Python numpy.irr() Examples

The following are 30 code examples for showing how to use numpy.irr(). These examples are extracted from open source projects. You can vote up the ones you like or vote down the ones you don't like, and go to the original project or source file by following the links above each example.

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Example 1
Project: recruit   Author: Frank-qlu   File: test_financial.py    License: Apache License 2.0 7 votes vote down vote up
def test_irr(self):
        v = [-150000, 15000, 25000, 35000, 45000, 60000]
        assert_almost_equal(np.irr(v), 0.0524, 2)
        v = [-100, 0, 0, 74]
        assert_almost_equal(np.irr(v), -0.0955, 2)
        v = [-100, 39, 59, 55, 20]
        assert_almost_equal(np.irr(v), 0.28095, 2)
        v = [-100, 100, 0, -7]
        assert_almost_equal(np.irr(v), -0.0833, 2)
        v = [-100, 100, 0, 7]
        assert_almost_equal(np.irr(v), 0.06206, 2)
        v = [-5, 10.5, 1, -8, 1]
        assert_almost_equal(np.irr(v), 0.0886, 2)

        # Test that if there is no solution then np.irr returns nan
        # Fixes gh-6744
        v = [-1, -2, -3]
        assert_equal(np.irr(v), np.nan) 
Example 2
Project: lambda-packs   Author: ryfeus   File: test_financial.py    License: MIT License 7 votes vote down vote up
def test_irr(self):
        v = [-150000, 15000, 25000, 35000, 45000, 60000]
        assert_almost_equal(np.irr(v), 0.0524, 2)
        v = [-100, 0, 0, 74]
        assert_almost_equal(np.irr(v), -0.0955, 2)
        v = [-100, 39, 59, 55, 20]
        assert_almost_equal(np.irr(v), 0.28095, 2)
        v = [-100, 100, 0, -7]
        assert_almost_equal(np.irr(v), -0.0833, 2)
        v = [-100, 100, 0, 7]
        assert_almost_equal(np.irr(v), 0.06206, 2)
        v = [-5, 10.5, 1, -8, 1]
        assert_almost_equal(np.irr(v), 0.0886, 2)

        # Test that if there is no solution then np.irr returns nan
        # Fixes gh-6744
        v = [-1, -2, -3]
        assert_equal(np.irr(v), np.nan) 
Example 3
Project: vnpy_crypto   Author: birforce   File: test_financial.py    License: MIT License 6 votes vote down vote up
def test_irr(self):
        v = [-150000, 15000, 25000, 35000, 45000, 60000]
        assert_almost_equal(np.irr(v), 0.0524, 2)
        v = [-100, 0, 0, 74]
        assert_almost_equal(np.irr(v), -0.0955, 2)
        v = [-100, 39, 59, 55, 20]
        assert_almost_equal(np.irr(v), 0.28095, 2)
        v = [-100, 100, 0, -7]
        assert_almost_equal(np.irr(v), -0.0833, 2)
        v = [-100, 100, 0, 7]
        assert_almost_equal(np.irr(v), 0.06206, 2)
        v = [-5, 10.5, 1, -8, 1]
        assert_almost_equal(np.irr(v), 0.0886, 2)

        # Test that if there is no solution then np.irr returns nan
        # Fixes gh-6744
        v = [-1, -2, -3]
        assert_equal(np.irr(v), np.nan) 
Example 4
Project: Mastering-Elasticsearch-7.0   Author: PacktPublishing   File: test_financial.py    License: MIT License 6 votes vote down vote up
def test_irr(self):
        v = [-150000, 15000, 25000, 35000, 45000, 60000]
        assert_almost_equal(np.irr(v), 0.0524, 2)
        v = [-100, 0, 0, 74]
        assert_almost_equal(np.irr(v), -0.0955, 2)
        v = [-100, 39, 59, 55, 20]
        assert_almost_equal(np.irr(v), 0.28095, 2)
        v = [-100, 100, 0, -7]
        assert_almost_equal(np.irr(v), -0.0833, 2)
        v = [-100, 100, 0, 7]
        assert_almost_equal(np.irr(v), 0.06206, 2)
        v = [-5, 10.5, 1, -8, 1]
        assert_almost_equal(np.irr(v), 0.0886, 2)

        # Test that if there is no solution then np.irr returns nan
        # Fixes gh-6744
        v = [-1, -2, -3]
        assert_equal(np.irr(v), np.nan) 
Example 5
Project: GraphicDesignPatternByPython   Author: Relph1119   File: test_financial.py    License: MIT License 6 votes vote down vote up
def test_irr(self):
        v = [-150000, 15000, 25000, 35000, 45000, 60000]
        assert_almost_equal(np.irr(v), 0.0524, 2)
        v = [-100, 0, 0, 74]
        assert_almost_equal(np.irr(v), -0.0955, 2)
        v = [-100, 39, 59, 55, 20]
        assert_almost_equal(np.irr(v), 0.28095, 2)
        v = [-100, 100, 0, -7]
        assert_almost_equal(np.irr(v), -0.0833, 2)
        v = [-100, 100, 0, 7]
        assert_almost_equal(np.irr(v), 0.06206, 2)
        v = [-5, 10.5, 1, -8, 1]
        assert_almost_equal(np.irr(v), 0.0886, 2)

        # Test that if there is no solution then np.irr returns nan
        # Fixes gh-6744
        v = [-1, -2, -3]
        assert_equal(np.irr(v), np.nan) 
Example 6
Project: koala   Author: vallettea   File: excellib.py    License: GNU General Public License v3.0 6 votes vote down vote up
def irr(values, guess = None):
    """
    Function to calculate the internal rate of return (IRR) using payments and periodic dates. It resembles the
    excel function IRR().

    Excel reference: https://support.office.com/en-us/article/IRR-function-64925eaa-9988-495b-b290-3ad0c163c1bc

    :param values: the payments of which at least one has to be negative.
    :param guess: an initial guess which is required by Excel but isn't used by this function.
    :return: a float being the IRR.
    """
    if isinstance(values, Range):
        values = values.values

    if is_not_number_input(values):
        return numeric_error(values, 'values')

    if guess is not None and guess != 0:
        raise ValueError('guess value for excellib.irr() is %s and not 0' % guess)
    else:
        try:
            return np.irr(values)
        except Exception as e:
            return ExcelError('#NUM!', e) 
Example 7
def test_irr(self):
        v = [-150000, 15000, 25000, 35000, 45000, 60000]
        assert_almost_equal(np.irr(v), 0.0524, 2)
        v = [-100, 0, 0, 74]
        assert_almost_equal(np.irr(v), -0.0955, 2)
        v = [-100, 39, 59, 55, 20]
        assert_almost_equal(np.irr(v), 0.28095, 2)
        v = [-100, 100, 0, -7]
        assert_almost_equal(np.irr(v), -0.0833, 2)
        v = [-100, 100, 0, 7]
        assert_almost_equal(np.irr(v), 0.06206, 2)
        v = [-5, 10.5, 1, -8, 1]
        assert_almost_equal(np.irr(v), 0.0886, 2)

        # Test that if there is no solution then np.irr returns nan
        # Fixes gh-6744
        v = [-1, -2, -3]
        assert_equal(np.irr(v), np.nan) 
Example 8
Project: pySINDy   Author: luckystarufo   File: test_financial.py    License: MIT License 6 votes vote down vote up
def test_irr(self):
        v = [-150000, 15000, 25000, 35000, 45000, 60000]
        assert_almost_equal(np.irr(v), 0.0524, 2)
        v = [-100, 0, 0, 74]
        assert_almost_equal(np.irr(v), -0.0955, 2)
        v = [-100, 39, 59, 55, 20]
        assert_almost_equal(np.irr(v), 0.28095, 2)
        v = [-100, 100, 0, -7]
        assert_almost_equal(np.irr(v), -0.0833, 2)
        v = [-100, 100, 0, 7]
        assert_almost_equal(np.irr(v), 0.06206, 2)
        v = [-5, 10.5, 1, -8, 1]
        assert_almost_equal(np.irr(v), 0.0886, 2)

        # Test that if there is no solution then np.irr returns nan
        # Fixes gh-6744
        v = [-1, -2, -3]
        assert_equal(np.irr(v), np.nan) 
Example 9
Project: mxnet-lambda   Author: awslabs   File: test_financial.py    License: Apache License 2.0 6 votes vote down vote up
def test_irr(self):
        v = [-150000, 15000, 25000, 35000, 45000, 60000]
        assert_almost_equal(np.irr(v), 0.0524, 2)
        v = [-100, 0, 0, 74]
        assert_almost_equal(np.irr(v), -0.0955, 2)
        v = [-100, 39, 59, 55, 20]
        assert_almost_equal(np.irr(v), 0.28095, 2)
        v = [-100, 100, 0, -7]
        assert_almost_equal(np.irr(v), -0.0833, 2)
        v = [-100, 100, 0, 7]
        assert_almost_equal(np.irr(v), 0.06206, 2)
        v = [-5, 10.5, 1, -8, 1]
        assert_almost_equal(np.irr(v), 0.0886, 2)

        # Test that if there is no solution then np.irr returns nan
        # Fixes gh-6744
        v = [-1, -2, -3]
        assert_equal(np.irr(v), np.nan) 
Example 10
Project: ImageFusion   Author: pfchai   File: test_financial.py    License: MIT License 6 votes vote down vote up
def test_irr(self):
        v = [-150000, 15000, 25000, 35000, 45000, 60000]
        assert_almost_equal(np.irr(v),
                            0.0524, 2)
        v = [-100, 0, 0, 74]
        assert_almost_equal(np.irr(v),
                            -0.0955, 2)
        v = [-100, 39, 59, 55, 20]
        assert_almost_equal(np.irr(v),
                            0.28095, 2)
        v = [-100, 100, 0, -7]
        assert_almost_equal(np.irr(v),
                            -0.0833, 2)
        v = [-100, 100, 0, 7]
        assert_almost_equal(np.irr(v),
                            0.06206, 2)
        v = [-5, 10.5, 1, -8, 1]
        assert_almost_equal(np.irr(v),
                            0.0886, 2) 
Example 11
Project: elasticintel   Author: securityclippy   File: test_financial.py    License: GNU General Public License v3.0 6 votes vote down vote up
def test_irr(self):
        v = [-150000, 15000, 25000, 35000, 45000, 60000]
        assert_almost_equal(np.irr(v), 0.0524, 2)
        v = [-100, 0, 0, 74]
        assert_almost_equal(np.irr(v), -0.0955, 2)
        v = [-100, 39, 59, 55, 20]
        assert_almost_equal(np.irr(v), 0.28095, 2)
        v = [-100, 100, 0, -7]
        assert_almost_equal(np.irr(v), -0.0833, 2)
        v = [-100, 100, 0, 7]
        assert_almost_equal(np.irr(v), 0.06206, 2)
        v = [-5, 10.5, 1, -8, 1]
        assert_almost_equal(np.irr(v), 0.0886, 2)

        # Test that if there is no solution then np.irr returns nan
        # Fixes gh-6744
        v = [-1, -2, -3]
        assert_equal(np.irr(v), np.nan) 
Example 12
Project: coffeegrindsize   Author: jgagneastro   File: test_financial.py    License: MIT License 6 votes vote down vote up
def test_irr(self):
        v = [-150000, 15000, 25000, 35000, 45000, 60000]
        assert_almost_equal(np.irr(v), 0.0524, 2)
        v = [-100, 0, 0, 74]
        assert_almost_equal(np.irr(v), -0.0955, 2)
        v = [-100, 39, 59, 55, 20]
        assert_almost_equal(np.irr(v), 0.28095, 2)
        v = [-100, 100, 0, -7]
        assert_almost_equal(np.irr(v), -0.0833, 2)
        v = [-100, 100, 0, 7]
        assert_almost_equal(np.irr(v), 0.06206, 2)
        v = [-5, 10.5, 1, -8, 1]
        assert_almost_equal(np.irr(v), 0.0886, 2)

        # Test that if there is no solution then np.irr returns nan
        # Fixes gh-6744
        v = [-1, -2, -3]
        assert_equal(np.irr(v), np.nan) 
Example 13
Project: Serverless-Deep-Learning-with-TensorFlow-and-AWS-Lambda   Author: PacktPublishing   File: test_financial.py    License: MIT License 6 votes vote down vote up
def test_irr(self):
        v = [-150000, 15000, 25000, 35000, 45000, 60000]
        assert_almost_equal(np.irr(v), 0.0524, 2)
        v = [-100, 0, 0, 74]
        assert_almost_equal(np.irr(v), -0.0955, 2)
        v = [-100, 39, 59, 55, 20]
        assert_almost_equal(np.irr(v), 0.28095, 2)
        v = [-100, 100, 0, -7]
        assert_almost_equal(np.irr(v), -0.0833, 2)
        v = [-100, 100, 0, 7]
        assert_almost_equal(np.irr(v), 0.06206, 2)
        v = [-5, 10.5, 1, -8, 1]
        assert_almost_equal(np.irr(v), 0.0886, 2)

        # Test that if there is no solution then np.irr returns nan
        # Fixes gh-6744
        v = [-1, -2, -3]
        assert_equal(np.irr(v), np.nan) 
Example 14
Project: twitter-stock-recommendation   Author: alvarobartt   File: test_financial.py    License: MIT License 6 votes vote down vote up
def test_irr(self):
        v = [-150000, 15000, 25000, 35000, 45000, 60000]
        assert_almost_equal(np.irr(v), 0.0524, 2)
        v = [-100, 0, 0, 74]
        assert_almost_equal(np.irr(v), -0.0955, 2)
        v = [-100, 39, 59, 55, 20]
        assert_almost_equal(np.irr(v), 0.28095, 2)
        v = [-100, 100, 0, -7]
        assert_almost_equal(np.irr(v), -0.0833, 2)
        v = [-100, 100, 0, 7]
        assert_almost_equal(np.irr(v), 0.06206, 2)
        v = [-5, 10.5, 1, -8, 1]
        assert_almost_equal(np.irr(v), 0.0886, 2)

        # Test that if there is no solution then np.irr returns nan
        # Fixes gh-6744
        v = [-1, -2, -3]
        assert_equal(np.irr(v), np.nan) 
Example 15
Project: formulas   Author: vinci1it2000   File: financial.py    License: European Union Public License 1.1 5 votes vote down vote up
def xirr(values, guess=0.1):
    with np.errstate(divide='ignore', invalid='ignore'):
        res = np.irr(tuple(flatten(text2num(replace_empty(values)).ravel())))
        res = (not np.isfinite(res)) and Error.errors['#NUM!'] or res

        def _(g):
            e = isinstance(g, str) and Error.errors['#VALUE!']
            return get_error(g, e) or res

        guess = text2num(replace_empty(guess))
        return np.vectorize(_, otypes=[object])(guess).view(Array) 
Example 16
Project: auto-alt-text-lambda-api   Author: abhisuri97   File: test_financial.py    License: MIT License 5 votes vote down vote up
def test_irr(self):
        v = [-150000, 15000, 25000, 35000, 45000, 60000]
        assert_almost_equal(np.irr(v), 0.0524, 2)
        v = [-100, 0, 0, 74]
        assert_almost_equal(np.irr(v), -0.0955, 2)
        v = [-100, 39, 59, 55, 20]
        assert_almost_equal(np.irr(v), 0.28095, 2)
        v = [-100, 100, 0, -7]
        assert_almost_equal(np.irr(v), -0.0833, 2)
        v = [-100, 100, 0, 7]
        assert_almost_equal(np.irr(v), 0.06206, 2)
        v = [-5, 10.5, 1, -8, 1]
        assert_almost_equal(np.irr(v), 0.0886, 2) 
Example 17
Project: Computable   Author: ktraunmueller   File: test_financial.py    License: MIT License 5 votes vote down vote up
def test_irr(self):
        v = [-150000, 15000, 25000, 35000, 45000, 60000]
        assert_almost_equal(np.irr(v),
                            0.0524, 2) 
Example 18
Project: cashflows   Author: jdvelasq   File: analysis.py    License: MIT License 5 votes vote down vote up
def irr(cflo):
    """Computes the internal rate of return of a generic cashflow as a periodic
    interest rate.

    Args:
        cflo (pandas.Series): Generic cashflow.

    Returns:
        Float or list of floats.

    **Examples.**

    >>> cflo = cashflow([-200] + [100]*4, start='2000Q1', freq='Q')
    >>> irr(cflo) # doctest: +ELLIPSIS
    34.90...

    >>> irr([cflo, cflo]) # doctest: +ELLIPSIS
    0    34.90...
    1    34.90...
    dtype: float64

    """
    

    if isinstance(cflo, pd.Series):
        cflo = [cflo]
    retval = pd.Series([0] * len(cflo), dtype=np.float64)
    for index, xcflo in enumerate(cflo):
        retval[index] = (100 * np.irr(xcflo))
    if len(retval) == 1:
        return retval[0]
    return retval

## modified internal rate of return 
Example 19
Project: koala   Author: vallettea   File: excellib.py    License: GNU General Public License v3.0 5 votes vote down vote up
def xirr(values, dates, guess=0):
    """
    Function to calculate the internal rate of return (IRR) using payments and non-periodic dates. It resembles the
    excel function XIRR().

    Excel reference: https://support.office.com/en-ie/article/xirr-function-de1242ec-6477-445b-b11b-a303ad9adc9d

    :param values: the payments of which at least one has to be negative.
    :param dates: the dates as excel dates (e.g. 43571 for 16/04/2019).
    :param guess: an initial guess which is required by Excel but isn't used by this function.
    :return: a float being the IRR.
    """

    if isinstance(values, Range):
        values = values.values

    if all(value < 0 for value in values):
        return 0

    if isinstance(dates, Range):
        dates = dates.values

    if is_not_number_input(values):
        return numeric_error(values, 'values')

    if is_not_number_input(dates):
        return numeric_error(dates, 'dates')

    if guess is not None and guess != 0:
        raise ValueError('guess value for excellib.irr() is %s and not 0' % guess)
    else:
        try:
            try:
                return scipy.optimize.newton(lambda r: xnpv(r, values, dates, lim_rate_low=False, lim_rate_high=True), 0.0)
            except (RuntimeError, FloatingPointError, ExcelError):  # Failed to converge?
                return scipy.optimize.brentq(lambda r: xnpv(r, values, dates, lim_rate_low=False, lim_rate_high=True), -1.0, 1e5)
        except Exception:
            return ExcelError('#NUM', 'IRR did not converge.') 
Example 20
Project: keras-lambda   Author: sunilmallya   File: test_financial.py    License: MIT License 5 votes vote down vote up
def test_irr(self):
        v = [-150000, 15000, 25000, 35000, 45000, 60000]
        assert_almost_equal(np.irr(v), 0.0524, 2)
        v = [-100, 0, 0, 74]
        assert_almost_equal(np.irr(v), -0.0955, 2)
        v = [-100, 39, 59, 55, 20]
        assert_almost_equal(np.irr(v), 0.28095, 2)
        v = [-100, 100, 0, -7]
        assert_almost_equal(np.irr(v), -0.0833, 2)
        v = [-100, 100, 0, 7]
        assert_almost_equal(np.irr(v), 0.06206, 2)
        v = [-5, 10.5, 1, -8, 1]
        assert_almost_equal(np.irr(v), 0.0886, 2) 
Example 21
Project: recruit   Author: Frank-qlu   File: financial.py    License: Apache License 2.0 4 votes vote down vote up
def npv(rate, values):
    """
    Returns the NPV (Net Present Value) of a cash flow series.

    Parameters
    ----------
    rate : scalar
        The discount rate.
    values : array_like, shape(M, )
        The values of the time series of cash flows.  The (fixed) time
        interval between cash flow "events" must be the same as that for
        which `rate` is given (i.e., if `rate` is per year, then precisely
        a year is understood to elapse between each cash flow event).  By
        convention, investments or "deposits" are negative, income or
        "withdrawals" are positive; `values` must begin with the initial
        investment, thus `values[0]` will typically be negative.

    Returns
    -------
    out : float
        The NPV of the input cash flow series `values` at the discount
        `rate`.

    Notes
    -----
    Returns the result of: [G]_

    .. math :: \\sum_{t=0}^{M-1}{\\frac{values_t}{(1+rate)^{t}}}

    References
    ----------
    .. [G] L. J. Gitman, "Principles of Managerial Finance, Brief," 3rd ed.,
       Addison-Wesley, 2003, pg. 346.

    Examples
    --------
    >>> np.npv(0.281,[-100, 39, 59, 55, 20])
    -0.0084785916384548798

    (Compare with the Example given for numpy.lib.financial.irr)

    """
    values = np.asarray(values)
    return (values / (1+rate)**np.arange(0, len(values))).sum(axis=0) 
Example 22
Project: lambda-packs   Author: ryfeus   File: financial.py    License: MIT License 4 votes vote down vote up
def npv(rate, values):
    """
    Returns the NPV (Net Present Value) of a cash flow series.

    Parameters
    ----------
    rate : scalar
        The discount rate.
    values : array_like, shape(M, )
        The values of the time series of cash flows.  The (fixed) time
        interval between cash flow "events" must be the same as that for
        which `rate` is given (i.e., if `rate` is per year, then precisely
        a year is understood to elapse between each cash flow event).  By
        convention, investments or "deposits" are negative, income or
        "withdrawals" are positive; `values` must begin with the initial
        investment, thus `values[0]` will typically be negative.

    Returns
    -------
    out : float
        The NPV of the input cash flow series `values` at the discount
        `rate`.

    Notes
    -----
    Returns the result of: [G]_

    .. math :: \\sum_{t=0}^{M-1}{\\frac{values_t}{(1+rate)^{t}}}

    References
    ----------
    .. [G] L. J. Gitman, "Principles of Managerial Finance, Brief," 3rd ed.,
       Addison-Wesley, 2003, pg. 346.

    Examples
    --------
    >>> np.npv(0.281,[-100, 39, 59, 55, 20])
    -0.0084785916384548798

    (Compare with the Example given for numpy.lib.financial.irr)

    """
    values = np.asarray(values)
    return (values / (1+rate)**np.arange(0, len(values))).sum(axis=0) 
Example 23
Project: lambda-packs   Author: ryfeus   File: financial.py    License: MIT License 4 votes vote down vote up
def npv(rate, values):
    """
    Returns the NPV (Net Present Value) of a cash flow series.

    Parameters
    ----------
    rate : scalar
        The discount rate.
    values : array_like, shape(M, )
        The values of the time series of cash flows.  The (fixed) time
        interval between cash flow "events" must be the same as that for
        which `rate` is given (i.e., if `rate` is per year, then precisely
        a year is understood to elapse between each cash flow event).  By
        convention, investments or "deposits" are negative, income or
        "withdrawals" are positive; `values` must begin with the initial
        investment, thus `values[0]` will typically be negative.

    Returns
    -------
    out : float
        The NPV of the input cash flow series `values` at the discount
        `rate`.

    Notes
    -----
    Returns the result of: [G]_

    .. math :: \\sum_{t=0}^{M-1}{\\frac{values_t}{(1+rate)^{t}}}

    References
    ----------
    .. [G] L. J. Gitman, "Principles of Managerial Finance, Brief," 3rd ed.,
       Addison-Wesley, 2003, pg. 346.

    Examples
    --------
    >>> np.npv(0.281,[-100, 39, 59, 55, 20])
    -0.0084785916384548798

    (Compare with the Example given for numpy.lib.financial.irr)

    """
    values = np.asarray(values)
    return (values / (1+rate)**np.arange(0, len(values))).sum(axis=0) 
Example 24
Project: auto-alt-text-lambda-api   Author: abhisuri97   File: financial.py    License: MIT License 4 votes vote down vote up
def npv(rate, values):
    """
    Returns the NPV (Net Present Value) of a cash flow series.

    Parameters
    ----------
    rate : scalar
        The discount rate.
    values : array_like, shape(M, )
        The values of the time series of cash flows.  The (fixed) time
        interval between cash flow "events" must be the same as that for
        which `rate` is given (i.e., if `rate` is per year, then precisely
        a year is understood to elapse between each cash flow event).  By
        convention, investments or "deposits" are negative, income or
        "withdrawals" are positive; `values` must begin with the initial
        investment, thus `values[0]` will typically be negative.

    Returns
    -------
    out : float
        The NPV of the input cash flow series `values` at the discount
        `rate`.

    Notes
    -----
    Returns the result of: [G]_

    .. math :: \\sum_{t=0}^{M-1}{\\frac{values_t}{(1+rate)^{t}}}

    References
    ----------
    .. [G] L. J. Gitman, "Principles of Managerial Finance, Brief," 3rd ed.,
       Addison-Wesley, 2003, pg. 346.

    Examples
    --------
    >>> np.npv(0.281,[-100, 39, 59, 55, 20])
    -0.0084785916384548798

    (Compare with the Example given for numpy.lib.financial.irr)

    """
    values = np.asarray(values)
    return (values / (1+rate)**np.arange(0, len(values))).sum(axis=0) 
Example 25
Project: vnpy_crypto   Author: birforce   File: financial.py    License: MIT License 4 votes vote down vote up
def npv(rate, values):
    """
    Returns the NPV (Net Present Value) of a cash flow series.

    Parameters
    ----------
    rate : scalar
        The discount rate.
    values : array_like, shape(M, )
        The values of the time series of cash flows.  The (fixed) time
        interval between cash flow "events" must be the same as that for
        which `rate` is given (i.e., if `rate` is per year, then precisely
        a year is understood to elapse between each cash flow event).  By
        convention, investments or "deposits" are negative, income or
        "withdrawals" are positive; `values` must begin with the initial
        investment, thus `values[0]` will typically be negative.

    Returns
    -------
    out : float
        The NPV of the input cash flow series `values` at the discount
        `rate`.

    Notes
    -----
    Returns the result of: [G]_

    .. math :: \\sum_{t=0}^{M-1}{\\frac{values_t}{(1+rate)^{t}}}

    References
    ----------
    .. [G] L. J. Gitman, "Principles of Managerial Finance, Brief," 3rd ed.,
       Addison-Wesley, 2003, pg. 346.

    Examples
    --------
    >>> np.npv(0.281,[-100, 39, 59, 55, 20])
    -0.0084785916384548798

    (Compare with the Example given for numpy.lib.financial.irr)

    """
    values = np.asarray(values)
    return (values / (1+rate)**np.arange(0, len(values))).sum(axis=0) 
Example 26
Project: Computable   Author: ktraunmueller   File: financial.py    License: MIT License 4 votes vote down vote up
def npv(rate, values):
    """
    Returns the NPV (Net Present Value) of a cash flow series.

    Parameters
    ----------
    rate : scalar
        The discount rate.
    values : array_like, shape(M, )
        The values of the time series of cash flows.  The (fixed) time
        interval between cash flow "events" must be the same as that
        for which `rate` is given (i.e., if `rate` is per year, then
        precisely a year is understood to elapse between each cash flow
        event).  By convention, investments or "deposits" are negative,
        income or "withdrawals" are positive; `values` must begin with
        the initial investment, thus `values[0]` will typically be
        negative.

    Returns
    -------
    out : float
        The NPV of the input cash flow series `values` at the discount `rate`.

    Notes
    -----
    Returns the result of: [G]_

    .. math :: \\sum_{t=0}^{M-1}{\\frac{values_t}{(1+rate)^{t}}}

    References
    ----------
    .. [G] L. J. Gitman, "Principles of Managerial Finance, Brief," 3rd ed.,
       Addison-Wesley, 2003, pg. 346.

    Examples
    --------
    >>> np.npv(0.281,[-100, 39, 59, 55, 20])
    -0.0084785916384548798

    (Compare with the Example given for numpy.lib.financial.irr)

    """
    values = np.asarray(values)
    return (values / (1+rate)**np.arange(0, len(values))).sum(axis=0) 
Example 27
Project: Mastering-Elasticsearch-7.0   Author: PacktPublishing   File: financial.py    License: MIT License 4 votes vote down vote up
def npv(rate, values):
    """
    Returns the NPV (Net Present Value) of a cash flow series.

    Parameters
    ----------
    rate : scalar
        The discount rate.
    values : array_like, shape(M, )
        The values of the time series of cash flows.  The (fixed) time
        interval between cash flow "events" must be the same as that for
        which `rate` is given (i.e., if `rate` is per year, then precisely
        a year is understood to elapse between each cash flow event).  By
        convention, investments or "deposits" are negative, income or
        "withdrawals" are positive; `values` must begin with the initial
        investment, thus `values[0]` will typically be negative.

    Returns
    -------
    out : float
        The NPV of the input cash flow series `values` at the discount
        `rate`.

    Notes
    -----
    Returns the result of: [G]_

    .. math :: \\sum_{t=0}^{M-1}{\\frac{values_t}{(1+rate)^{t}}}

    References
    ----------
    .. [G] L. J. Gitman, "Principles of Managerial Finance, Brief," 3rd ed.,
       Addison-Wesley, 2003, pg. 346.

    Examples
    --------
    >>> np.npv(0.281,[-100, 39, 59, 55, 20])
    -0.0084785916384548798

    (Compare with the Example given for numpy.lib.financial.irr)

    """
    values = np.asarray(values)
    return (values / (1+rate)**np.arange(0, len(values))).sum(axis=0) 
Example 28
Project: GraphicDesignPatternByPython   Author: Relph1119   File: financial.py    License: MIT License 4 votes vote down vote up
def npv(rate, values):
    """
    Returns the NPV (Net Present Value) of a cash flow series.

    Parameters
    ----------
    rate : scalar
        The discount rate.
    values : array_like, shape(M, )
        The values of the time series of cash flows.  The (fixed) time
        interval between cash flow "events" must be the same as that for
        which `rate` is given (i.e., if `rate` is per year, then precisely
        a year is understood to elapse between each cash flow event).  By
        convention, investments or "deposits" are negative, income or
        "withdrawals" are positive; `values` must begin with the initial
        investment, thus `values[0]` will typically be negative.

    Returns
    -------
    out : float
        The NPV of the input cash flow series `values` at the discount
        `rate`.

    Notes
    -----
    Returns the result of: [G]_

    .. math :: \\sum_{t=0}^{M-1}{\\frac{values_t}{(1+rate)^{t}}}

    References
    ----------
    .. [G] L. J. Gitman, "Principles of Managerial Finance, Brief," 3rd ed.,
       Addison-Wesley, 2003, pg. 346.

    Examples
    --------
    >>> np.npv(0.281,[-100, 39, 59, 55, 20])
    -0.0084785916384548798

    (Compare with the Example given for numpy.lib.financial.irr)

    """
    values = np.asarray(values)
    return (values / (1+rate)**np.arange(0, len(values))).sum(axis=0) 
Example 29
def npv(rate, values):
    """
    Returns the NPV (Net Present Value) of a cash flow series.

    Parameters
    ----------
    rate : scalar
        The discount rate.
    values : array_like, shape(M, )
        The values of the time series of cash flows.  The (fixed) time
        interval between cash flow "events" must be the same as that for
        which `rate` is given (i.e., if `rate` is per year, then precisely
        a year is understood to elapse between each cash flow event).  By
        convention, investments or "deposits" are negative, income or
        "withdrawals" are positive; `values` must begin with the initial
        investment, thus `values[0]` will typically be negative.

    Returns
    -------
    out : float
        The NPV of the input cash flow series `values` at the discount
        `rate`.

    Notes
    -----
    Returns the result of: [G]_

    .. math :: \\sum_{t=0}^{M-1}{\\frac{values_t}{(1+rate)^{t}}}

    References
    ----------
    .. [G] L. J. Gitman, "Principles of Managerial Finance, Brief," 3rd ed.,
       Addison-Wesley, 2003, pg. 346.

    Examples
    --------
    >>> np.npv(0.281,[-100, 39, 59, 55, 20])
    -0.0084785916384548798

    (Compare with the Example given for numpy.lib.financial.irr)

    """
    values = np.asarray(values)
    return (values / (1+rate)**np.arange(0, len(values))).sum(axis=0) 
Example 30
Project: Fluid-Designer   Author: Microvellum   File: financial.py    License: GNU General Public License v3.0 4 votes vote down vote up
def npv(rate, values):
    """
    Returns the NPV (Net Present Value) of a cash flow series.

    Parameters
    ----------
    rate : scalar
        The discount rate.
    values : array_like, shape(M, )
        The values of the time series of cash flows.  The (fixed) time
        interval between cash flow "events" must be the same as that for
        which `rate` is given (i.e., if `rate` is per year, then precisely
        a year is understood to elapse between each cash flow event).  By
        convention, investments or "deposits" are negative, income or
        "withdrawals" are positive; `values` must begin with the initial
        investment, thus `values[0]` will typically be negative.

    Returns
    -------
    out : float
        The NPV of the input cash flow series `values` at the discount
        `rate`.

    Notes
    -----
    Returns the result of: [G]_

    .. math :: \\sum_{t=0}^{M-1}{\\frac{values_t}{(1+rate)^{t}}}

    References
    ----------
    .. [G] L. J. Gitman, "Principles of Managerial Finance, Brief," 3rd ed.,
       Addison-Wesley, 2003, pg. 346.

    Examples
    --------
    >>> np.npv(0.281,[-100, 39, 59, 55, 20])
    -0.0084785916384548798

    (Compare with the Example given for numpy.lib.financial.irr)

    """
    values = np.asarray(values)
    return (values / (1+rate)**np.arange(0, len(values))).sum(axis=0)