Sampling methods for investment portfolio formulation procedure at increased market volatility

Aim/purpose – In this paper, a market volatility-robust portfolio composition frame- work under the modified Markowitz’s approach with use of sampling methods is developed in order to improve allocation efficiency for financial in- struments formulation procedure at an increased volatility. Design/methodology/approach overcome risk not receiving optimal solution optimization (suboptimal outcomes attribution weights procedures) model, first, implements rationale that markets largely feature two states, i.e., quiescent (non-crisis; low volatility) periods are occasionally interspersed stress (crisis; high and, second, relies on many input samples rates return, either from empirical distribution or theoretical (mitigating estimation risk). All computational results reported publicly available historical daily data sets selected Polish blue-chip securities. Findings Not only did presented method produce more diversified allocation, but also successfully minimized unfavorable effects volatility by providing less risky portfolios comparison Newton’s method, typically used theory. Research implications/limitations The research emphasized get investment it crucial outdo limitations single sample (utilized model) which may some occasions be statistically biased. Thus was proved allow obtain concentrated and volatile contributes decision-making. However, current focused solely particular manner, additional analysis can prepared other jurisdictions asset classes. There considered than variance measures. Originality/value/contribution suggested framework existing wide array quantitative simulation tools composing unique directly addresses task minimizing adverse implications that, consequence, pertains knowledgeable attributing proportions individual institutional investors. hold demanded quality importantly, capacity further development. Keywords: decisions, techniques, selection, statistical methods. JEL Classification: C150, C610, G110.