BUS107: Investors Always Think They’re Getting Ripped Off. Here’s Why They’re Right: Quantitative Methods Assignment, SUSS, Singapore

Question 1

Read the article below and answer the questions.

Article 1: Investors Always Think They’re Getting Ripped Off. Here’s Why They’re Right

It’s hard to beat the market, but we keep trying—and believing in—new products that promise to outperform.

Early in January in a Chicago hotel, Campbell Harvey gave a rip-snorting presidential address to the American Finance Association, the world’s leading society for research on financial economics. To get published in journals, he said, there’s a powerful temptation to torture the data until it confesses—that is, to conduct round after round of tests in search of a finding that can be claimed to be statistically significant. Said Harvey, a professor at Duke University’s Fuqua School of Business: “Unfortunately, our standard testing methods are often ill-equipped to answer the questions that we pose.” He exhorted the group: “We are not salespeople. We are scientists!”

The problems Harvey identified in academia are as bad or worse in the investing world. Mass-market products such as exchange-traded funds are being concocted using the same flawed statistical techniques you find in scholarly journals. Most of the empirical research in finance is likely false, Harvey wrote in a paper with a Duke colleague, Yan Liu, in 2014. “This implies that half the financial products (promising outperformance) that companies are selling to clients are false.”

It’s hard to beat the market, but there’s always a new product that tries anyway

Most of us have a vague sense that we’re being ripped off by investment firms that charge hefty fees while producing results that are no better than you’d get throwing darts at a page of stock listings. It’s troubling nonetheless to find out we’re correct. And it’s important to understand the mechanics of what has gone wrong.

The core of the problem is that it’s hard to beat the market, but people keep trying anyway. An abundance of computing power makes it possible to test thousands, even millions, of trading strategies. The standard method is to see how the strategy would have done if it had been used during the ups and downs of the market over, say, the past 20 years. This is called backtesting. As a quality check, the technique is then tested on a separate set of “out of sample” data—i.e., a market history that wasn’t used to create the technique.

With reference to the article above, write your answers with quotes from the article to substantiate your answers.

1. Based on the article above, what do you think are the qualitative and quantitative variables that the financial models will use? Explain their impact on the financial models’ results.

2. If the financial theorist was able to find data for the whole population, do you think the model will be more accurate than using a sample? List down and show if you use a population that will lead to a more accurate model or not.

3. What are the advantages and disadvantages of using statistics? List down 4 advantages disadvantages each, and explain if you agree with the article that statistics, in general, is not accurate.

4. If you were tasked to come up with a new financial model, walk through the whole process of how you would be able to convince other statisticians and financial theorists that your model works or is more accurate than the ones currently found on the market.