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One of us (Marcos Lopez de Prado) has been interviewed on the topic of educational training in the finance field by Institutional Investor. A brief synopsis of this interview is below. The full article is HERE.
How Universities Are Failing Finance Students
With investment shops fighting over mathematicians and engineers, a Guggenheim executive argues that finance degrees and departments “face irrelevancy.”
Synopsis: In an “Invited Editorial Comment,” in Institutional Investor, Marcos López de Prado takes higher finance education and academic research to task for operating in a vacuum outside the pragmatic world of industry. Holder of a couple of PhDs
Continue reading How universities are failing finance students
Many now accept that artificial intelligence, robotics and other high-tech developments will upend blue-collar professions such as retail sales, truck driving, package delivery, fast food and more. Some observers now estimate that self-driving vehicles could replace 1.7 million truckers in the next decade. Drivers of delivery vehicles could see their jobs replaced by Amazon drones.
But what about finance, the epitome of white collar employment? Far from being immune, white collar occupations in general, and finance in particular, are arguably even more prone to be substantially affected. Entire categories of highly-paid workers could be rendered obsolete in a matter of
Continue reading Will artificial intelligence upend the financial world?
Are workers saving enough?
As we emphasized in a 2014 Mathematical Investor blog, individual investors are not very well equipped, and certainly not very effective, in managing their own investment savings. They chronically fail to save enough, and very often mismanage what they do save.
This is unfortunate, because fewer workers than in the past, particularly in the U.S., are covered by a “defined-benefit” retirement system (pension). Instead, a growing fraction of workers rely on 401(k) systems or the equivalent, where they optionally contribute to an investment fund that they have either partial or full discretion to manage. More than
Continue reading Poor investor performance: What can be done?
Charts
Examining charts is a long-standing fixture of modern finance. For example, we have all seen “scary charts”, which often spread like viruses. One example is the following (first chart). But as Matthew O’Brien pointed out, the scary parallel pretty much disappears if one scales the two charts properly (second chart):
Technical analysis
Charting typically goes hand-in-hand with “technical analysis,” namely the usage of relatively unsophisticated analysis schemes, typically computed from high-level statistics on stock market data. The field has its own terminology, as exemplified for example by a recent report in the Concord Register: parabolic stop and reverse
Continue reading Charts and technical analysis: Do they work?
We have learned that two of our MAFFIA group (Bailey and Lopez de Prado), together with Jonathan Borwein (posthumously) and Amir Salehipour, were awarded the “Silver Bullet” award (from the “Dash of Insight” group) for our article “Evaluation and ranking of market forecasters.”
See the entry for 5/20/2017 HERE.
(Only Bailey’s name was listed at the above URL, but all authors should be equally credited.)
Our preprint manuscript is available HERE.
Introduction
The last few years have been difficult times for hedge funds. For the majority of these funds, performance has lagged market averages, certainly not in keeping with the exalted fees charged by the fund managers. For example, as of 1 July 2017, the HFRI Fund Weighted Composite Index is up 3.28% year-to-date, and 4.79% annualized gain for the previous 5 years. The corresponding figures for the S&P500 Index (including dividends) are 9.34% and 13.6%.
These chronic performance shortfalls have led many clients to rethink their hedge fund investments. In 2014, the California Public Employees’ Retirement System (CalPERS), the largest
Continue reading Which hedge funds actually beat the market?
The folly of panic selling and market timing
A recent DALBAR study found that over a 30-year period, the average self-directed equity mutual fund investor earned only 3.7 percent, compared with 10.3 percent that could be obtained by simply investing in a S&P500 index fund. Much of this huge shortfall is due to panic selling during market downturns, or attempts to time the market.
A typical scenario is that in the midst of a market downturn, investors panic and sell out, with the intent of waiting for the market to “bottom out” before reinvesting. Some investors believe that they can
Continue reading Gender, marital status and investment performance
Optimistic and pessimistic forecasters
Many investors, individual as well as institutional, rely on market experts and forecasters when making investment decisions. Needless to say, some of these forecasts tend to be more accurate than others. How can one decide which of these forecasts, if any, to take seriously?
Some of these forecasts are optimistic. For example, on 3 January 2015 Thomas Lee predicted that the S&P 500 index would be at 2325 one year hence. (The S&P 500 ranged between 1867 and 2122 during this period, closing at 2012 on 4 January 2016, well short of the goal.)
Some are
Continue reading How accurate are market forecasters?
Warren Buffett, the Chairman of Berkshire Hathaway since 1970, sometimes called the “oracle of Omaha,” is arguably the world’s most successful stock-picking investor. Under his leadership Berkshire Hathaway has grown to a financial powerhouse, with total market capitalization of approximately USD$420 billion. Buffett has certainly shared in this success — as of this writing (27 February 2017), Buffett’s net worth was USD$76.5 billion, making him the second wealthiest person in the world.
So what advice does Buffett have for the rest of us mere mortals, individual investors as well as institutional investors?
His answer is quite arresting: Invest mainly in
Continue reading Investment advice from the world’s most successful stock picker
Introduction
In the past few years “smart beta” (also known as “alternative beta” or “strategic beta”) investments have grown rapidly in popularity. As of the current date (January 2017), assets in these investment categories have grown to over USD$500 billion, and are expected to reach USD$1 trillion by 2020. More than 844 exchange-traded funds employing a smart beta strategy are now in operation.
The basic idea behind smart beta is to observe that traditional capitalization-weighted investments (such as S&P 500 index funds) tend to be heavily weighted in favor of securities from large, stable firms. Thus the smart beta community
Continue reading Backtest overfitting in smart beta investments
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