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Orientador(es)
Resumo(s)
Despite its popularity, trend-following lacks a cohesive theoretical framework, resulting in
fragmented understanding and application. This thesis addresses this gap by integrating
principles from the Austrian School of Economics to provide a structured foundation for trendfollowing. It posits two key assumptions: the unpredictability of market movements and the
existence of trends, introducing the theorem of the impossibility of accurate market
predictions based on dispersed human knowledge.
Traditional risk-adjusted metrics like the Sharpe, Sortino, and Calmar Ratios have a different
set of limitations. This thesis proposes the Koljonen Ratio, a novel downside risk-adjusted
return metric that combines drawdown and downside volatility for a more nuanced
evaluation, particularly in cryptocurrency markets.
The study aims to: (1) consolidate trend-following philosophy with Austrian economic theory,
(2) develop a superior downside risk-adjusted return metric, (3) assess traditional trendfollowing strategies in cryptocurrency trading, and (4) implement an innovative and
sophisticated trading strategy with a deleveraging mechanism to enhance downside riskadjusted returns.
Anticipated contributions include a robust theoretical framework for trend-following,
improved performance evaluation metrics, practical insights into cryptocurrency trading, and
an advanced strategy for better downside risk-adjusted returns. This thesis aspires to advance
both academic research and practical applications in trading strategies.
Descrição
Dissertation presented as the partial requirement for obtaining a Master's degree in Statistics and Information Management, specialization in Risk Analysis and Management
Palavras-chave
Trend-Following Austrian School of Economics Cryptocurrencies Downside-Risk Algorithmic Trading Koljonen Ratio SDG 1 - No poverty SDG 2 - Zero hunger SDG 4 - Quality education SDG 8 - Decent work and economic growth SDG 10 - Reduced inequalities
