3rd JLTi Code Jam – May 2017
Input: price = [961, 984.5, 965, 988.5, 956.5]
Explanation: Now that your bank accounts are flooding with April bonus money and you are contemplating to invest in stock market why not join me in doing some analysis first? After all, we are engineers flooded with data (quite a lot of them are free) and the capability to analyse them. I opened JLT’s historical stock price from yahoo finance. It’s amazing! As part of the analysis, you know, we have to do a tremendous amount of work. As a start, I wanted to focus on when to buy and when to sell a stock so that I can make the most profit. For example, I took the data from 19th Dec 2016 to 23rd Dec 2016 as specified above. I did some manual calculation and found that had I bought on 19th Dec 2016 at £961 and sold on 22nd Dec 2016 £988.5, I could make the most profit, £27.5.
I also checked if I had to make the most profit by buying and selling a single JLT share once within 2016 , I could do so by buying on 9th Feb 2016 at £776.5 and selling on 11th Apr 2016 at £1070, making a whopping £293.5 profit! I have not put the data here as one year’s data is too huge to fit here. You can collect and verify it by downloading it as an excel file from the above yahoo link.
Output: Buy on day 1 at £961 and sell on day 4 at £988.5, making £27.5
I also checked the values from 15th Jan 2016 to 21st Jan 2016 (excluding 16th Jan 2016 and 17th Jan 2016 when stock market was closed) and the price looked like the below.
Input: price = [890, 890, 853.5, 828.5, 809]
You can see it kept on dropping and there was no way to make money in this period.
Output: Don’t buy stock
Task: As you realize, as part of the bigger data analysis work that we need to do, it is a small part. We got so much data for hundreds of companies. Hence, it is essential that we do it efficiently. To be precise, I am looking for a solution more time efficient than O(n2).
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