Marketsim - Revision history

Tucker: /* What to turn in */

2018-10-16T20:49:37Z

What to turn in

2018-10-16T20:48:13Z

Updates & FAQs

2018-08-30T03:44:32Z

2018-05-03T18:22:14Z

Required, Allowed & Prohibited

2018-03-08T16:40:28Z

Orders files to run your code on

2018-03-08T16:33:00Z

Updates & FAQs

2018-03-08T16:32:13Z

Updates & FAQs

2018-03-05T23:04:51Z

Template

2018-03-05T22:08:50Z

Removed draft notice

2018-03-05T18:35:42Z

orders2.csv

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 Be sure to follow these instructions diligently!
-Via T-Square, submit as attachment (no zip files; refer to schedule for deadline):
+Via Canvas, submit as attachment (no zip files; refer to schedule for deadline):
 * Your code as <tt>marketsim.py</tt> (only the function <tt>compute_portvals()</tt> will be tested)

@@ Line 31: / Line 31: @@
 Instructions:
-* Download the appropriate zip file [[File:marketsim.zip]]
+* Download the appropriate zip file [[File:18fall_marketsim.zip]]
 * Implement the <tt>compute_portvals()</tt> function in the file <tt>marketsim/marketsim.py</tt>.
 * The grading script is <tt>marketsim/grade_marketsim.py</tt>. For more details see here: [[ML4T_Software_Setup#Running_the_grading_scripts]]

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 * Unladen African swallows.
 * You may use the NumPy, SciPy, matplotlib and Pandas libraries.  Be sure you are using the correct versions.
 * Code provided by the instructor, or allowed by the instructor to be shared.
 * To read in orders files pandas.read_csv() is allowed.
@@ Line 300: / Line 299: @@
 * Reading in data by any means other than the functions in util.py or pandas.read_csv()
 * Any libraries or modules not listed in the "allowed" section above.
-* Any code you did not write yourself (except for the 5 line rule in the "allowed" section).
+* Any code you did not write yourself.
 * Code that takes longer than 10 seconds to run.
 * Any Classes (other than Random) that create their own instance variables for later use (e.g., learners like kdtree).

@@ Line 126: / Line 126: @@
 Example orders files are available in the orders subdirectory.
-Here are some additional test cases: [[Media:Testcases_mc2p1.zip|testcases_mc2p1.zip]]
+Here are some additional test cases:
 ==Short example to check your code==

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 * Q: How can I be sure that my function is returning a DataFrame? Q: Check the type of the returned item foo with <tt>type(foo)</tt>
-* Q: Do we have to reject the order if the stock is not trading on that day?  A: You should fill orders for any day the market is open.  Suggested operation: Drop days when the market is not open (check by looking at SPY), fill forward, then fill back.
+* Q: Do we have to reject the order if the stock is not trading on that day?  A: You should fill orders for any day the market is open, and reject orders for any day the market is closed. Suggested operation: Drop days when the market is not open (check by looking at SPY), fill forward, then fill back.
 * Q: Is it true that the orders might not be in order in the csv? A: Yes.

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 ==Updates & FAQs==
 FAQs:
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 * Q: How can I be sure that my function is returning a DataFrame? Q: Check the type of the returned item foo with <tt>type(foo)</tt>
-* Q: Do we have to reject the order if the stock is not trading on that day?  A: Yes, but you should fill the data forward and back first, which should eliminate this possibility.
+* Q: Do we have to reject the order if the stock is not trading on that day?  A: You should fill orders for any day the market is open.  Suggested operation: Drop days when the market is not open (check by looking at SPY), fill forward, then fill back.
 * Q: Is it true that the orders might not be in order in the csv? A: Yes.

← Older revision		Revision as of 22:08, 5 March 2018
Line 1:		Line 1:
−	~~==Draft==~~
−
−	~~This project is in draft mode. When it is finalized, this notice will be removed.~~
−
	==Updates & FAQs==		==Updates & FAQs==

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 <pre>
-Data Range: 2011-01-10 to 2011-12-20
+Data Range: 2011-01-14 00:00:00 to 2011-12-14 00:00:00
 Sharpe Ratio of Fund: 0.552604907987
-Sharpe Ratio of $SPX: 0.0183389807443
+Sharpe Ratio of $SPX: -0.177203019906
 Cumulative Return of Fund: 0.0538411196951
-Cumulative Return of $SPX: -0.0224059854302
+Cumulative Return of $SPX: -0.0629581516192
 Standard Deviation of Fund: 0.00728172910323
-Standard Deviation of $SPX: 0.0149716091522
+Standard Deviation of $SPX: 0.0150564855724
 Average Daily Return of Fund: 0.000253483085898
-Average Daily Return of $SPX: 1.7295909534e-05
+Average Daily Return of $SPX: -0.000168071648902
 Final Portfolio Value: 1051088.0915