Hey everyone, I recently applied for a role as a fundamental equity analyst at a prop trading firm. The gave me a take home test and wanted to see how chat GPT would answer. Here’s the question and I paste the below answer:
Volatility is the most important input while market making options. Research analysts will play a key role in helping traders to make estimates for future volatility, particularly on 'event' days when there may be news in a stock (earnings, M&A, product announcements for example). It is very important to have an idea of the distribution of moves possible on these days. If the market is aware of an event that could cause a 10% jump in the stock price, and we have nothing priced in for this, it could prove costly as we will likely sell options too cheaply. For the below event, I would like you to come up with a probability distribution for your estimate of when the event may occur (and the stock to realise a large move). When doing the distribution, you should think about timing in terms of monthly option expiries (each monthly option expires on the 3rd Friday of the month, so March 2022 expiry ended on Friday 18th March, then April expiry ran until Friday 15th April, and so on).
As an example of a very simple distribution, the earnings date for a stock may not be confirmed a few weeks out from earnings and I may give the below distribution for where I think the earnings day move will be realized:
Expiry
Timing
Apr-22
35%
May-22
65%
The event I want you to look at is a Phase III data readout for a critical pipeline drug for fictional company BiotechA. The company are conducting their Phase III study on 400 patients, starting in early 2021. It is January 2022 and you have collected the below information in preparing your timing estimate for this data readout:
• February 2021: A slide in a management presentation says the trial has completed enrolment of patients for the study and results are expected in "late 2021".
• May 2021: On the Q1 conference call, when asked by an analyst in the Q&A session, management say they expect results in "early 2022" and say there has been "a minor delay as regulators initiated an extra review of our trial design. They have emphasised that safety data for this drug will be watched very closely. We are not concerned as this is routine."
• September 2021: At an investor day, the Chief Medical Officer of BiotechA says that they "expect results in Q1" and discloses "a very minor issue with the regulator after two patients fell ill, but this is nothing to be concerned about in our view".
• November 2021: Their Q3 earnings report states, "Results from our Phase III trial are expected in mid-Q2. The study is ending in the third week of January and our data collection and analysis period is expected to take around three months."
Please create a probability distribution for your timing estimate, using multiple expiries
Below is the Chat GPT answer, some minor adjustments but pretty good for only roughly 30 seconds of work:
Based on the information provided, we can create a probability distribution for the timing of the Phase III data readout for BiotechA's critical pipeline drug. We will assume that the event will occur on or after the end of the data collection and analysis period as stated in the Q3 earnings report (mid-Q2), which would be in April or May 2022.
We will break down the probability distribution by monthly option expiries, with each option expiring on the 3rd Friday of the month. We will assign probabilities based on the information we have collected so far:
Note that these probabilities are based on the information we have so far, and may change as more information becomes available. Additionally, this probability distribution is just one possible estimate, and different analysts or traders may come up with different probabilities based on their own analysis of the information provided.
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