Portfolio Optimization Theory Research Articles

A Heuristic Model to Find Optimal or Realistic Target Industry Sectors

Policymakers or prospective investors recognize a continuing need to find target industry sectors to expand or contract for a sustainably healthy economy or investment portfolios. This paper discusses how to apply an optimal portfolio theory to selecting target industry sectors. With the information technology and the analytical approach in mind, this paper provides an operational and workable framework for selecting target industry sectors for an economy. The application incorporates the capital asset pricing model, ways to find excess return to risk ratios, unsystematic risk measures, etc. First, this paper shows a practical approach to finding the optimal weights for target industry sectors. Second, this paper develops a heuristic framework for analyzing the performance of industry sectors to construct realistic mixes of industry sectors.

Theoretical Foundations and Implications of Neural Ordinary Differential Equations (Nodes) For Real-Time Portfolio Optimization

This paper embarks on a comprehensive exploration of the theoretical landscape surrounding the integration of Neural Ordinary Differential Equations (NODEs) into the domain of real-time portfolio optimization. The study commences by establishing the background and motivation for this research, shedding light on the challenges encountered in real-time portfolio management and the potential transformative role NODEs can play in addressing these challenges. The theoretical framework unfolds in a structured manner, encompassing critical facets of portfolio optimization theory. It delves into classical portfolio optimization methodologies, including the mean- variance framework and continuous-time stochastic control techniques. This solid theoretical foundation provides the basis for understanding the nuances of optimizing portfolio weights, expected returns, and risk measures. The heart of the research lies in the integration of NODEs, an innovative fusion of deep learning and differential equations, into the fabric of portfolio optimization. NODEs, with their adaptability and ability to model continuous- time dynamics, emerge as a potent tool for real-time portfolio rebalancing and decision-making. The study provides an in-depth overview of NODEs, elucidating their architecture and their application in modeling financial time series data. This theoretical journey leads to the exploration of practical implications. The study highlights the potential benefits of incorporating NODEs into portfolio management, including improved risk management, enhanced returns, and the capacity for adaptive asset allocation strategies. However, it also addresses the limitations and challenges associated with this integration, such as data quality issues and computational requirements. In conclusion, this research presents a theoretical framework that bridges the gap between deep learning and continuous-time financial models, offering a promising avenue for real-time portfolio optimization. The insights derived from this study serve as a foundation for future research and practical applications in navigating the intricate landscape of financial markets.

Modern Portfolio Theory: analysis and implication

The Modern Portfolio Theory (MPT) from quantitative theory explains the correct of the logic of investment which isnt put all your eggs in one basket. Although this theory is published in 1952, investors are still using this theory nowadays. Therefore, this paper is researching why this theory is enduring, whether it can provide some insights into the behavior of investors, and what shortcomings can be solved by using other derivative theories based on this theory. The most significant observation of this study can be divided into two parts. Firstly, many limitations of MPT can be improved by Goal-based investing and Post-modern portfolio theory. Secondly, this theory can help the investor to choose the optimal portfolio theory depending on their attitude and goal when they chose the portfolio. There is a strong need for a novel approach, especially for concluding extra costs when investors calculate the risk-adjusted returns. After that, this theory is using historical data to calculate the expected data. Those limitations will influence the choice of optimal portfolio theory.

Semi-Metric Portfolio Optimization: A New Algorithm Reducing Simultaneous Asset Shocks

This paper proposes a new method for financial portfolio optimization based on reducing simultaneous asset shocks across a collection of assets. This may be understood as an alternative approach to risk reduction in a portfolio based on a new mathematical quantity. First, we apply recently introduced semi-metrics between finite sets to determine the distance between time series’ structural breaks. Then, we build on the classical portfolio optimization theory of Markowitz and use this distance between asset structural breaks for our penalty function, rather than portfolio variance. Our experiments are promising: on synthetic data, we show that our proposed method does indeed diversify among time series with highly similar structural breaks and enjoys advantages over existing metrics between sets. On real data, experiments illustrate that our proposed optimization method performs well relative to nine other commonly used options, producing the second-highest returns, the lowest volatility, and second-lowest drawdown. The main implication for this method in portfolio management is reducing simultaneous asset shocks and potentially sharp associated drawdowns during periods of highly similar structural breaks, such as a market crisis. Our method adds to a considerable literature of portfolio optimization techniques in econometrics and could complement these via portfolio averaging.

Sector Rotation Investment Strategy by Implementing Piotroski F-Score and Markowitz Portfolio Theory for Portfolio Construction: Indonesia Stock Market 2020 to 2022

IHSG or IDX Composite Index crash during 2020 where the index fell 37.5% since beginning of 2020 until mid march to the level points of 3,938, recovered and marking up in 2021 where the index reaching the peak in November to the level points of 6,723, and then consolidating at the year of 2022 where the index move in a ranging movements of up and down within the level points of 6,500 to 7,300. The different cycles of stock market movement are happening because of changes and different economic factors, making investors presented with a different opportunities and risks at the stock market. In order to capitalize these changes at the market, investors need to analyzed their portfolio periodically for evaluation and assessment. These research were conducted to examines what are the best portfolio for each year of 2020, 2021, and 2022 using sector rotation investment strategy by implementing sector comparison analysis and Piotroski F-score for stock screening method, while using Markowitz portfolio optimization theory for portfolio construction.

Application of LSTM and portfolio optimization in Chinese stock market

The purpose of this paper is to examine the application of LSTM and mean variance portfolio optimization in Chinese stock market. 20 stocks are selected from CSI 300 components, we collect their High, Low, Open, Adjust Close and trade volume from June 16th 2020 to June 16th 2022. Then we use LSTM model to forecast the stock price. The forecast results are used to construct 2 portfolios. One portfolio maximize Sharpe ratio, the other portfolio minimize variance. From April 6th to June 16th 2022, the Maximize Sharpe Ratio portfolio outperformed CSI 300 index, the Minimize Variance Portfolio did not beat the market but the return was very close to CSI. Therefore, the combination of LSTM and Mean Variance Portfolio Optimization theory is effective in Chinese stock market.

Portfolio Selection in NSE Expected Return & Risk through Markowitz Portfolio Theory

This article tells us about selection of portfolio from National Stock Exchange. Investors are more concerned about their objective minimizing risk and maximizing returns. They considering their tradeoff b/w risk and return from the portfolio, a financial economist, Harry Markowitz, proposed the So-called optimal portfolio theory in 1952. The aim of this article is to provide a practical study of Markowitz model on the Indian Stock Market (NSE) from 1st June 2009 to 30th June 2019.The Markowitz model has been widely used by investors, its application on National Stock Exchange is limited. From the data input which are monthly adjusted closing & daily adjusted closing prices. As a result, investors can select the optimal portfolio that maximizes portfolio return with respect to risk. It is vividly manifest that the investor tends to be risk averters, the attitude towards risk and return tends to play a vital role for the selection of the portfolio. Thus, there is the need to comprehend the investor’s attitude towards different portfolio choices. Diversification always reduces the non-systematic risk, it is also given by Morgan Kelly in 1994 gives the benefits of diversification (all the eggs in one basket: portfolio diversification of US households). In other words, diversification allows an opportunity for investments to grow with minimum volatility, security behave differently in different market conditions.

Optimization Investment Structure on Petroleum Exploration and Development

Abstract In order to improve the decision-making ability of exploration and development investment of petroleum enterprises, our study focuses on the optimization method of investment structure. First, this paper analyzed ten risk factors that are most likely encountered by oil enterprises in exploration and development investment by using Markowitz's portfolio theory. A conclusive objective function was established based on the net present value mean-variance, semivariance, and semi-absolute deviation risk model. Second, studying the link between regional exploration investment and expected reserves, trapping exploration investment and controlling reserves, evaluating exploration investment and proved reserves, the relationship model between reserve price and reserves was constructed through commercializing reserves. By studying the relationship between exploration investment and reserves, development investment and production, we used the portfolio optimization theory to establish a comprehensive model for the optimization of oil and gas multi-stage exploration and development investment structure. Third, based on the established exploration and development portfolio optimization model and the actual economic evaluation needs of oil fields, this study established the medium and long-term investment model, block equilibrium constrained investment structure optimization model, reserve replacement rate constrained investment structure optimization model, and short-term investment structure optimization models. These models provided a basis for different investment decisions of oil and gas exploration and development.

Modified Mean-Variance Analysis, Portfolio Optimization and Prospect Theory

Modified Mean-Variance Analysis, Portfolio Optimization and Prospect Theory

Optimal Transaction Model Based on Venture Capital

Market is full of volatile assets, making traders dazzling when investing and forming portfolios. Surely, even the most intelligent one can fall head over heels when facing rug-pull. However, the goal to maximize total return is possible if a best strategy is made. Instead of invest blindly and behave impulsively and help the trader to achieve his goal, we preprocess the prices of gold and bitcoin, build three models to achieve the best balance between risk and return. With the help of MA calculations and through rotating test, we come to our conclusion that Bitcoin is not strongly correlated with gold and can be hedged against risk and is more volatile and suitable for short-term holdings while gold should be made into long-term investment and avoid frequent trading. With the help of optimal portfolio theory, we build our model and test the best proportion of gold and bitcoin when selling and buying.

Essence and Concept of Capitalization of Enterprises its Types and Methods of Evaluation

The historical aspect of the development of scientists' views on the company's capitalization is studied in the work, the stages of development of the concept of cost-oriented management are determined. The role and place of market capitalization in the system of indicators of cost-oriented management are determined, modern methodical approaches to the assessment of the value of the enterprise taking into account the indicator of market capitalization are given. The fundamental differences between the areas of application of indicators of market value of the enterprise and market capitalization are established. The current problems of the Ukrainian economy that limit the widespread use of market capitalization in the valuation of companies are outlined, and proposals are made on the feasibility of valuing Ukrainian companies in terms of real capitalization. The importance of enterprise capitalization in the development of a market economy is emphasized. The evolution of the views of foreign scientists on the capitalization of enterprises has been studied. It is established that the economic essence of the capitalization of enterprises, as well as any asset, is the present value of future income generated by this asset. Bringing future income to the present is a process of discounting. The theory of capitalization of the company in its modern context began to be formed by neoclassical economists from the end of the XIX century. and gained popularity in the second part XX century. The theory of capitalization has given impetus to well-known neoclassical theories of corporate finance, such as the irrelevance theorem, risk theory, investment portfolio optimization theory, arbitrage pricing theory, and so on. It is established that according to the theory of capitalization, the capitalization of the enterprise and the market value of the enterprise are identical concepts, although the methods of their calculation differ. The theory of capitalization has given impetus to the development of many modern financial theories, which are currently under development and improvement.

Ispitivanje portfolio optimizacije ulaganjem u berzanske indekse i bitkoin

This paper presents an empirical verification of the effectiveness and usefulness of investment diversification using the main stock exchange indices and Bitcoin. The objective is to determine the effects applying the Markowitz portfolio optimization theory, i.e., the advantages of applying the modern portfolio theory for institutional investors. The research offers an answer to the following question: what are the advantages and disadvantages of using Bitcoin in portfolio optimization? The paper contributes to the representation of the reach and limitations of the modern portfolio theory for institutional investors. The conclusion is that rational behaviour of institutional investors requires consideration of portfolio optimization using the Markowitz model, because it is possible to create portfolios which, on the basis of historical returns, provide desired returns alongside certain risks. The methodology includes the analysis of high frequency data, i.e., daily trading data were used. The results indicate that the use of the Markowitz portfolio selection method, with all its limitations, is desirable, possible and applicable, but that it entails serious flaws in the sense of neglecting transaction costs, foreign exchange differences and the real value in the stock market. The results of the research show that Bitcoin is a good source of diversification in a portfolio that contains traditional financial instruments both for the risk-averse investor as well as for those investors who have a greater appetite for risk. The conclusion is that rational behavior of institutional investors requires consideration of investing in Bitcoin using the Markowitz model. However, given the high degree of volatility, investors should be very careful when making decisions about including Bitcoin in the portfolio.

Analisis Portofolio Optimal Saham Syariah Jakarta Islamic Index (JII) Periode 2015-2017

Tren investasi di pasar saham syariah Indonesia mengalami peningkatan dari tahun 2015 sampai dengan 2017. Peningkatan ini juga harus diimbangi dengan sikap investor yang mampu memilih kombinasi saham terbaik dengan tingkat pengembalian dan risiko yang terukur melalui portofolio optimal. Tujuan penelitian ini adalah untuk menghitung portofolio optimal saham syariah Jakarta Islamic Index menggunakan Model Markowitz dengan preferensi risiko terendah, Model Markowitz dengan sharpe ratio optimal, dan Single Index Model. Analisis kemudian dilakukan untuk membandingkan tingkat pengembalian yang diharapkan dan tingkat risiko portofolio yang terbentuk dari model tersebut, dan memberikan rekomendasi portofolio optimal kepada investor yang dapat dijadikan sebagai bahan pertimbangan pengambilan keputusan dalam berinvestasi pada saham syariah Jakarta Islamic Index. Penelitian ini menggunakan data harga saham harian, data dividen, IHSG, dan data sukuk. Pemilihan 18 objek saham diperoleh dengan menggunakan metode purposive sampling. Berdasarkan hasil perhitungan, portofolio optimal diperoleh menggunakan model Markowitz dengan sharpe ratio optimal yang menghasilkan kombinasi saham terbaik dengan tingkat pengembalian yang diharapkan dan tingkat risiko sebesar 33,74 persen dan 22 persen dalam setahun.

An analysis of the efficiency of the oil refining industry in the OECD countries

This study investigated the efficiency of the oil refining industry using the two-stage method of Markowitz portfolio optimization theory and panel data analysis of about 30 OECD countries from 2005 to 2016, which is a new methodology for measuring the efficiency of the oil industry. The oil refining industry's efficiency is derived from the prices of petroleum products (Naphtha, Gasoline, Kerosene, Diesel, and Fuel Oil) using the portfolio theory. The panel data was constructed using the following dependent variables, the crude oil production efficiency, energy consumption, renewable energy consumption, and R&D investment. Using the panel data analysis, empirical analyzes are conducted on how the efficiency of the oil refining industry is affected by explanatory variables. The results show that crude oil production and energy use in OECD countries have a negative effect on the efficiency of the oil refining industry, and consumption of renewable energy and R&D investment have a positive effect. Contrary to conventional perception, the petroleum industry can coexist with the renewable energy industry for sustainable development.

Metals futures market: a comparative analysis of investment and arbitrage strategies

The article deals with the application of optimal portfolio theory and pair trading theory on the metals futures market. Advantages of the futures market over the spot market include relatively small initial price, low transaction costs, and high volatility. The main aim of the study is to explore the potential of both strategies for effective trading. The following financial instruments were chosen as the inputs of the models: futures on industrial metals (aluminum, copper, nickel, zinc, lead, tin), futures on precious metals (gold and silver). When building the optimal portfolio, it was decided to include Dow Jones Index futures and S&P Index futures among metals. This is because these instruments are extremely volatile and may play the role of a hedge in the portfolio. A drawdown indicator was used to assess the effectiveness of each strategy. The results show that both strategies can be applied on the real-life market. The final choice will depend on the level of risk taking by investors and the desired value of return.

Risk-conscious optimization model to support bioenergy investments in the Brazilian sugarcane industry

The past decades have seen a diversification of the sugarcane industry with the emergence of new technology to produce bioenergy from by-product and waste process streams. Given Brazil’s ambitious goal of reducing green-house gas emissions by over 40% below 2005 levels by 2030, it is of paramount importance to develop reliable decision-making systems in order to stimulate investment in these low-carbon technologies. This paper seeks to develop a more accurate optimization model to inform risk-conscious investment decisions for bioenergy generation capacity in sugarcane mills. The main objective is for the model to enable a better understanding of how Brazilian government policies, such as the electricity price in the regulated market, may impact these investments, by taking into account the uncertainty in sugar, ethanol and spot electricity markets and the interdependency between production and investment decisions in terms of saleable product mix. The proposed methodology combines portfolio optimization theory with superstructure process modeling and it relies on simple surrogates derived from a detailed sugarcane plant simulator to retain computational tractability and enable scenario analysis. The case study of an existing sugarcane plant is used to demonstrate the methodology and illustrate how the model can assist decision-makers. In all of the scenarios assessed, the model recommends investment in extra bioelectricity capacity via the anaerobic digestion of vinasse but advises against investment in second-generation ethanol production via the hydrolysis of surplus bagasse. Furthermore, the decision to upgrade the cogeneration system with a condensation turbine is highly sensitive to the electricity price practiced in the regulated market, capacity constraints on the sugar-ethanol mix, and the accepted level of risk. Another key insight drawn from the case study is that recent market conditions have favored a production focused on the sugar business, making it challenging for policy-makers to create attractive scenarios for biofuels. Long-term electricity contracting appears to be the main hedging strategy for de-risking other products and investments in the sugarcane business, provided it is priced adequately.

Trading risk control model of electricity retailers in multi‐level power market of China

AbstractThe decision‐making and risk assessment of electricity purchase and sales is the key to adapt to the electricity market for independent electricity retailers in China. This research carried out the purchase and sales risks of electricity for electricity retailers and constructed the multi‐level market purchase and sales combination optimization model. Based on the portfolio optimization theory, the conditional value at risk theory (CVaR) was proposed. Based on the evaluation index about the conditional risk profit and CVaR, electricity retailers purchase and sales combined optimization model has been constructed to explore the impact of purchase and sales risks by different factors in multi‐level electricity market. The example analysis was carried out by the fixed spread mode and the linkage spread mode. The results showed that the mathematical mean and variance of market spread had great influence on the electricity purchase and sales combination. Especially in the mature electricity market, the mathematical mean of spread and risk in medium‐ and long‐term market was smaller than that in spot market, and the best point of the electricity purchase and sales combination was shown on the smallest value of CVaR, while the electricity purchase and sales combination was optimal under limited conditions.

Optimal Hajj Funds Management by Islamic Bank

The purpose of this paper is to find the optimal portfolio of Hajj fund management by the Islamic banks in Indonesia. BPKH, as an authority, can place the Hajj fund on Islamic bank deposits. However, Islamic banks limited the expected returns and risks set by BPKH so that the appropriate strategy is required to establish the optimal of portfolio. Islamic banks face a trade-off because of the increased level of risk constrains the intention to get higher returns. This study uses a mean-variance portfolio optimization theory to construct such an optimal portfolio. Finally, this study recommends Murabaha financing and SBIS to Islamic banks as the optimal portfolio selection. The combination of an efficient portfolio that has formed cannot be fully employed because the expectation limits them. However, Islamic banks can still select the optimal portfolio combination according to their risk preferences.JEL Classification: G11, G18

Forecasting Efficient Risk/Return Frontier for Equity Risk with a KTAP Approach—A Case Study in Milan Stock Exchange

We introduce and discuss a dynamics of interaction of risky assets in a portfolio by resorting to methods of statistical mechanics developed to model the evolution of systems whose microscopic state may be augmented by variables which are not mechanical. Statistical methods are applied in the present paper in order to forecast the dynamics of risk/return efficient frontier for equity risk. Specifically, we adopt the methodologies of the kinetic theory for active particles (KTAP) with stochastic game-type interactions and apply the proposed model to a case study analyzing a subset of stocks traded in Milan Stock Exchange. In particular, we evaluate the efficient risk/return frontier within the mean/variance portfolio optimization theory for 13 principal components of the Milan Stock Exchange and apply the proposed kinetic model to forecast its short-term evolution (within one year). The model has the aim to pave the way to many different research perspectives and applications discussed eventually in the paper. In particular, the case of efficient frontier obtained by minimizing the Conditional Value-at-Risk (CVaR) is introduced and a preliminary result is proposed.

Region sown areas portfolio optimization taking into account crop production economic risk

Grain production is one of the Ukrainian agro-industrial complex main branches. An indicator of the grain production efficiency is its profitability. It is characterized by significant annual fluctuations that induce risk. Redistribution of existing grain crops areas taking into consideration their profitability can bring to increase of production efficiency. The paper observes Markowitz’s optimal portfolio theory appliance to grain branch. The central aim of this work is the development and justification of a new technique of sown areas portfolio risk evaluating. In this study, the annual profitability of four cereal crops cultivated in the Rivne region: wheat, barley, corn, and oats, have been analyzed. It is shown that the profitability of the cereals is not normally distributed. Under these conditions, the portfolio variance loses part of its informativity and can not serve as a good risk measure. It has been determined that the profitability of crops with good precision follows Laplace distribution (double exponential distribution). The analytical expression for Value-at-Risk measures has been obtained using the Laplace distribution function. Numerical risk assessments performed. Using a modified Markowitz model and obtained risk estimates the efficient frontiers of cereal sown areas portfolios in the Rivne region were constructed. Obtained results allow indicating ways for optimization the region grain industry structure.