Sure, here is a Python function using numpy to compute the net present value (NPV) of a set of cash flows given their timing and a single discount rate with continuous compounding.

```python
import numpy as np

def npv(cash_flows, timing, discount_rate):
"""
Compute the net present value of a set of cash flows given their timing and a single discount rate with continuous compounding.

Parameters:
cash_flows (numpy array): The cash flows.
timing (numpy array): The timing of the cash flows.
discount_rate (float): The discount rate.

Returns:
float: The net present value of the cash flows.
"""
# Compute the present value of each cash flow
present_values = cash_flows * np.exp(-discount_rate * timing)

# Sum up the present values to get the net present value
npv = np.sum(present_values)

return npv
```

Here's how you can use this function:

```python
cash_flows = np.array([100, 200, 300, 400, 500])
timing = np.array([1, 2, 3, 4, 5])
discount_rate = 0.05

print(npv(cash_flows, timing, discount_rate))
```

This will compute the NPV of the cash flows [100, 200, 300, 400, 500] at times [1, 2, 3, 4, 5] with a discount rate of 5%. The `np.exp(-discount_rate * timing)` part is the formula for continuous compounding.

Question

Sure, here is a Python function using numpy to compute the net present value (NPV) of a set of cash flows given their timing and a single discount rate with continuous compounding.

```python
import numpy as np

def npv(cash_flows, timing, discount_rate):
    """
    Compute the net present value of a set of cash flows given their timing and a single discount rate with continuous compounding.

Parameters:
    cash_flows (numpy array): The cash flows.
    timing (numpy array): The timing of the cash flows.
    discount_rate (float): The discount rate.

Returns:
    float: The net present value of the cash flows.
    """
    # Compute the present value of each cash flow
    present_values = cash_flows * np.exp(-discount_rate * timing)

# Sum up the present values to get the net present value
    npv = np.sum(present_values)

return npv
```

Here's how you can use this function:

```python
cash_flows = np.array([100, 200, 300, 400, 500])
timing = np.array([1, 2, 3, 4, 5])
discount_rate = 0.05

print(npv(cash_flows, timing, discount_rate))
```

This will compute the NPV of the cash flows [100, 200, 300, 400, 500] at times [1, 2, 3, 4, 5] with a discount rate of 5%. The `np.exp(-discount_rate * timing)` part is the formula for continuous compounding.

Knowee AI · Accepted Answer

Sure, here is a Python function using numpy to compute the net present value (NPV) of a set of cash flows given their timing and a single discount rate with continuous compounding.

```python
import numpy as np

def npv(cash_flows, timing, discount_rate):
    """
    Compute the net present value of a set of cash flows given their timing and a single discount rate with continuous compounding.

Parameters:
    cash_flows (numpy array): The cash flows.
    timing (numpy array): The timing of the cash flows.
    discount_rate (float): The discount rate.

Returns:
    float: The net present value of the cash flows.
    """
    # Compute the present value of each cash flow
    present_values = cash_flows * np.exp(-discount_rate * timing)

# Sum up the present values to get the net present value
    npv = np.sum(present_values)

return npv
```

Here's how you can use this function:

```python
cash_flows = np.array([100, 200, 300, 400, 500])
timing = np.array([1, 2, 3, 4, 5])
discount_rate = 0.05

print(npv(cash_flows, timing, discount_rate))
```

This will compute the NPV of the cash flows [100, 200, 300, 400, 500] at times [1, 2, 3, 4, 5] with a discount rate of 5%. The `np.exp(-discount_rate * timing)` part is the formula for continuous compounding.

Using numpy, write function npv to compute the net present value of a set of cash flows given their timing and a single discount rate with continuous compounding.

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