Financial Analysis - Build a ChatGPT Pairs Trading Bot - Testing the Strategy

Financial Analysis - Build a ChatGPT Pairs Trading Bot - Testing the Strategy

Assessment

Interactive Video

Computers

10th - 12th Grade

Hard

Created by

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The video tutorial walks through debugging a trading algorithm. Initially, the code is rerun to check for issues, revealing a problem with the trading signals. The instructor identifies a bug related to the normalization of the spread and bounds, leading to incorrect signals. By removing unnecessary normalization, the algorithm is corrected, resulting in improved performance and returns. The tutorial concludes with a demonstration of the corrected algorithm's results, showing a more logical switching between long and short positions.

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7 questions

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1.

MULTIPLE CHOICE QUESTION

30 sec • 1 pt

What was the initial issue with the trading signals for KO and Pepsi?

The signals were not being generated at all.

The signals were fluctuating too frequently.

The signals were only going long for both assets.

The signals were consistently long for one asset and short for the other.

2.

MULTIPLE CHOICE QUESTION

30 sec • 1 pt

What was the identified bug related to the spread and bounds?

The spread was not normalized, unlike the bounds.

The spread was not being calculated.

The spread was always below the lower bound.

The spread was always above the upper bound.

3.

MULTIPLE CHOICE QUESTION

30 sec • 1 pt

What was the mistake in the normalization process?

Neither the spread nor the assets were normalized.

Only the spread was normalized, not the assets.

Both the spread and assets were normalized.

The normalization was applied to the wrong dataset.

4.

MULTIPLE CHOICE QUESTION

30 sec • 1 pt

After correcting the normalization, what issue did the algorithm still face?

The algorithm returned excessively high values.

The algorithm returned negative values.

The algorithm returned zero consistently.

The algorithm returned random values.

5.

MULTIPLE CHOICE QUESTION

30 sec • 1 pt

What was the final correction made to resolve the issue?

Reverting to the original code.

Using the spread instead of the spread mean.

Using the spread mean instead of the spread.

Adjusting the spread to be the mean.

6.

MULTIPLE CHOICE QUESTION

30 sec • 1 pt

What was the outcome after the final correction?

The algorithm produced a 10% return.

The algorithm produced a 25% return.

The algorithm produced no return.

The algorithm produced a 50% return.

7.

MULTIPLE CHOICE QUESTION

30 sec • 1 pt

How did the positions behave after the final correction?

They only went short.

They remained constant.

They switched between long and short.

They only went long.