en Investigating the Effect of Futures Leverage on Constrained Cryptocurrency Portfolios Using Mean-Semi Variance Model and Invasive Weed Optimization Algorithm اقتصاد Economics پژوهشی اصیل - كاربردی Original Research - Empirical <span style="font-size:14pt"><span style="line-height:107%"><span new="" roman="" style="font-family:" times=""><b><span style="font-size:12.0pt"><span style="line-height:107%">Investigating the Effect of Futures Leverage on Constrained Cryptocurrency Portfolios Using Mean-Semi Variance Model and Invasive Weed Optimization Algorithm</span></span></b></span></span></span> <div dir="ltr" style="text-align: justify;"><span style="font-size:12.0pt"><span style="line-height:107%"><span new="" roman="" style="font-family:" times="">In financial markets, a primary concern for investors is achieving enhanced returns while effectively managing portfolio risk. Leveraged trading is one potential strategy for increasing returns; however, the fundamental question is to find the optimal degree of leverage that yields the most efficient investment portfolio. This paper investigates the optimal leverage level of cryptocurrency futures within a diversified portfolio comprising digital assets, employing a constrained mean semi-variance model and the Invasive Weed Optimization (IWO) algorithm. The dataset, sourced from Coin Market Cap, consists of daily returns for 10 cryptocurrencies and 5 futures contracts over the period from 2022 to 2025. The proposed model incorporates allocation constraints, wherein each asset in the portfolio is subject to upper and lower bounds on its weight. Due to the imposed constraints, the problem is not solvable via traditional quadratic programming techniques, necessitating the application of the IWO algorithm as the optimization method. Empirical results reveal that incorporating futures into a cryptocurrency portfolio does not inherently enhance its performance. While leverage may increase expected returns, it simultaneously elevates portfolio risk. Consequently, based on the Sortino ratio, the overall risk-adjusted performance of the portfolio does not necessarily improve with the use of leveraged futures</span></span></span></div> <span style="font-size:12.0pt"><span style="line-height:107%"><span new="" roman="" style="font-family:" times="">In financial markets, a primary concern for investors is achieving enhanced returns while effectively managing portfolio risk. Leveraged trading is one potential strategy for increasing returns; however, the fundamental question is to find the optimal degree of leverage that yields the most efficient investment portfolio. This paper investigates the optimal leverage level of cryptocurrency futures within a diversified portfolio comprising digital assets, employing a constrained mean semi-variance model and the Invasive Weed Optimization (IWO) algorithm. The dataset, sourced from Coin Market Cap, consists of daily returns for 10 cryptocurrencies and 5 futures contracts over the period from 2022 to 2025. The proposed model incorporates allocation constraints, wherein each asset in the portfolio is subject to upper and lower bounds on its weight. Due to the imposed constraints, the problem is not solvable via traditional quadratic programming techniques, necessitating the application of the IWO algorithm as the optimization method. Empirical results reveal that incorporating futures into a cryptocurrency portfolio does not inherently enhance its performance. While leverage may increase expected returns, it simultaneously elevates portfolio risk. Consequently, based on the Sortino ratio, the overall risk-adjusted performance of the portfolio does not necessarily improve with the use of leveraged futures.</span></span></span> Portfolio Optimization, Cryptocurrency Market, Invasive Weed Optimization Algorithm, Mean Semi-Variance, Sortino Ratio Portfolio Optimization, Cryptocurrency Market, Invasive Weed Optimization Algorithm, Mean Semi-Variance, Sortino Ratio 347 361 http://jme.mbri.ac.ir/browse.php?a_code=A-10-659-1&slc_lang=en&sid=1 Majid Afsharirad مجید افشاری راد m.feshari@khu.ac.ir 10031947532846007138 10031947532846007138 Yes Kharazmi University دانشگاه خوارزمی، تهران، ایران Pooria Mazaherifar پوریا مظاهری فر pooriamazaherifar1990@gmail.com 10031947532846007139 10031947532846007139 No Kharazmi University دانشگاه خوارزمی، تهران، ایران