In January last year, Reuters polled 1,000 oil market experts who basically agreed that oil would remain anchored in the $65-$70/bbl range through 2023. Only 3% of these experts thought that oil might rise to $90/bbl or more in 2020. I posted my analysis at this link: Market Fundamentals and Forecasting Groupthink. Later that year I published my own analysis, “Next Move in Oil Prices: $5-$10 Lower,” concluding that, …oil price will likely see another leg down… with Brent falling toward high $40s and WTI toward low $40s. Continue reading
Category Archives: Behavioral finance
Do trend followers move markets? (they do).
A few months ago, when reviewing our trades on US Treasury futures, I was so delighted, I drafted a bragging article titled “How we knew yields would collapse?” summarizing the results of our trading. That performance was entirely generated by my I-System model, first built in 1999. I still find myself awestruck that this works… We generated profitable trades through both the bear and the bull market in bonds, literally without needing to know a single thing about the market fundamentals. The trades were strictly based on the knowledge framework built into the system more than 20 years ago (by the way, our strategies are still generating excellent signals in those same markets). Continue reading
Failure of price forecasting: the unit of account conundrum
In addition to the better understood challenges of market analysis, like access to timely and accurate data, there is another – rather massive, but usually completely ignored – problem that renders forecasting largely an exercise in futility.
Over the years I’ve written quite a bit on the unreliable nature of price forecasts based on the analysis of market supply and demand . Most recently, in “Market fundamentals, forecasting and the groupthink effect,” I discussed the problem of data quality as well as the very real problem of groupthink among leading analysts, providing an example of a staggeringly wrong oil price forecast they produced. Some of the very same experts later produced this gem: Continue reading
Trend following might save your tail
In the age of central bank quantitative easing, trend following has become an unpopular investment strategy, even earning tiself a bad name as trend following funds performed miserably compared to bonds, equities, and passive index funds. Below is a chart put together by AutumnGold showing a growing gap between Managed Futures funds the S&P 500 and Barclay’s Aggregate Bond index. Managed futures funds are a good proxy for trend following performance as most of them apply systematic trend following strategies in one way or another.
Lessons Of Japan’s 1980s Bull Market
Afer popping, Japan’s 1980s bull market gave way to an 82% drop over the following 20 years.
Three decades later, Japanes equities are still more than 40% below peak valuations.
One of the most effective methods of navigating the boom/bust cycles has been the systematic trend following.
Sooner or later a crash is coming, and it may be terrific
Roger Babson, 5 Sep. 1929
If everybody indexed, the only word you could use is chaos, catastrophe. The markets would fail
Jack Bogle, founder of The Vanguard Group
As of December 2018, passive index funds controlled 17.2% of the stock of all U.S. publicly traded companies, up from only 3.5% in 2000. The 5-fold increase was in part the consequence of the ongoing stock market growth, which now has the distinction of being the longest running bull market ever recorded. Buoyed in large part by central banks’ unprecedented quantitative easing (QE) programs, the rising stocks have lulled many investors into complacency.
On model risk in quantitative trading
- Quantitative strategies have become increasingly popular in trading and investing
- The experience with using them has been mixed, largely as a result of three categories of problems
- Still, quantitative approach is well worth exploring and offers important advantages to their users
Over the past few years, the use of quantitative strategies has become increasingly popular in trading and investment management. According to JPMorgan, passive and quantitative investors now account for 60% of equity assets under management (vs. 30% ten years ago) and only about 10% of trading volumes originate from fundamental discretionary traders.[1] Appealing new buzzwords like, robo-advising, artificial intelligence and machine learning stoked the imagination of many investors and boosted the quantitative trading gold rush. Continue reading
Lessons in asset valuation: the great warrants bubble of China
Investors exert a great deal of intellectual effort to determine the correct valuation of securities. Economic value is central to our decision making and it plays a major role in our intuitive psyche. In daily life, when we buy a loaf of bread or a tank of gasoline, we tend to have a good idea about what we think is cheap and what’s expensive. We like bargains, don’t enjoy being ripped off, and in the same way we’re inclined to shop for value as consumers, we find value investing intuitively appealing. But here’s the critical difference between buying goods and investing: shopping for investments is speculative while buying stuff isn’t, and speculation activates the part of our mental circuitry that can heat up to a boiling point and overwhelm any rational consideration of value. Continue reading
Of Bitcoins and bubbles
In my book, “Mastering Uncertainty in Commodities Trading” I argued that security prices “are driven by human psychology and its self-stoking collective action that can sustain major trends spanning many years.” That’s because in speculative decision making, our views about the actions of others can entirely override our rational appraisal of the underlying asset value.
The most recent example of this is the price of Bitcoin that has surged from below $400 in January last year to $4,300 this week. When we set up the Altana Digital Currency Fund several years ago, many people thought that digital currencies were just a strange fad and investors continued to show little interest in them – until very recently. Continue reading
Speculation in the natural world
Nature has … some sort of arithmetical-geometrical coordinate system, because nature has all kinds of models. What we experience of nature is in models, and all of nature’s models are so beautiful. – R. Buckminster Fuller
Nature’s survival strategies that bear the most similarities to activities of market speculators are those of predators. To live, predators must hunt and this activity includes elements of speculation. Like trading, predation requires knowledge, skills, judgment and decision-making. It also entails risk and uncertainty. A predator can’t be sure where her next meal is coming from. Each hunt is an investment of resources; it involves the risk of injury and loss of energy expended in failed hunts, which tend to be more frequent than successful ones. To survive and procreate, predators must consistently generate a positive return on this investment. Too much of a losing streak could turn out to be fatal. In his book, “The Serengeti Lion: A Study of Predator-Prey Relations” George B. Schaller painstakingly documented the details of hundreds of hunts by large cats in the Serengeti National Park in Tanzania. We have all seen wildlife television programs showing lions and cheetahs hunting, but Schaller’s work offers a much richer account of the life of predatory cats including their hunting behavior.
The anatomy of a hunt Continue reading
The illusion of expertise in financial markets
Participants in financial markets have to deal with uncertainty on a daily basis. Their need to research and understand markets has given rise to a massive industry delivering security prices, reports and expert analyses to traders and investors seeking to make sense of the markets and predict how they might unfold in the future.
The need to understand stuff is innate to our psychology: when something happens, we almost reflexively want to know why it happened. But the compulsion to pair an effect with its cause sometimes gets us jumping to conclusions. If such conclusions turn out to be mistaken or irrelevant, they could prove useless – or something worse. Consider two recent titles from the ZeroHedge blog, published 89 minutes apart: Continue reading
The Naked Hedgie 