Risk & portfolios

Value at risk, volatility targeting, regime models and how diversified strategies are combined into a portfolio.

• 
  An introduction to value at risk

  What value at risk measures and what it does not, the historical, parametric and Monte Carlo methods with a worked example, scaling across horizons, backtesting VaR with exceptions, its theoretical weaknesses, and why banking regulation moved to expected shortfall.

• Choosing your risk: volatility targets, drawdown limits and position sizing

  How systematic strategies decide how much risk to take: volatility targeting, risk budgets, fixed-fractional and Kelly sizing, drawdown limits, leverage and stop-losses, with the assumptions behind each and the ways they fail.

• Combining diversified alpha to deliver a superior Sharpe ratio

  Why several modest, weakly correlated strategies can produce a better risk-adjusted return than one strong strategy: the Sharpe ratio of a combined portfolio, Grinold's fundamental law of active management, risk-based weighting between strategies, and the correlation traps that undo diversification.

• Hidden Markov models for market regimes: an introduction

  An introduction to Markov chains and hidden Markov models for detecting market regimes: transition matrices, emission distributions, the forward algorithm, Baum-Welch estimation and Viterbi decoding, a two-state example, and the pitfalls of using regime probabilities in trading research.