Volume 1 of "The Strategic Analysis of Financial Markets," — Framework, is premised on the belief that markets can be understood only by dropping the assumptions of rationality and efficient markets in their extreme forms, and showing that markets still have an inherent order and inherent logic. But that order results primarily from the "predictable irrationality" of investors, as well as from people's uncoordinated attempts to profit. The market patterns that result do not rely on rationality or efficiency. A framework is developed for understanding financial markets using a combination of psychology, statistics, game and gambling analysis, market history and the author's experience. It expresses analytically how professional investors and traders think about markets — as games in which other participants employ inferior, partially predictable strategies. Those strategies' interactions can be toxic and lead to booms, bubbles, busts and crashes, or can be less dramatic, leading to various patterns that are mistakenly called "market inefficiencies" and "stylized facts." A logical case is constructed, starting from two foundations, the psychology of human decision making and the "Fundamental Laws of Gambling." Applying the Fundamental Laws to trading leads to the idea of "gambling rationality" (grationality), replacing the efficient market's concept of "rationality." By classifying things that are likely to have semi-predictable price impacts (price "distorters"), one can identify, explore through data analysis, and create winning trading ideas and systems. A structured way of doing all this is proposed: the six-step "Strategic Analysis of Market Method." Examples are given in this and Volume 2. Volume 2 of "The Strategic Analysis of Financial Markets" — Trading System Analytics, continues the development of Volume 1 by introducing tools and techniques for developing trading systems and by illustrating them using real markets. The difference between these two Volumes and the rest of the literature is its rigor. It describes trading as a form of gambling that when properly executed, is quite logical, and is well known to professional gamblers and analytical traders. But even those elites might be surprised at the extent to which quantitative methods have been justified and applied, including a life cycle theory of trading systems. Apart from a few sections that develop background material, Volume 2 creates from scratch a trading system for Eurodollar futures using principles of the Strategic Analysis of Markets Method (SAMM), a principled, step-by-step approach to developing profitable trading systems. It has an entire Chapter on mechanical methods for testing and improvement of trading systems, which transcends the rather unstructured and unsatisfactory "backtesting" literature. It presents a breakout trend following system developed using factor models. It also presents a specific pairs trading system, and discusses its life cycle from an early, highly profitable period to its eventual demise. Recent developments in momentum trading and suggestions on improvements are also discussed.

Volume 2 of "The Strategic Analysis of Financial Markets"--Trading System Analytics, continues the development of Volume 1 by introducing tools and techniques for developing trading systems and by illustrating them using real markets. The difference between these two Volumes and the rest of the literature is its rigor. It describes trading as a form of gambling that when properly executed, is quite logical, and is well known to professional gamblers and analytical traders. But even those elites might be surprised at the extent to which quantitative methods have been justified and applied, including a life cycle theory of trading systems. Apart from a few sections that develop background material, Volume 2 creates from scratch a trading system for Eurodollar futures using principles of the Strategic Analysis of Markets Method (SAMM), a principled, step-by-step approach to developing profitable trading systems. It has an entire Chapter on mechanical methods for testing and improvement of trading systems, which transcends the rather unstructured and unsatisfactory "backtesting" literature. It presents a breakout trend following system developed using factor models. It also presents a specific pairs trading system, and discusses its life cycle from an early, highly profitable period to its eventual demise. Recent developments in momentum trading and suggestions on improvements are also discussed."--Publisher's website.

Volume 1 of ""The Strategic Analysis of Financial Markets,"" - Framework, is premised on the belief that markets can be understood only by dropping the assumptions of rationality and efficient markets in their extreme forms, and showing that markets still have an inherent order and inherent logic. But that order results primarily from the ""predictable irrationality"" of investors, as well as from people's uncoordinated attempts to profit. The market patterns that result do not rely on rationality or efficiency. A framework is developed for understanding financial markets using a combination of psychology, statistics, game and gambling analysis, market history and the author's experience. It expresses analytically how professional investors and traders think about markets - as games in which other participants employ inferior, partially predictable strategies. Those strategies' interactions can be toxic and lead to booms, bubbles, busts and crashes, or can be less dramatic, leading to various patterns that are mistakenly called ""market inefficiencies"" and ""stylized facts."" A logical case is constructed, starting from two foundations, the psychology of human decision making and the ""Fundamental Laws of Gambling."" Applying the Fundamental Laws to trading leads to the idea of ""gambling rationality"" (grationality), replacing the efficient market's concept of ""rationality."" By classifying things that are likely to have semi-predictable price impacts (price ""distorters""), one can identify, explore through data analysis, and create winning trading ideas and systems. A structured way of doing all this is proposed: the six-step ""Strategic Analysis of Market Method."" Examples are given in this and Volume 2. Volume 2 of ""The Strategic Analysis of Financial Markets"" - Trading System Analytics, continues the development of Volume 1 by introducing tools and techniques for developing trading systems and by illustrating them using real markets. The difference between these two Volumes and the rest of the literature is its rigor. It describes trading as a form of gambling that when properly executed, is quite logical, and is well known to professional gamblers and analytical traders. But even those elites might be surprised at the extent to which quantitative methods have been justified and applied, including a life cycle theory of trading systems. Apart from a few sections that develop background material, Volume 2 creates from scratch a trading system for Eurodollar futures using principles of the Strategic Analysis of Markets Method (SAMM), a principled, step-by-step approach to developing profitable trading systems. It has an entire Chapter on mechanical methods for testing and improvement of trading systems, which transcends the rather unstructured and unsatisfactory ""backtesting"" literature. It presents a breakout trend following system developed using factor models. It also presents a specific pairs trading system, and discusses its life cycle from an early, highly profitable period to its eventual demise. Recent developments in momentum trading and suggestions on improvements are also discussed.

This book presents studies of stock market crashes big and small that occur from bubbles bursting or other reasons. By a bubble we mean that prices are rising just because they are rising and that prices exceed fundamental values. A bubble can be a large rise in prices followed by a steep fall. The focus is on determining if a bubble actually exists, on models to predict stock market declines in bubble-like markets and exit strategies from these bubble-like markets. We list historical great bubbles of various markets over hundreds of years. We present four models that have been successful in predicting large stock market declines of ten percent plus that average about minus twenty-five percent. The bond stock earnings yield difference model was based on the 1987 US crash where the S&P 500 futures fell 29% in one day. The model is based on earnings yields relative to interest rates. When interest rates become too high relative to earnings, there almost always is a decline in four to twelve months. The initial out of sample test was on the Japanese stock market from 1948-88. There all twelve danger signals produced correct decline signals. But there were eight other ten percent plus declines that occurred for other reasons. Then the model called the 1990 Japan huge -56% decline. We show various later applications of the model to US stock declines such as in 2000 and 2007 and to the Chinese stock market. We also compare the model with high price earnings decline predictions over a sixty year period in the US. We show that over twenty year periods that have high returns they all start with low price earnings ratios and end with high ratios. High price earnings models have predictive value and the BSEYD models predict even better. Other large decline prediction models are call option prices exceeding put prices, Warren Buffett's value of the stock market to the value of the economy adjusted using BSEYD ideas and the value of Sotheby's stock. Investors expect more declines than actually occur. We present research on the positive effects of FOMC meetings and small cap dominance with Democratic Presidents. Marty Zweig was a wall street legend while he was alive. We discuss his methods for stock market predictability using momentum and FED actions. These helped him become the leading analyst and we show that his ideas still give useful predictions in 2016-2017. We study small declines in the five to fifteen percent range that are either not expected or are expected but when is not clear. For these we present methods to deal with these situations. The last four January-February 2016, Brexit, Trump and French elections are analzyed using simple volatility-S&P 500 graphs. Another very important issue is can you exit bubble-like markets at favorable prices. We use a stopping rule model that gives very good exit results. This is applied successfully to Apple computer stock in 2012, the Nasdaq 100 in 2000, the Japanese stock and golf course membership prices, the US stock market in 1929 and 1987 and other markets. We also show how to incorporate predictive models into stochastic investment models. Contents: IntroductionDiscovery of the Bond–Stock Earnings Yield Differential ModelPrediction of the 2007–2009 Stock Market Crashes in the US, China and IcelandThe High Price–Earnings Stock Market Danger Approach of Campbell and Shiller versus the BSEYD ModelOther Prediction Models for the Big Crashes Averaging –25%Effect of Fed Meetings and Small-Cap DominanceUsing Zweig's Monetary and Momentum Models in the Modern EraAnalysis and Possible Prediction of Declines in the –5% to –15% RangeA Stopping Rule Model for Exiting Bubble-like Markets with ApplicationsA Simple Procedure to Incorporate Predictive Models in Stochastic Investment Models

This book provides a comprehensive overview of the emerging field of cultural finance. It summarizes research results of cultural differences in financial decision making and financial markets. Many of the results have been published in leading academic journals over the last ten years but some are presented here for the first time. The book is based on an international survey on risk and time preferences — the INTRA study, conducted in 53 countries worldwide. Applications to financial markets include the equity premium puzzle, the value premium, dividend payout policies and asset allocations.