# busn603 discussion response

Hello,

I need two responses of at least 150 words each for the below students discussions for this week. Also in the bold below are the questions the students at answering.

Instructions:

C.W. Churchman once said that “mathematics tends to lull the unsuspecting into believing that he who thinks elaborately thinks well.” Do you think that the best QA models are the ones that are most elaborate and complex mathematically? Why or why not? (LO 1, 5)

In your responses to others, please review your peer’s posts – do their explanations make sense? Respond accordingly.

Student one:

The attributes of a good quantitative analysis model are low variance to the observed, a relatively lower amount of variables, and a quantitative analysis model that makes sense in general.

In my undergraduate econometrics course, we were assigned to create a quantitative analysis model that calculated the price of a Roman gold coin. The variables that were available were the quality, the rarity, and which Caesar was featured on the coin. Using just the quality and rarity we were able to able to calculate a relatively accurate price compared to the observed data in a linear fashion.

As you add more variables to a quantitative analysis model, the direct correlation or causation of an input variable on a observed variable diminishes. Was it the quality of the coin, the shininess of a coin, the smile of the Caesar on a coin, or the rarity of the coin that makes it worth more? Some of these variables would have no effect on the price of the coin and removing them from your model allows you to focus on the input variables that matter.

When I mentioned a quantitative analysis model that makes sense in general, you need to think about your estimated variable correlated or caused by your input variables. There is a joke, that in the hedge fund world, you see a straight line of growth over multiple years on paper, but someone sells you exponential growth in the near future (Durden, 2019). There are places where an exponential growth model makes sense, such as YouTube video views, and there are times where you expect an input variable to correlate or cause the observed variable in a linear fashion. With better econometric software you can observe multiple variables in a multi-dimensional way.

References:

Durden, T. (Alias) (September 6th, 2019) SoftBank Employees Furious As WeWork Fiasco Could Force Them to Forfeit Pay Retrieved From https://www.zerohedge.com/news/2019-09-06/softbank-employees-furious-wework-fiasco-could-force-them-forfeit-pay

-Christian

Student two:

This week’s power point presentation on Quantitative analysis is a great tool to use in answering the question posed in the forum. It gives a clear understanding of the subject and goes into detail about the topic

Anyway, to answer the question, I do not think that the best Quantitative Analysis models are the ones that are most elaborate and complex mathematically. The best Quantitative analysis models are the instead the ones that are that have data that is accurately calculated. Quantitative factors such as interest rates, inventory levels, and labor cost as well as qualitative factors such as weather and state and federal legislation are all examples of factors that make up a great quantitative analysis. Even though mathematical tools have been utilized for thousands of years, making them complex does not equate to a great QA.

The attributes of a good quantitative analysis model include data that can help predict real-world events (Kenton, 2019). Such QAs do not need to be complex and elaborate mathematically. Simple Mathematical formulas make actually make a quantitative analysis easier to understand the data. The whole point of a QA is to have data that is easy for users to understand. This therefore means that having easy, more understandable methods of prediction will make the material easily read and understood.

This does not mean that one should avoid creating Quantitative Analysis that are complex mathematically, it only means that Quantitative Analysis should not be made complex mathematically for the sole purpose of deeming them the best. Quantitative analysis that are made simply mathematically provide much insight and can also help in detecting the potential errors in those that are complex. The complex ones might not be accurate because of the uncertainty in additional parameters (Zwietering, 2009)

Kenton, W. (2019, April 18). Quantitative Analysis (QA). Retrieved from Investopedia: https://www.investopedia.com/terms/q/quantitativea…

Zwietering, Marcel H. â€œQuantitative Risk Assessment: Is More Complex Always Better?â€ International Journal of Food Microbiology 134.1-2 (2009): 57â€“62. Web

-Fuanyi