Price: $85.46
Risk management first emerged in scientific and management literature in the 1920s and was formally recognized as a science in the 1950s. Despite the evolution, the fundamental principles based on risk reduction, avoidance, sharing, and retention have largely remained the same. The question remains, can risk management play a more strategic role in guiding tactical investment decisions? We believe it’s high time for the next stage of its evolution.
In our book, we take a data-driven approach to exploring risks instead of being dominated by them. We illustrate how to devise simple yet potent strategies using the following key concepts for investment success:
– Return vs. Risk Duality in a Probabilistic (Non-Deterministic) World
– Context-Dependent Dynamic Asset Allocation vs. Static Allocation
– Statistical Edge, Asymmetric Payoff, and Law of Large Numbers
– Maximizing Return-Risk Ratio by Matching Best-Performing Assets to the Right Risk Environments
We demonstrate how eight investment strategies consistently outperformed the S&P 500 and Nasdaq 100 indexes with higher returns and lower risk, year after year. All of this is supported by verified market data.
How was this method developed? The author, dissatisfied with the traditional tools (forecasting, valuation, chart reading, etc.) that yield little better than a 50-50 success rate even when skillfully used, decided to try a novel approach. This led to the birth of the SMIGRM method, an acronym for the book’s title.
The initial idea was to create an advanced warning system to alert investors of impending stock market crashes well in advance. Through rigorous testing and continual refinement, it has evolved into a powerful tool to guide investment strategies and tactical decisions (market timing). The results speak for themselves.
The author brings over 30 years of financial market experience, managing billion-dollar portfolios on trading desks at international banks from New York to Hong Kong and São Paulo. He has weathered various financial