get a stock historical value from google finance (Python)

2008-09-07T12:03:11-07:00

Python recipe 576495 by bussiere bussiere (finance, google, historical, value).

how to get a stock historical value from google finance

NPV / IRR / Payback Analysis (Python)

2013-09-06T23:04:55-07:00

Python recipe 576686 by Alia Khouri (finance). Revision 18.

A few financial functions for quick analysis of an investment opportunity and a series of associated cashflows.

As a module, it currently provides straightforward and easy to understand implementations of the Net Present Value (NPV), Internal Rate of Return (IRR), and Payback Period functions.

As a script, it provides a simple command line interface which integrates the above functions into a concise analysis of the investment opportunity.

    usage: invest discount_rate [cashflow0, cashflow1, ..., cashflowN]
        where 
            discount_rate is the rate used to discount future cashflows 
                             to their present values
            cashflow0 is the investment (always a negative value)
            cashflow1 .. cashflowN values can be positive (net inflows) 
                                                 or
                                                 negative (net outflows)

Here is an example of actual usage and output:

$ ./invest 0.05 -10000 6000 6000 6000
----------------------------------------------------------------------
year      0        1      2      3     
cashflow  -10,000  6,000  6,000  6,000 

Discount Rate: 5.0%

Payback: 1.67 years
    IRR: 36.31%
    NPV: 6339.49

==> Approve Investment of 10,000
----------------------------------------------------------------------

Note: A check of the output of the Microsoft Excel NPV function against that of the function implemented here reveals a curious discrepancy/bug in the way Excel calculates its NPV. For further details see: http://www.tvmcalcs.com/blog/comments/the_npv_function_doesnt_calculate_net_present_value/

Furthermore, the method used to calculate the IRR is rough to say the least and fails at fewer than 3 entries. Please use the secant method along the lines of the following haskell code from (http://www.haskell.org/haskellwiki/Haskell_Quiz/Internal_Rate_of_Return/Solution_Dolio) for greater accuracy.

secant :: (Double -> Double) -> Double -> Double
secant f delta = fst $ until err update (0,1)
  where
    update (x,y) = (x - (x - y) * f x / (f x - f y), x)
    err (x,y) = abs (x - y) < delta

npv :: Double -> [Double] -> Double
npv i = sum . zipWith (\t c -> c / (1 + i)**t) [0..]

irr :: [Double] -> Double
irr cashflows = secant (`npv` cashflows) (0.1**4)

Multidimensional Pareto front (Python)

2012-10-13T23:26:12-07:00

Python recipe 578287 by Jamie Bull (engineering, finance, optimal, pareto, pareto_front, pareto_frontier, pareto_set). Revision 2.

Method for finding non-dominated options in multi-dimensional data.

Brownian Motion of Stock (Python)

2009-05-19T05:16:29-07:00

Python recipe 576760 by alexander baker (finance).

Brownian Motion of a Stock

zero curve bootstrapping and forward curve generation (Python)

2012-09-10T08:07:56-07:00

Python recipe 578257 by alexander baker (finance, matplotlib, sympy).

example of a bootstrapping and forward curve generation this can be used to build a set of curves for different currencies

Yahoo Stock Information (Python)

2012-08-25T17:16:47-07:00

Python recipe 577989 by Alexander James Wallar (computation, corey_goldberg, finance, information, python, realtime, stock, yahoo). Revision 3.

This recipe is solely due to the programming of Corey Goldberg (corey@goldb.org). The only thing I did to it was make it into a class. I thought that by uploading it here that more people would come across it and more people could use it. It is really good. It gives you stock information.

Pareto front (Python)

2012-08-01T09:04:04-07:00

Python recipe 578230 by Jamie Bull (engineering, finance, optimal, pareto_front, pareto_frontier, pareto_set).

Function for finding a 2D Pareto frontier given two lists of matched length.

Script that compares various Interest Rate term structure models. (Python)

2012-09-10T08:02:34-07:00

Python recipe 578256 by alexander baker (finance, matplotlib, python).

A common model used in the financial industry for modelling the short rate (think overnight rate, but actually an infinitesimally short amount of time) is the Vasicek model. # Although it is unlikely to perfectly fit the yield curve, it has some nice properties that make it a good model to work with. The dynamics of the Vasicek model are describe below.

In this model, the parameters are constants, and the random motion is generated by the Q measure Brownian motion . An important property of the Vasicek model is that the interest rate is mean reverting to , and the tendency to revert is controlled by . Also, this process is a diffusion process, hence Markovian, which will lead to some nice closed form formulas. Finally, the future value of the interest rate is normally distributed with the distribution .

Monte Carlo Engine : How to find the optimised wager for next bet, following a recent loss. (Python)

2014-04-28T08:41:49-07:00

Python recipe 578869 by alexander baker (finance, optimise, python, tree).

Simple Engine to help understand how to best wager your next bet, given that you just made a loss. The engine uses the modified Powell method to optimise the weight to apply to your wager on the next position.

{'My Simple Heads And Tails Model': <BackTest.Simulation object at 0x0583D410>} participants [100] survivors [90.0%] losers [10.0%] weight [0.073858] solving for r: [ 0.07385806] simulations 100, trials 100 starting pot 1000 calling initialise {'My Simple Heads And Tails Model': <BackTest.Simulation object at 0x0583D430>} participants [100] survivors [86.0%] losers [14.0%] weight [0.072220] solving for r: [ 0.07221954] Optimization terminated successfully. Current function value: 8.000000 Iterations: 2 Function evaluations: 30 highest survivability following loss, multiply wager by 7.2949 %

.

Ran 2 tests in 25.545s

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