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In a 25 May 2018 Forbes article, Brett Steenbarger interviews David H. Bailey and Marcos Lopez de Prado on the growing crisis of pseudoscience in finance.
Here is an excerpt:
Imagine that a pharmaceutical company develops 1000 drugs and tests these on 1000 groups of volunteer patients. When a few dozen of the tests prove “significant” at the .05 level of chance, those medications are marketed as proven remedies. Believing the “scientific tests”, patients flock to the new wonder drugs, only to find that their conditions become worse as the medications don’t deliver the expected benefit. Some consumers become quite
Continue reading Bailey and Lopez de Prado on the crisis of pseudoscience in finance
Beware snake oil salesmen!
Economics
Bloomberg columnist Mohamed El-Erian recently lamented that the discipline of economics “is divorced from real-world relevance and has lost credibility.” Among the problems he mentions currently afflicting the field are the following:
The proliferation of simplifying assumptions that lead to an “overreliance on excessively abstract estimation techniques and approaches.” Insufficient consideration of the possibility that financial dislocations can disrupt the economy. Poor and grudging adoption of important insights from behavioral science and other disciplines. An oversimplification of uncertainty. An overemphasis of equilibrium conditions and mean reversion, and an underemphasis on structural changes and tipping
Continue reading Economics, finance and pseudoscience
In this post we look at the one plot that proves that technical analysis is useless.
Technical analysis and horoscopes
As volatility has returned in recent months, investors have sought advice from asset managers and other investment professionals. In many instances, such advice includes technical analysis (TA). Even many highly respected investment firms and financial news sources promote TA:
Charles Schwab represents TA as an indispensable tool for active traders (examples: here and here). Merrill Lynch offers a Market Analysis Technical Handbook. Some Bank of America / Merrill Lynch analysts utilize technical analysis: here. Fidelity considers TA an advanced technique
Continue reading The most important plot in finance
Introduction
Two of the most talked-about topics in modern finance are machine learning and quantitative finance. Both of these are addressed in a new book, written by noted financial scholar Marcos Lopez de Prado, entitled Advances in Financial Machine Learning.
In this book, Lopez de Prado strikes a well-aimed karate chop at the naive and often statistically overfit techniques that are so prevalent in the financial world today. But Lopez de Prado does more than just expose the mathematical and statistical sins of the field. Instead, he presents a technically sound roadmap for those who want to do state-of-the-art
Continue reading Advances in Financial Machine Learning
Introduction
Index investing has grown significantly over the past 30 years. Back in 1990, few were even aware of the option for indexing, and options were limited mostly to a handful of conventional mutual funds tracking the U.S. S&P 500 index. In 1993, Boston’s State Street Global Advisors launched the first S&P 500 index-tracking exchanged traded fund (ETF), with ticker SPY. Today this ETF controls over USD$300 billion in assets. Thousands of other index-tracking mutual funds and ETFs, tracking numerous different indices, in numerous different world markets and regions, are now in operation; in the U.S. alone, there were 1716
Continue reading Does indexing threaten the market?
FTSE 100 index
Introduction
Many individual investors employ mutual funds as an alternative to direct ownership of stocks or bonds.
Indeed, mutual funds have some advantages:
Diversity: Even a single fund can encapsulate a large sector of the market. Peace of mind: One is less likely to stress out about sudden bad news regarding a particular firm if one owns shares in it only indirectly as part of a large mutual fund’s portfolio. Management fees: Several leading index mutual funds have even lower management fees than corresponding exchange-traded funds (ETFs). And as a class, mutual funds have significantly lower
Continue reading Can mutual fund investors beat the market?
Hoarfrost: Courtesy Wikimedia
Introduction
The “January effect,” in common with the “Halloween indicator” and “sell in May and go away”, is a catchy, get-rich-quick investment idea adored by financial commentators because it is so easy to explain to unsophisticated readers. It rests on the claim that the U.S. stock market performs better in January, compared to the other months in the year.
Unfortunately, financial reports promoting the “January effect” are often vague and confusing. One recent example is here, which, like others in this genre, lacks a specific actionable investment strategy. In fact, this particular report does not even
Continue reading Can the January effect be exploited in the market?
This site was created out of growing concern with the usage of less-than-fully rigorous mathematical and statistical methodologies in the financial/investment world. One example is the increasing prevalence of backtest overfitting, due in part to the ease of generating large numbers of model variations using modern computer technology. Very few peer-reviewed research papers or commercial products disclose the number of computer trials used in development, so it follows that many published and marketed strategies are statistically bogus. Indeed, such statistical errors are the primary reason that investment funds and strategies, designed for optimal performance based on historical market data, often
Continue reading Overview of the Mathematical Investor
Introduction
“Big data” is already a frequently-heard buzzword, both in the business analytics arena, but also in the field of high-performance scientific computing. Basically, “big data” encompasses the collection, processing, indexing and utilization of large-scale datasets. Some concrete examples include temperature and sunlight data downloaded from satellites monitoring of the Earth’s environment, particle tracking data produced by the Large Hadron Collider in Europe, and anonymized smartphone position data made available, in some cases, by wireless operators and even certain smartphone applications.
Courtesy Quandl, DigitalGlobe and Orbital Insight
Big data has enormous potential to revolutionize the world of finance, mainly
Continue reading How is big data impacting the finance world?
David H. Bailey will join other speakers at the Artificial Intelligence and Data Science: Capital Markets conference, to be held 6-7 December 2017 at the National Museum of the American Indian (NMAI), One Bowling Green, New York City.
According to the conference website,
Complex mathematical modelling has always been part of the data-driven financial world, but today professional money managers are exploring a new range of techniques including machine learning, deep learning and neural networks. They have also become familiar with the relatively new discipline of data science – really an intersection of software engineering, statistical modelling, research analytics,
Continue reading Bailey to speak at AI-Capital Markets Conference in NYC
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