The beginning of the year marks the time when chief investment officers, market strategists and other chief prognosticators publish their top investment themes. Barron’s also publishes their much anticipated “round table” issues in mid to late January, which pull together top investors to discuss the state of the markets and where they see investment opportunities.
There are hundreds of firms producing research all the time, most of it free. The big Wall Street firms produce enormous amounts of content, but so do practically all buy-side investment management firms these days. If you’re not careful, combing through research reports for trading and investment ideas can absorb all of the day. There are also the independent firms such as Ned Davis Research, BCA Research and the Leuthold Group, which are very expensive, but provide lots of interesting and useful information for asset class traders.
Common sense suggests that you can’t just read the research, implement the trades suggested and expect to outperform the market. That would be too easy. This is the case even for costly research from the independents, because after all, tens of thousands of professional portfolio managers can afford these services.
For an asset class trader, reading research and market commentary is important, primarily so you understand what everyone else is thinking, become aware of crowded trades and estimate what information is already priced into the markets. Every once in a while, a new piece of information is gleaned or a new way of thinking about an asset class is found. If discovered ahead of most other market participants, this information can be the seed of a new trade.
At any point in time, there are industry thought leaders who seem to have a special knack for investing and trading the markets. When they speak, I pay careful attention because the probability of discovering a new trade idea from them is much higher than reading the everyday, run-of-the-mill content.
Generally, these thought leaders are very experienced, talented and rich. They’re not inhibited by career risk. Their motivations are aligned with us, because being right about an investment theme is the most important goal associated with speaking publically since the prediction is on the record. Contrast this motivation with that of research content providers and newsletter writers, where maximizing readership is the primary goal. (more…)
An essential component of successful trading is having a good sense of timing. The standard industry tool for getting the timing right is technical analysis, so we need to examine its effectiveness. I’ll assume the reader is familiar with technical analysis, and as an asset class trader, I’ll also assume we control a limited amount of assets such that positions can be bought and liquidated with minimal trading impact costs.
For extremely large asset management firms and hedge funds, technical analysis is not an available tool because all-in trading costs are prohibitively expensive with this approach. These firms are forced to use other approaches such as value investing, which is, ironically, a horrible tool for timing price moves. Even large trend following CTAs are forced to use the most liquid futures contracts to minimize trading impact costs. So perhaps being small and using technical analysis is an advantage for us.
In a nutshell, technical analysis is the analysis of price and trading volume patterns to identify current and future price uptrends, downtrends and trend turning points. Practically all trading “how-to” books rely almost exclusively on technical analysis. Technical analysis techniques and patterns appear to be valid on all time scales and with any tradable security.
I gravitated to TA rather quickly when I first started trading, because as a full-time engineer, trading was a hobby. I didn’t have the time or expertise to dig through how the “fundamentals” influenced prices. I read many books on technical analysis and trading. The classic books are still the best,1-4 while most others fail to provide additional insight. In the next few blog posts I’ll talk about technical analysis, trend following and backtesting issues associated with mechanical trading models. Nowadays, I still look at charts and use basic technical analysis, but I don’t expect too much from it. (more…)
In the last blog, I discussed the trading edge associated with predicting investment flows. In this blog, I’ll provide examples using this trading edge to pick outperforming asset classes. Of course, this is a hypothetical exercise with the full benefit of hindsight, and as is often the case, flows may not be the only cause of the observed performance.
1995 to 1999
This era is widely recognized as the culmination of the 1982 to 1999 secular bull market in U.S. equities. As shown in Figure 1, it was a time when retail investors were obsessed with stocks as illustrated by the meteoric rise in CNBC viewership.1 Index investing was also becoming very popular, but at that time indexing solely meant investing in the S&P 500. Mutual fund managers were the investment stars of the era.
Figure 1. CNBC viewership history.1
Figure 2 from Ned Davis Research shows equity mutual fund net flows as a percentage of U.S. market capitalization from 1960 to present.2 These flows can be attributed primarily to retail investors, who throughout the 1990s powered a strong equity bull market. (more…)
In a nutshell, I want to own securities held by asset classes receiving large inflows of cash over an intermediate 6 to 12 month time scale, and avoid asset classes facing large intermediate-to-long term outflows.
Large intermediate-term inflows create essentially continuous daily net-demand that tends to bid up the price of the associated securities over time. Outflows do the opposite. We want to jump ahead of the buying and selling as long as the flows are significant and expected to continue over time. Inflows leading to outperformance can also be self-reinforcing as many investors are susceptible to performance chasing (flows lead to more flows).
Who’s on the other side of this trade? Long-term flows tend to be strategic allocation decisions made by large institutional investors, foreign investors, investment advisors/brokers and retail investors, in a manner that is typically price-insensitive. Nowadays the vast majority of investors spend their time deciding what investment manager to hire rather than what securities to purchase. When fund managers receive new money, they tend to buy what they already own. Not all funds do this, but most do, and index funds in particular must buy securities in exact proportion to the current portfolio.
While there are many excellent and talented investors in all the above groups, allocation decisions tend to be herd-like and heavily correlated with each other. These allocation waves can last for years as hundreds of institutional investors, millions of advisors/brokers and tens of millions of retail investors implement the latest fashionable portfolio allocation approach. The faster an asset class trader can jump on these trends, the more profitable this edge may become. (more…)
Providing liquidity to motivated buyers and sellers has worked throughout history. It’s an enduring trading edge that I expect to work forever – both in and out of the trading arena. In life, a person highly motivated to purchase a specific house, a specific car or the latest consumer gadget pays a price that’s higher than a reasonable substitute. A person forced to sell a house will likely concede a not-so-small financial penalty because of the need to sell immediately.
Consistently being a motivated buyer of things will act as a drag on the personal balance sheet. Taking advantage of sales or the occasional motivated seller provides a little alpha in the growth of personal wealth.
Similar opportunities occur in the financial markets. With respect to the motivated buying/selling (MB/MS) edge, we’re searching for moments in time when the price action is affected by a large amount of buying/selling that is price-insensitive AND is occurring due to reasons unrelated to enhancing portfolio risk-adjusted returns.
We distinguish MB/MS from everyday price volatility by understanding the motivations and techniques used by other market participants, and identifying instances when a price is perhaps being pushed away from equilibrium value for non-economic reasons. We sell into the price strength or buy into price weakness created by the MB/MS and then wait for prices to snap back when done.
This trading edge takes experience and educated guesswork. You might ask if there’s too much competition in this space from market makers, Wall Street trading desks, high frequency traders, statistical arbitrage hedge funds and others. The answer is absolutely yes, and I’m not asking you to compete with these pros. The goal is to be on the lookout for when market makers and other arbs need some help pushing prices back to the equilibrium value. (more…)
In a previous blog I discussed the efficient market hypothesis (EMH), which can be summed up with the following statement by recent Nobel Prize winner Eugene Fama.
An efficient capital market is one in which security prices fully reflect all available information.1
I presented the following three arguments in favor of pragmatically adopting an efficient markets view when investing.
- The logic of hyper-competition in a fair trading arena – any trading edge will quickly attract competition and be arbitraged away.
- The mathematical fact that investors as a whole cannot beat the market, and since professional investors manage the majority of assets, aggregate professional alpha must be close to zero before fees.
- While acknowledging that there can be long-term skilled winners, the empirical evidence suggests it’s very difficult to distinguish luck and skill when evaluating past performance, even when judging your own trading ability.
In this blog I’ll go one level deeper to discuss the fundamental foundations for an efficient market. Why review these? Mainly to develop a better understanding of “the enemy,” and to identify weaknesses in the EMH assumptions that may lead to trading edges. Rather than argue about whether a market is efficient, let’s search for nuanced moments in time and securities-space when the EMH assumptions may not hold – leading to an exploitable trading edge for us. (more…)