("Unexpected order type.")
+def handle_order(date, order, holding, prices, commission, impact):
+    """Process the order."""
+    symbol, order, shares = order
+    adj_closing_price = prices[symbol]
+    cost = shares * adj_closing_price
+    # Charge commission and deduct impact penalty
+    holding['cash'] -= (commission + impact * adj_closing_price * shares)
+    if order == "BUY":
+        # print(f"Buy  {shares:6} of {symbol:4} on {date}")
+        holding['cash'] -= cost
+        holding[symbol] += shares
+    elif order == "SELL":
+        # print(f"Sell {shares:6} of {symbol:4} on {date}")
+        holding['cash'] += cost
+        holding[symbol] -= shares
+    else:
+        raise Exception("Unexpected order type.")
 
 
-def compute_portvals(orders_file="./orders/orders-01.csv", start_val=1000000, commission=9.95, impact=0.005):
+def compute_portvals(orders_file, start_val=1000000, commission=9.95, impact=0.005):
     orders = read_orders(orders_file)
     start_date, end_date, symbols = get_order_book_info(orders)
 
@@ -106,22 +103,17 @@ def compute_portvals(orders_file="./orders/orders-01.csv", start_val=1000000, co
     holding = {s: 0 for s in symbols}
     holding['cash'] = start_val
 
-    orders_processed = 0
+    # Iterate over all trading days that are in the (inclusive) range of the
+    # order book dates. This implicitly ignores orders placed on non-trading
+    # days.
     for date, values in prices.iterrows():
-        if date in orders.index:
-            current_orders = orders.loc[date:date]
-            orders_processed += current_orders.shape[0]
-            handle_orders(current_orders, holding, values)
-
+        # Process orders for that day.
+        for date, order in orders.loc[date:date].iterrows():
+            handle_order(date, order, holding, values, commission, impact)
         # Compute portfolio value at the end of day.
         values['Portval'] = get_portfolio_value(holding, values)
 
-    # Make sure we have processed all orders. If there was an order on a
-    # non-trading day we would currently not handle it.
-    assert(orders.shape[0] == orders_processed)
-
-    portvals = prices[['Portval']]
-    return portvals
+    return prices[['Portval']]
 
 
 def test_code():
@@ -129,6 +121,7 @@ def test_code():
     sv = 1000000
 
     portvals = compute_portvals(orders_file=of, start_val=sv)
+
     if isinstance(portvals, pd.DataFrame):
         portvals = portvals[portvals.columns[0]]  # just get the first column
     else:
@@ -161,5 +154,9 @@ def test_code():
     print(f"Final Portfolio Value: {portvals[-1]}")
 
 
+def author():
+    return 'felixm'
+
+
 if __name__ == "__main__":
     test_code()
diff --git a/marketsim/orders/orders-short.csv b/marketsim/orders/orders-short.csv
new file mode 100644
index 0000000..0785a65
--- /dev/null
+++ b/marketsim/orders/orders-short.csv
@@ -0,0 +1,3 @@
+Date,Symbol,Order,Shares
+2011-01-05,AAPL,BUY,1500
+2011-01-20,AAPL,SELL,1500