Quantitative Momentum. Vogel Jack R.. Читать онлайн. Newlib. NEWLIB.NET

Автор: Vogel Jack R.
Издательство: John Wiley & Sons Limited
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Жанр произведения: Зарубежная образовательная литература
Год издания: 0
isbn: 9781119237259
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is perhaps surprising that Graham, Malkiel, Buffett, and Klarman would be so dismissive of technical analysis, given what seems to be a rich vein of successful historical practitioners and a stack of academic research that is arguably higher than the research that supports the merits of a fundamental, or value investing, approach. Nevertheless, these fundamental investors' views are reflective of those of many in the value investing community and of fundamental practitioners in general. The value investing religion is alive and well.

THE AGE OF EVIDENCE-BASED INVESTING

      “Avoid extremely intense ideology because it ruins your mind.”

– Charlie Munger, Vice Chairman, Berkshire Hathaway12

      Why did Ben Graham, a data-driven financial economist at heart, have a knee-jerk distrust for technical methods? Perhaps some of this doubt relates to how technical analysis differs from fundamental analysis. For value investors, fundamentals lead, and prices follow, albeit noisily. However, for technical investors, prices lead, and perhaps even drive fundamentals, but fundamentals are not the core driver of stock movements. Moreover, the technician label captures a larger group of the investing public, with a much larger distribution of skills, ranging from the peon to the preeminent. This wider distribution means the average technician tends to be more subjective, less professional, and generally less sophisticated than the average fundamental investor. Thus, one criticism of technical analysis might be that investors are seeking out patterns where no patterns really exist – a reasonable concern, given what we know about human behavior.

      Contrast the technical analyst with the fundamental analyst. The fundamental analyst is looking at concrete data – financial statements – that are based on established conventions. For example, positive net income ratios, ample free cash flow, and low levels of debt can be considered fairly objective measures of good financial health. Additionally, the fundamental analyst must do a lot of hard work to conduct her security analysis: after all, she is trying to identify the present value of all future cash flows from a business and discount them to the present time.

      The fundamental analyst is thus arguably engaged in a more thoughtful and intellectually rigorous pursuit. In this sense, she is perhaps more credible. Buying based on fundamentals seems more reasonable than examining recent price charts with a Ouija board. The technical analyst is assumed to have a simpler job because one can reasonably argue that a history of prices is a limited and simplistic signal, whereas for the fundamental analyst, there is a much wider and deeper array of financial information to digest and consider.

      But in the end, does effort and sophistication really matter? Taking a step back, the mission for long-term active investors is to beat the market. Active investors should focus on the scientific method to address a basic question: What works? Warren Buffett obviously showed that value investing, irrespective of technical considerations, can work. But Stanley Druckenmiller, George Soros, and Paul Tudor Jones also showed that technical analysis can work just as well. An ever-growing body of academic research formalizes the evidence that fundamental strategies (e.g., value and quality) and technical strategies (e.g., momentum and trend-following) both seem to work.13 Many dogmatic investors, however, looking to confirm what they already believe, selectively adopt the research evidence that fits their investing religion. In contrast, an evidence-based investor will conclude that fundamental and technical analysis strategies can work because they are two sides of the same coin. They are cousins – because they share the common objective of exploiting the poor decisions of market participants influenced by biased decision making. As Andrew Lo, an influential and forward-looking financial economist at MIT, correctly observes about the debate between fundamental and technical traders, “In the end we all have the same goal, which is to forecast uncertain market prices. We should be able to learn from each other.”

      We Agree: Less Religion, More Reason

      The debate outlined above is merely the tip of the analysis iceberg and is meant to demonstrate the contentious debates that surround different investment philosophies. And as people become devoted to a particular philosophy, their beliefs often become more firmly established. Thus, while ascertaining the winner in these debates is impossible, one thing is certain: Once an investment strategy has gained a convert, it is nearly impossible to “flip” that convert to another investment religion. But why do these debates necessarily need to be so contentious? Why should value and momentum approaches be mutually exclusive? Indeed, a key aspect of the scientific method is to preserve the freedom to doubt, for without doubt we would cease to explore new ideas. We argue in Chapter 2 that there is an overarching framework for understanding why certain strategies work. We call our framework the sustainable active investing framework. This framework does not seek to identify the best investment strategy, but aims to identify the necessary conditions for any investment strategy to succeed in the future.

DON'T WORRY: THIS BOOK IS ABOUT STOCK-SELECTION MOMENTUM

      In this introductory chapter, we've already discussed technical analysis, fundamental analysis, and psychology. A lot of topics in short order and no mention of how to build a momentum strategy – and we will continue to explore these important topics in the next few chapters. But we want to be clear: this book is about stock-selection momentum. But in order to really understand how to build any active investing strategy, we need context to understand how and why this strategy will presumably work in the future. This discussion will be covered in Chapters 2 through 4. If you are an advanced practitioner, we recommend you skip ahead to Chapter 5 for the cookbook details on how to create what we consider to be an effective active momentum strategy; however, if you want to understand and be successful with the momentum strategy proposed, you will want to read the chapters in the order we present them. Also, we must emphasize that the strategy we outline is not for everyone, primarily because it requires discipline to follow, but more explicitly because the math doesn't add up. From an equilibrium perspective, not everyone can follow our strategy because for every stock we buy, there is a seller on the other side of the trade.

      With that disclaimer out of the way, let's outline what we mean by stock-selection momentum. There is sometimes confusion associated with so-called momentum strategies – we want to clear the muddy waters. We break momentum into two categories to differentiate between the different approaches to measure momentum:

      1. Time-series momentum: Sometimes referred to as absolute momentum, time-series momentum is calculated based on a stock's own past return, considered independently from the returns of other stocks.14

      2. Cross-sectional momentum: Originally referred to as relative strength, before academics developed a more jargon-like term, cross-sectional momentum is a measure of a stock's performance, relative to other stocks.15

      A simple example will illustrate the difference. Consider a hypothetical scenario where we have two stocks in our universe: Apple and Google. Twelve months ago, Apple was $25 per share and Google was also $25 per share. Today, Apple is $100 per share and Google is $50 per share.

      Next, we examine a simple time-series momentum rule and a simple cross-sectional momentum rule.

      The time-series rule will buy a stock that has positive performance over the past 12 months, and will sell a stock if the stock has negative performance. Here is how our time-series momentum-trading rule would treat this scenario:

      • Time-series momentum: Long Apple and long Google because both stocks have strong absolute momentum.

      Our cross-sectional rule will buy a stock if the stock's past performance over the past 12 months is relatively stronger than the past performance of other stocks in the universe (and will sell a stock if it has poor relative performance to other stocks). Here is how our cross-sectional momentum-trading rule would treat this scenario:

      • Cross-sectional momentum: Long


<p>12</p>

Charlie Munger USC Law Commencement Speech, May 2007. www.youtube.com/watch?v=NkLHxMWAZgQ, accessed February 28, 2016.

<p>13</p>

See Wesley Gray and Tobias Carlisle, Quantitative Value: A Practitioner's Guide to Automating Intelligent Investment and Eliminating Behavioral Errors (Hoboken, NJ: John Wiley & Sons, 2012), and Chris Geczy and Mikhail Samonov, “Two Centuries of Price Return Momentum,” Financial Analysts Journal (2016).

<p>15</p>

See Andreas Clenow, “Stocks on the Move: Beating the Market with Hedge Fund Momentum Strategies,” self-published, 2015, for a practitioner perspective, and see Narasimhan Jegadeesh and Sheridan Titman, “Returns to Buying Winners and Selling Losers: Implications for Stock Market Efficiency,” The Journal of Finance 48 (1993): 65–91, for an academic discussion.