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Über dieses Buch

This compelling book examines the price-based revolution in investing, showing how research over recent decades has reinvented technical analysis. The authors discuss the major groups of price-based strategies, considering their theoretical motivation, individual and combined implementation, and back-tested results when applied to investment across country stock markets. Containing a comprehensive sample of performance data, taken from 24 major developed markets around the world and ranging over the last 25 years, the authors construct practical portfolios and display their performance—ensuring the book is not only academically rigorous, but practically applicable too. This is a highly useful volume that will be of relevance to researchers and students working in the field of price-based investing, as well as individual investors, fund pickers, market analysts, fund managers, pension fund consultants, hedge fund portfolio managers, endowment chief investment officers, futures traders, and family office investors.



Chapter 1. Data, Portfolios, and Performance: How We Test the Strategies

In this chapter, the authors reviewed the methods, then tested and implemented particular strategies. They presented the data sources and explained how they had prepared the samples. Having demonstrated how they had formed the portfolios and implemented the strategies, the authors specified both the methods and indicators used to evaluate the strategies.
Adam Zaremba, Jacob “Koby” Shemer

Chapter 2. The Trend Is Your Friend: Momentum Investing

Momentum is defined as the tendency of securities with good (poor) past performance to overperform (underperform) in the future. It is one of the most pervasive anomalies ever discovered and evidenced across numerous asset classes. In this chapter, the authors reviewed diverse momentum techniques and their variations, presenting potential improvements: volatility scaling, timing the momentum crashes, time-series and intermediate versions of momentum, a trend range, and the 52-week high strategies. They provided theoretical explanations and surveyed rich empirical evidence of momentum profitability, testing three momentum-based strategies across 24 international equity markets.
Adam Zaremba, Jacob “Koby” Shemer

Chapter 3. Trees Do Not Grow to the Sky: Reversals in a Stock Market

While the momentum strategy assumes the continuation of the price movement, the reversal strategies rely on a contrary assumption: predicting the price trend to revert. How can both the phenomena coexist? The solution is the investment horizon. While the momentum effect arises in the mid-term (3–12 months), the reversal occurs either in the short term (1 month) or in the long term (3–5 years). This chapter thoroughly discusses both the sources and implementation of reversal strategies in financial markets. The authors also showcased various improvements to the reversal strategies providing vast theoretical and empirical evidence in their support. Finally, they individually tested the reversal techniques across 24 different equity markets.
Adam Zaremba, Jacob “Koby” Shemer

Chapter 4. No Pain, No Gain? The Puzzle of Risk-Return Relationship

The relationship between risk and return in finance seems controversial. While the crucial implication of the standard models dictates—the higher the risk, the higher the expected return—the empirical evidence seems to contradict this expectation. Emerging evidence has proven that the standard measures of realized risk, including volatility or systematic risk, negatively predict abnormal returns. Surprisingly, some other measures related to tail risk or downside risk have proven as positive predictors of performance. Importantly, all the measures might help investors to predict abnormal returns. In this chapter, the authors carefully reviewed the risk-based return-predictive signals along with their theoretical and empirical evidence and conducted thorough tests of example strategies across 24 international equity markets.
Adam Zaremba, Jacob “Koby” Shemer

Chapter 5. Are Stocks Lotteries? The Shape of Distribution Matters

As shown by studies, the shape of return distributions can also predict future returns. Investors, to some extent, treat stocks as lotteries that can reward them with a substantial fortune. In consequence, the right-skewed distributions, where there is a large chance of exceptionally high returns, tend to disappoint in the end. The impact of skewness can be measured in various ways: from very sophisticated measures, like co-skewness or idiosyncratic skewness, to plain and simple ones, like maximum daily return over the previous month. All of these measures can serve as powerful predictors of future returns. The authors reviewed the skewness-based strategies, providing both explanations and evidence, and re-examined them in 24 international equity markets.
Adam Zaremba, Jacob “Koby” Shemer

Chapter 6. Januaries, Mays, and Lunar Cycles: Stock Selection with Seasonal Anomalies

Seeking seasonal regularities in the stock market is as old as the art of investment analysis. January seasonality and “sell in May and go away” are patterns known to any stock market investor. While popular, they still remain extremely controversial. For a long time, the seasonal anomalies belonged to the most “magical” tools of technical analysis. Nonetheless, the recent research has completely changed the picture as many of the seasonal anomalies could be captured by the so-called cross-sectional seasonality—the foundation of all seasonal anomalies. In short, the cross-sectional seasonality is the tendency of the stocks which in the same calendar month in the past performed well (poorly) on average to continue to outperform (underperform) in the following year. Following these considerations in this chapter, the authors reviewed the seasonal anomalies and re-examined the performance of strategies based on cross-sectional seasonality in 24 international stock markets.
Adam Zaremba, Jacob “Koby” Shemer

Chapter 7. Predicting Prices Based on… Prices? The Role of Nominal Prices

Can we predict returns based on… raw prices? Does the nominal price forecast future performance? Is it better to invest in low- or high-priced stocks? The relevant evidence seems conflicting. In this chapter, the authors reviewed the evidence and re-examined the nominal-price investing analyzing multiple countries.
Adam Zaremba, Jacob “Koby” Shemer

Chapter 8. To Time or Not to Time? Tactical Allocation Across Strategies

In this final chapter, the authors presented how to build an efficient portfolio of price-based strategies. The chapter not only presents the benefits of extensive diversification but also uncovers the possibilities of timing and tactical asset allocation. Momentum, cross-sectional seasonality, and value investing are still powerful, robust, and pervasive investment techniques working across multiple asset classes. Interestingly, the recent academic studies have shown them to work also at the meta-level: across investment strategies. In other words, it is possible to time price-based strategies based on their various characteristics stemming from the past returns. In the chapter, the authors reviewed these methods and showed how they could be efficiently used to form portfolios of strategies.
Adam Zaremba, Jacob “Koby” Shemer

Chapter 9. Conclusions

Recent academic research has rekindled the interest in studying investment techniques based purely on prices. These modern approaches could be broadly described as a new perspective on technical analysis. They offer investors a number of quantitative tools helping to select the best performing securities. In this book we have collected, reviewed, and replicated investment strategies based on the simplest possible variable: price. All of them could be effectively employed across multiple equity markets.
Adam Zaremba, Jacob “Koby” Shemer


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