diff --git a/README.md b/README.md
index c8e31d1..96d277a 100644
--- a/README.md
+++ b/README.md
@@ -23,3 +23,6 @@ might add a makefile to automize this later.
 unzip -n 20Spring_martingale.zip
 ```
 
+[Here](https://pythonprogramming.net/candlestick-ohlc-graph-matplotlib-tutorial/)
+is a tutorial for how to plot candlestick data. Will come in handy later.
+
diff --git a/martingale/figure_1.png b/martingale/figure_1.png
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diff --git a/martingale/figure_3.png b/martingale/figure_3.png
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diff --git a/martingale/martingale.md b/martingale/martingale.md
new file mode 100644
index 0000000..fdaca71
--- /dev/null
+++ b/martingale/martingale.md
@@ -0,0 +1,7 @@
+# Report 
+
+![](figure_1.png)
+![](figure_2.png)
+![](figure_3.png)
+![](figure_4.png)
+![](figure_5.png)
diff --git a/martingale/martingale.py b/martingale/martingale.py
index cbcf53a..4c73ed7 100644
--- a/martingale/martingale.py
+++ b/martingale/martingale.py
@@ -26,6 +26,7 @@ GT ID: 900897987 (replace with your GT ID)
 """
 
 import numpy as np
+import matplotlib.pyplot as plt
 
 def author():
     return 'tb34' # replace tb34 with your Georgia Tech username.
@@ -39,27 +40,95 @@ def get_spin_result(win_prob):
         result = True
     return result
 
-def test_code():
+def run_experiment(max_winnings=80, max_bets=1000, initial_credit=0):
     win_prob = 18 / 38 # 18 black numbers out of 38 total numbers
+    current_bet, episode_winnings, bet_amount = 0, 0, 1
+    winnings = np.zeros(max_bets)
+
+    # Keep making bets until we reach desired winnings or betting limit
+    while episode_winnings < max_winnings and current_bet < max_bets:
+        if get_spin_result(win_prob):
+            episode_winnings += bet_amount
+            bet_amount = 1
+        else:
+            episode_winnings -= bet_amount
+            bet_amount *= 2
+        winnings[current_bet] = episode_winnings
+        current_bet += 1
+
+        # Handle experiment 2 where we have a initial maximum bankroll
+        if initial_credit > 0:
+            current_credit = initial_credit + episode_winnings
+            if current_credit <= 0:
+                break
+            if bet_amount > current_credit:
+                bet_amount = current_credit
+
+    # Fill remaining fields with last value
+    while current_bet < max_bets:
+        winnings[current_bet] = episode_winnings
+        current_bet += 1
+
+    return winnings
+
+def configure_plot():
+    plt.figure()
+    axes = plt.gca()
+    axes.set_xlim([0, 300])
+    axes.set_ylim([-256, 100])
+    plt.xlabel("#bets []")
+    plt.ylabel("win [$]")
+
+def experiment_1_figure_1(number_runs=10):
+    configure_plot()
+    for _ in range(number_runs):
+        winnings = run_experiment()
+        plt.plot(winnings)
+    plt.savefig('figure_1.png')
+
+def experiment_1_figure_2(number_runs=1000):
+    configure_plot()
+    runs = np.array([run_experiment() for _ in range(number_runs)])
+    winnings_mean = runs.mean(axis=0)
+    winnings_std = winnings_mean.std()
+
+    plt.plot(winnings_mean, linewidth=0.7)
+    plt_std_setting = {'ls': '-', 'color': 'blue', 'linewidth': 0.3}
+    plt.plot(winnings_mean + winnings_std, **plt_std_setting)
+    plt.plot(winnings_mean - winnings_std, **plt_std_setting)
+    plt.savefig('figure_2.png')
+
+    experiment_1_figure_3(runs)
+
+def experiment_1_figure_3(runs, figurename='figure_3.png'):
+    configure_plot()
+    winnings_median = np.median(a=runs, axis=0)
+    winnings_std = winnings_median.std()
+    plt.plot(winnings_median, linewidth=0.7)
+    plt_std_setting = {'ls': '-', 'color': 'blue', 'linewidth': 0.3}
+    plt.plot(winnings_median + winnings_std, **plt_std_setting)
+    plt.plot(winnings_median - winnings_std, **plt_std_setting)
+    plt.savefig(figurename)
+
+def experiment_2_figure_4(number_runs=1000):
+    configure_plot()
+    runs = np.array([run_experiment(initial_credit=256)
+                    for _ in range(number_runs)])
+    winnings_mean = runs.mean(axis=0)
+    winnings_std = winnings_mean.std()
+    plt.plot(winnings_mean, linewidth=0.7)
+    plt_std_setting = {'ls': '-', 'color': 'blue', 'linewidth': 0.3}
+    plt.plot(winnings_mean + winnings_std, **plt_std_setting)
+    plt.plot(winnings_mean - winnings_std, **plt_std_setting)
+    plt.savefig('figure_4.png')
+    experiment_1_figure_3(runs, figurename='figure_5.png')
+
+def test_code():
     np.random.seed(gtid()) # do this only once
-
-    episode_winnings = 0
-    winnings = [0]
-    while episode_winnings < 80:
-        won = False
-        bet_amount = 1
-        while not won:
-            won = get_spin_result(win_prob)
-            if won:
-                episode_winnings += bet_amount
-            else:
-                episode_winnings -= bet_amount
-                bet_amount *= 2
-            winnings.append(episode_winnings)
-
-    print(winnings)
-
-    # add your code here to implement the experiments
+    experiment_1_figure_1()
+    experiment_1_figure_2()
+    experiment_2_figure_4()
 
 if __name__ == "__main__":
     test_code()
+