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Supplementary matlab code for the paper Modeling asset allocations and a new portfolio performance score, Digital Finance, Springer 2021.

  • Installation

To install the dependencies, set the working space to the root of this repository and run

install
  • Execution of the code

To run the code, the main function is compute_scores. The inputs of the function are:

  1. sigma: The estimation of the covariance matrix of the distribution of the assets' returns.
  2. mu: The estimation of the mean of the distribution of the assets' returns.
  3. asset_returns: The vector of the assets' returns to evaluate the performance of the portfolio.
  4. Ptf: The portfolio to evaluate its performance.
  5. num_risk_levels: The number of levels of risk of the allocation strategies in the stock market.
  6. num_dispersion_levels: The number of levels of dispersion for each level of risk of the allocation strategies in the stock market.
  7. risk_behavioral_function: The behavioral function for the risk of the allocation strategies.
  8. dispersion_behavioral_function: The behavioral function for the dispersion of each risk level.

The outputs of the function are:

  1. parametric_score: The parametric score of the input portfolio.
  2. Ws: The sequence of weight vectors corresponding to each score in the vector of parametric score.
  3. bias_vector: The bias vector computed by the input behavioral functions.
  4. mean_score: The mean score.
  5. a_sequence: The sequence of the parameters that control the level of dispersion for each risk level.
  6. q_sequence: The sequence of the parameters that control the level of risk of the allocation strategies.
  7. volatility_sequence: The sequence of portfolio volatilities corresponding to the q_sequence.

You can also see the code in the script example.