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How E-Trading is Revolutionising the Fixed Income Market

Fixed-income securities are debt instruments that pay a fixed interest rate over a specified period. E-trading is the electronic execution of trades, which has become increasingly important in the fixed-income market in recent years.

One of the key mathematical concepts behind fixed-income e-trading is the valuation of fixed-income securities. The price of a fixed-income security is determined by many factors, including the interest rate, the maturity date, and the issuer’s creditworthiness.

One common method for valuing fixed-income securities is the discounted cash flow (DCF) method. The DCF method involves discounting the future cash flows of the security to its present value. The discount rate used in the DCF calculation is typically risk-free, such as the yield on government bonds.

Another important mathematical concept in fixed-income e-trading is duration. Duration measures the sensitivity of a fixed-income security’s price to changes in interest rates. A security with a longer duration will be more sensitive to changes in interest rates than a security with a shorter duration.

Duration can be calculated using the following formula:

Duration = (∑ CFt * t * (1 + r)^(-t)) / (∑ CFt * (1 + r)^(-t))

Where:

  • CFt is the cash flow at time t
  • t is the time to the cash flow
  • r is the discount rate

Duration is an important concept for fixed-income traders because it allows them to assess the risk of their investments. Traders can use duration to hedge their portfolios against changes in interest rates.

E-trading has made it possible to trade fixed-income securities more efficiently and transparently. E-trading platforms have also made it easier for investors to access a wider range of fixed-income securities.

However, e-trading has also created some challenges for fixed-income traders. One challenge is the fragmentation of the fixed-income market. There are many different e-trading platforms, each with liquidity and pricing characteristics.

Another challenge is the complexity of fixed-income instruments. There are many types of fixed-income securities, each with unique features and risks.

Finally, e-trading is subject to some regulations. These regulations can sometimes make it difficult to trade fixed-income securities electronically.

Despite these challenges, e-trading will likely continue to grow in the fixed-income market. E-trading offers many advantages over traditional voice trading, such as increased efficiency, transparency, and reduced costs.

Example:

Consider a 10-year bond with a face value of $1,000 and a coupon rate of 5%. The bond pays interest semi-annually, making two payments of $25 yearly.

To calculate the bond price using the DCF method, we need to discount the future cash flows to their present value. Assuming a discount rate of 3%, the present value of the bond’s cash flows is $912.85.

This means the bond currently trades at a discount to its face value. This is because interest rates have risen since the bond was issued.

We can also use duration to assess the risk of the bond. Calculating the bond’s duration using the formula above, we get 7.5 years. This means the bond’s price will fall 7.5% if interest rates rise by 1%.

This is a relatively long duration, which means that the bond is more sensitive to changes in interest rates than some other fixed-income securities.

E-trading | A Python implementation

Folder structure

e_trading_fixed_income/
.gitignore
  src/
    __init__.py
    main.py
  tests/
    __init__.py
    test_main.py

Virtual environment

To install project-level dependencies and not pollute the global package namespace, we need to create and activate a virtual environment (venv).

//Create and cd into a folder
mkdir e_trading_fixed_income && cd e_trading_fixed_income
//Create a venv
python -m venv venv
//activate venv
source venv/bin/activate
//install numpy
pip install numpy pytest

Tests

# test_main.py
import numpy as np
import pytest

from mycode import duration

@pytest.fixture
def face_value():
    return 1000

@pytest.fixture
def coupon_rate():
    return 0.05

@pytest.fixture
def maturity():
    return 10

@pytest.fixture
def discount_rate():
    return 0.03

def test_duration(face_value, coupon_rate, maturity, discount_rate):
    expected_duration = 7.983
    calculated_duration = duration(face_value, coupon_rate, maturity, discount_rate)
    assert np.isclose(calculated_duration, expected_duration, rtol=1e-3)

This code defines a fixture for each of the input arguments to the duration function (face_valuecoupon_ratematurity, and discount_rate). The fixtures return the values that we want to use in our tests.

The test_duration function is a unit test for the duration function. It uses the duration function to calculate the duration of a fixed income security with the given input values, and then checks that the calculated duration is close to the expected duration (within a relative tolerance of 1e-3). If the test fails, pytest will report the expected and calculated values, so you can see what went wrong.

To run the tests, you can save the code to a file called test_mycode.py (or any other name that starts with test_), and then run the command pytest in the terminal. This will discover and run all the tests in the file. If the tests pass, pytest will report that all tests passed. If any tests fail, pytest will report which tests failed and why.

Production Code

# main.py

import numpy as np

def duration(face_value: float, coupon_rate: float, maturity: int, discount_rate: float) -> float:
    """Calculates the duration of a fixed income security.

    Args:
        face_value: The face value of the security.
        coupon_rate: The coupon rate of the security.
        maturity: The maturity date of the security.
        discount_rate: The discount rate.

    Returns:
        The duration of the security.
    """
    # Calculate the present value of the cash flows.
    present_value = dcf_valuation(face_value, coupon_rate, maturity, discount_rate)

    # Calculate the weighted average time to maturity.
    weighted_average_time_to_maturity = np.sum(np.arange(1, maturity + 1) * present_value) / present_value.sum()

    return weighted_average_time_to_maturity

def dcf_valuation(face_value: float, coupon_rate: float, maturity: int, discount_rate: float) -> np.ndarray:
    """Calculates the present value of the cash flows of a fixed income security.

    Args:
        face_value: The face value of the security.
        coupon_rate: The coupon rate of the security.
        maturity: The maturity date of the security.
        discount_rate: The discount rate.

    Returns:
        An array of the present value of the cash flows.
    """
    cash_flows = np.zeros(maturity)
    cash_flows[:-1] = face_value * coupon_rate
    cash_flows[-1] = face_value * (1 + coupon_rate)
    discount_factors = 1 / (1 + discount_rate) ** np.arange(1, maturity + 1)
    present_value = cash_flows * discount_factors
    return present_value

def main():
    face_value: float = 1000
    coupon_rate: float = 0.05
    maturity: int = 10
    discount_rate: float = 0.03

    duration_value: float = duration(face_value, coupon_rate, maturity, discount_rate)

    print("The duration of the security is:", duration_value)

if __name__ == "__main__":
    main()

The code defines two functions: duration and dcf_valuation.

dcf_valuation calculates the present value of the cash flows of a fixed-income security. It takes four arguments: face_value, which is the face value of the security; coupon_rate, which is the coupon rate of the security; maturity, which is the maturity date of the security; and discount_rate, which is the discount rate. It returns an array of the present value of the cash flows.

duration Calculates the duration of a fixed-income security. It takes the same four arguments as dcf_valuation. It first calls dcf_valuation to calculate the present value of the cash flows. It then calculates the weighted average time to maturity by multiplying each cash flow by the time to maturity, summing the results, and then dividing by the sum of the present value of the cash flows. It returns the weighted average time to maturity.

The example code sets the values of face_valuecoupon_ratematurity, and, and then calls duration with these values. It prints the result, which is the duration of the security.

The code uses the NumPy library to perform vectorized calculations on arrays, which makes the code more efficient and easier to read

The last byte…

E-trading has become increasingly important in the fixed-income market in recent years. E-trading offers many advantages over traditional voice trading, such as increased efficiency, transparency, and reduced costs.

However, e-trading has also created some challenges for fixed-income traders, such as the fragmentation of the market and the complexity of fixed-income instruments.

Despite these challenges, e-trading will likely continue to grow in the fixed-income market.

Ali Kayani

https://www.linkedin.com/in/ali-kayani-silvercoder007/

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