Presence Of Transaction Costs Research Articles

Neural Networks for Portfolio Analysis With Cardinality Constraints.

Portfolio analysis is a crucial subject within modern finance. However, the classical Markowitz model, which was awarded the Nobel Prize in Economics in 1991, faces new challenges in contemporary financial environments. Specifically, it fails to consider transaction costs and cardinality constraints, which have become increasingly critical factors, particularly in the era of high-frequency trading. To address these limitations, this research is motivated by the successful application of machine learning tools in various engineering disciplines. In this work, three novel dynamic neural networks are proposed to tackle nonconvex portfolio optimization under the presence of transaction costs and cardinality constraints. The neural dynamics are intentionally designed to exploit the structural characteristics of the problem, and the proposed models are rigorously proven to achieve global convergence. To validate their effectiveness, experimental analysis is conducted using real stock market data of companies listed in the Dow Jones Index (DJI), covering the period from November 8, 2021 to November 8, 2022, encompassing an entire year. The results demonstrate the efficacy of the proposed methods. Notably, the proposed model achieves a substantial reduction in costs (which combines investment risk and reward) by as much as 56.71% compared with portfolios that are averagely selected.

Hedging goals

Goal-based investing is concerned with reaching a monetary investment goal by a given finite deadline, which differs from mean-variance optimization in modern portfolio theory. In this article, we expand the close connection between goal-based investing and option hedging that was originally discovered in Browne (Adv Appl Probab 31(2):551–577, 1999) by allowing for varying degrees of investor risk aversion using lower partial moments of different orders. Moreover, we show that maximizing the probability of reaching the goal (quantile hedging, cf. Föllmer and Leukert in Finance Stoch 3:251–273, 1999) and minimizing the expected shortfall (efficient hedging, cf. Föllmer and Leukert in Finance Stoch 4:117–146, 2000) yield, in fact, the same optimal investment policy. We furthermore present an innovative and model-free approach to goal-based investing using methods of reinforcement learning. To the best of our knowledge, we offer the first algorithmic approach to goal-based investing that can find optimal solutions in the presence of transaction costs.

Discrete‐time risk sensitive portfolio optimization with proportional transaction costs

AbstractIn this paper we consider a discrete‐time risk sensitive portfolio optimization over a long time horizon with proportional transaction costs. We show that within the log‐return i.i.d. framework the solution to a suitable Bellman equation exists under minimal assumptions and can be used to characterize the optimal strategies for both risk‐averse and risk‐seeking cases. Moreover, using numerical examples, we show how a Bellman equation analysis can be used to construct or refine optimal trading strategies in the presence of transaction costs.

Models of the dynamics of maximal and optimal profits of a manufacturing enterprise implementing technological innovations

The published article presents new mathematical models that describe the dynamics of the development of manufacturing enterprises using innovative technologies. It is shown that the level of use of innovative technologies in an enterprise depends on dimensionless coefficients that describe the diffusion process of introducing technological innovations and affect the increase in output and cost reduction. The dependence of the enterprise's profit on the levels of production and transaction costs has been studied. It has been established that the formation of transaction costs arising from the search and processing of economic information, financing of negotiation procedures, conclusion of contracts with partners, protection of property rights and payment for the opportunistic behavior of employees and management of the enterprise, force the management of the enterprise to maximize not only the profit function, but also the target a transactional utility function that takes into account the redistribution of profits in the interests of the enterprise's management and for the implementation of socially-oriented programs. Dimensionless redistribution coefficients are calculated, which determine the size of the part of the profit that is used for non-production purposes. It is shown that in the presence of transaction costs, the limiting value of the enterprise's profit is not its maximum possible value, but its lower optimal value.

EX ANTE PREDICTABILITY OF STOCK RETURNS IN A FRONTIER MARKET

This study reports results on the ex ante predictability of stock returns using real-time stock market data in Vietnam, a frontier market, from June 2008 to June 2021. Countries classified as a frontier market are often known for currency manipulation, financial market illiquidity, and political instability. Despite the enormous risk usually posed by these inefficiencies, potential profits are large and achievable for many investors. This study provides evidence on existing a strategy to form out-of-sample long portfolios that generate statistically significant and positive mean monthly returns even in the presence of transaction costs. I also justify the magnitude of these returns by showing that they exceed those of VnIndex and MSCI Vietnam Index. The results reject the hypothesis that the stock prices in Vietnamese market follow random walks, thus oppose the stock market efficiency hypothesis. Evidence found in this study provides a better understanding of informational efficiency in a frontier equity market setting. Specifically, there are several implications on portfolio selection strategies, stock price patterns, and trading behavior bias related to Vietnamese stock market can be drawn from this study.

Aggregating exponential gradient expert advice for online portfolio selection under transaction costs

As an application of machine learning techniques in the field of portfolio management, online portfolio selection (OLPS) aims at optimising the allocation of wealth in an uncertain environment. When making investment decisions, the transaction cost is such an important factor that investor should not ignore. Thus, this paper extends an existing online portfolio selection strategy Continuous Aggregating Exponential Gradient (CAEG) (Yang et al., 2022) in the presence of transaction costs. The proportional transaction costs model is constructed when the transaction costs are incorporated into the decision-making process, and we call this new strategy . Theoretical guarantee proves that the mean of the logarithmic cumulative wealth of has an asymptotic upper bound with that of its benchmark. The numerical examples demonstrate the impact of transaction costs on the proposed strategy on the one hand, and on the other hand, verify that outperforms other related OLPS strategies and is comparable to its benchmark strategy.

Spatial market integration of rice in Bangladesh in the presence of transaction cost

Modeling transaction costs is of particular importance when analyzing price integration in developing countries. Spatial price integration among five major Bangladesh rice markets are examined over the post-liberalization period that covered a long time span from January 1999 to December 2021, the longest period covered ever. We account for nonlinear price adjustments induced by transaction costs using a threshold cointegration approach to account for the impact of transaction costs in the price adjustment process. Our results show that large price deviations from long-run equilibrium are corrected within 2–3 months. Our results provide strong supporting evidence of the presence of threshold effects, which means that large transaction costs contribute to slow equilibrium price adjustments. Thus, our results provide important policy implications for Bangladesh rice markets, namely that polices aimed at reducing transaction costs are needed to engender greater pricing efficiency in Bangladesh rice markets.

Super‐replication with transaction costs under model uncertainty for continuous processes

AbstractWe formulate a superhedging theorem in the presence of transaction costs and model uncertainty. Asset prices are assumed continuous and uncertainty is modeled in a parametric setting. Our proof relies on a new topological framework in which no Krein–Smulian type theorem is available.

Land rental market reforms: Can they increase outmigration from agriculture? Evidence from a quantitative model

Recent econometric work suggests that there is a positive link between the development of land rental markets and the migration of workers out of agriculture in the developing world. I investigate this claim using a two-sector model of structural transformation that takes into account the well-known inverse relationship between farm size and farm productivity. The model studies how the allocation of employment between agricultural and non-agricultural activities is affected by the presence of transaction costs in the land rental market, as well as by the initial distribution of land ownership. Theoretically, a reduction in transaction costs induces outmigration from agriculture if agricultural prices are sufficiently flexible, while rigid agricultural prices may lead to the reverse phenomenon of immigration in agriculture. Practically, the model predicts that for most of the countries tested, a reduction in transaction costs causes little labor movement between sectors. This is equally true concerning the effect of a land redistribution. In spite of this, these reforms are found to increase substantially the production efficiency and welfare of farmers. These results suggest that the main benefit of stimulating land rentals is not in fostering structural transformation, but in improving the livelihoods of farmers.

TRANSACTION COSTS IN THE ACTIVITIES OF INSURANCE INSTITUTIONS

Introduction. The concept of transaction costs plays an important role in understanding the relationship between insurer and the insured, the principle of mutual good faith in the relations of these participants, the nature of the insurance company, managing insurance relations to increase the size of the insurance portfolio and increase solvency, increase insurer value. The presence of transaction costs in practice leads to a decrease in the efficiency of insurance institutions, as well as to a decrease in the financial results of insurance. The purpose of the study is the theoretical substantiate the nature of transaction costs that arise in the activities of insurance institutions, and development of practical recommendations for their reduction. The methodological basis of the study is a systematic approach, methods of analysis and synthesis, theoretical and abstract-logical generalizations and hypotheses, methods of comparison and grouping, the method of classification. Results. The institutional features inherent in the formation and development of insurance institutions are highlighted. It is determined that the main reason for transaction costs in insurance relations is the existence of asymmetry of information about the object of insurance, the probability of the insured event, the financial stability of the insurer, etc. The main types of transaction costs of insurance institutions are described: information retrieval, negotiation, measurement, costs of specification and protection of property rights, costs of opportunistic behavior. Based on the study, potential ways to minimize transaction costs of insurance institutions are revealed: state policy, vertical integration, reduction of bureaucratization, development of information and communication technologies, transactional analysis, process management model. The practical significance of the study lies in the justification of the need to purposefully influence the amount of transaction costs of insurance institutions in order to minimize them.

Expected vs. real transaction costs in European option pricing

<p style='text-indent:20px;'>As an application and extension of some previous results contained in [<xref ref-type="bibr" rid="b1">1</xref>], we face up the problem of the option pricing in presence of transaction costs and hence in the framework of incomplete markets. The model proposed herein passes through defining properly the expected transaction costs, opposite to the real transaction costs in trading. The analysis is carried out both in the discrete and the continuous case and leads to suitable modifications of Cox-Ross-Rubinstein and Black-Scholes formulas. An application to a specific case referred to real market data at the end of the paper seems to validate our approach.</p>

Optimal multi-period transaction-cost-aware long-only portfolios and time consistency in efficiency

This paper studies a multi-period mean–variance (MV) portfolio selection problem in a market of one risk-free asset and one risky asset traded with proportional transaction costs and no-shorting constraint. A particular interest of this study is to investigate the time consistency in efficiency (TCIE) of the optimal MV portfolio in the presence of transaction costs. To this end, we derive a semi-closed-form solution of the optimal pre-committed dynamic MV policy in the no-shorting non-frictionless market with a combination of embedding and dynamic programming techniques, as well as its several analytical properties. We show that the optimal MV policy is always TCIE when no-shorting constraint is imposed, which gives right to the long-only portfolios in dynamic settings advocated in some empirical evidences. Numerically, we conduct sensitivity analyses of the efficient frontiers and the width of the no-transaction region with respect to the rates of transaction costs and initial wealth allocations. Moreover, we show the significance of the TCIE and the intuitive rationale behind it.

Optimal exercise of American puts with transaction costs under utility maximization

American option pricing plays an essential role in quantitative finance and has been extensively studied in the past. However, how transaction costs affect the American option price, particularly the most important feature of American options, the optimal exercise price, is much less investigated. It is primarily because such a study must be conducted under an incomplete market, which presents additional difficulties on top of an already difficult nonlinear mathematical problem. This paper attempts to provide a supplement study in this area by analyzing the optimal exercise price of an American option in addition to the option price itself in the presence of transaction costs through a utility-based approach. With a computationally efficient numerical scheme, we are able to demonstrate clearly how the optimal exercise price should be calculated and consequently how the option prices for the buyer and writer as well as the early exercise decision are affected by the inclusion of transaction cost.

The Effect of Transaction Costs on The Benefits of Hybrid Maize Farming in Dompu District, West Nusa Tenggara

The characteristics of imperfect markets are characterized by the presence of transaction costs. One sector that is an imperfect market is the agricultural sector. The purpose of this study was to analyze the structure of transaction costs and the implications of transaction costs on the benefits of hybrid corn farming. The research method uses transaction cost analysis and multiple linear regression. The research was conducted in Dompu Regency, West Nusa Tenggara with 120 respondents as corn farmers. The results show that implementation costs are the component of transaction costs that have the highest percentage of 43.35%, then supervision costs are 28.37%, transportation costs are 20.61%, negotiation costs are 3.70%, information costs are 3.41% and coordination 0.57%. These transaction cost components are distributed in each hybrid corn farming cycle, among others; (1) birth cycle; (2) cropping cycle; (3) maintenance cycle; (4) supervision; (5) harvest cycle; and (6) postharvest cycle. The postharvest cycle is the cycle that has the highest percentage of 23.17%, then the maintenance cycle is 18.53%, the harvest cycle is 17.65%, the cropping cycle is 17.28% and the control cycle is 13.99%. Transaction costs have a positive and significant effect on the profits of hybrid corn farming.

Mean–variance combining rules that outperform naïve diversification

The mean–variance framework developed by Markowitz (1952). Portfolio selection, The Journal of Finance, 7(1), 77–91 is still the major model used nowadays in asset allocation and active portfolio management. However, the estimated mean–variance rules often fail to deliver superior performance compared with the simple naïve rule (the equally weighted portfolio) due to the problem of estimation errors. In this paper, I propose a portfolio construction method that is effective in dealing with estimation errors in the optimization process. Particularly, I specify the portfolio weights as an optimal combination of the equally weighted portfolio and a sample zero-investment portfolio. I show analytically that the proposed method alleviates the problem of estimation errors and dominates naïve diversification. I suggest two implementable versions of the combining method and show, empirically, their good performances relative to the naïve rule. The newly developed rules work well, particularly, for portfolios with a medium and high number of assets. Moreover, the outperformance persists generally even in the presence of transaction costs. Since the combinations are theory-based, my study may be interpreted as reaffirming the usefulness of the Markowitz portfolio theory in practice.

Predicting the dynamics of the maximum and optimal profits of innovative enterprises

This article proposes new economic and mathematical models of the dynamics of the development of industrial enterprises that introduce innovative technologies. The level of attraction of innovative technologies by the enterprise is set by dimensionless coefficients of innovations, which depend on time and affect the increase in output and decrease in costs. The influence of not only production costs, but also transaction costs on the size of the enterprise’s profit was investigated, the sources of which are the forced costs of searching and processing economic information, financing negotiation procedures, developing and concluding contracts with partners, organizing the protection of property rights, paying for the opportunistic behavior of employees and enterprise managers, etc. It is found, that transaction costs force to maximize not only the profit function of the enterprise, but also the target transaction utility function, which takes into account the redistribution of profits in the interests of the enterprise management and for the implementation of socially oriented programs. The size of the part of the profit spent in the interests of the enterprise management and for the implementation of socially oriented programs is set by dimensionless redistribution coefficients. It is shown, that in the presence of transaction costs, the enterprise, instead of the maximum value of profit, achieves a lower optimal value of profit.

Technology Uncertainty and Incompleteness in Trade Agreements: Reflections from the Design of India’s Bilateral Agreements Covering Services

International trade agreements are incomplete contracts. The international environment is non-stationary, and technological progress affects both the nature of services and modes of service delivery. This creates uncertainty about future developments in technology-based services. In the presence of transactions costs and due to limited foresight, it is difficult to specify all contingencies within trade agreements ex ante, resulting in contractual incompleteness. This article investigates the design of India’s services agreements to assess the approach followed while listing the ex ante commitment and its implication on technology-based services. It also discusses the ex post mechanism under these agreements to address the gaps in the commitments with respect to new services, and the enforcement mechanism to facilitate the inclusion of these services. It is found that India’s bilateral agreements leave the inclusion of services that may not be technically feasible, ex ante, at the discretion of the trading partners, ex post. Some of India’s agreements also institute a governance mechanism for facilitating this inclusion. The article argues that there is a need for addressing the issue of technology uncertainty both at an international-trade-policy level and under bilateral agreements. Internationally, efforts are underway for a technology-neutral classification of services. Bilateral agreements must include a robust mechanism within the scope of the Agreement for filling gaps that may arise with technological advancements. For furthering the objective of trade agreements, these mechanisms must be backed by sound governance structure.JEL Codes: L80, L84, L86, F13, K33, F53, F55

Semiparametric Portfolio Policies

We present a semiparametric portfolio optimization method in which portfolio weights are parameterized as a non-linear function of firm characteristics. This approach generalizes the linear parametric portfolio policy of Brandt et al. (2009) and can be applied to high-dimensional problems at a relatively low computational cost. An empirical implementation exploiting the size, value, and momentum anomalies in the universe of CRSP stocks reveals that non-linearities as well as interaction effects are both important and complementary for the portfolio construction problem. Moreover, an out-of-sample evaluation indicates that the semiparametric strategies perform well in terms of returns, risk, and risk-adjusted returns both in the absence and in the presence of transaction costs. Our evidence suggests that allowing for a more flexible relation between portfolio weights and firm characteristics can provide a more accurate description of the empirical patterns seen in data.

Delta Hedging of Derivatives using Deep Reinforcement Learning

Building on previous work of Kolm and Ritter (2019) and Cao et al. (2019), this paper explores the novel application of Deep Reinforcement Learning for Delta Hedging of options in an utility based framework where an agent is faced with a trade-off between hedging error and transaction costs while aiming at maximizing the expected profit and loss and minimizing its variance. In the presence of transaction costs we compare the performance of two state-of-the-art Reinforcement Learning algorithms with two simple benchmark strategies widely used in practice. We perform the analysis on synthetic data for different market characteristics, transaction costs, option maturities and hedging frequencies, and find that the agents deliver a strong performance in markets characterized by stochastic volatility and jumps in asset prices, as well as for high transaction costs, high hedging frequency and for options with long maturities. Furthermore, we apply trained algorithms to similar (but not seen before) options and present a way of improving the robustness of the algorithms to different levels of volatility. Finally, we transfer the hedging strategies learned on simulated data to empirical option data on the S&P500 index, and demonstrate that transfer learning is successful: hedge costs encountered by reinforced learning decrease by as much as 30% compared to the Black- Scholes hedging strategy. Our results indicate that the hedging strategies based on Reinforcement Learning outperform the benchmark strategies and are suitable for traders taking real-life hedging decisions, even when the networks are trained on synthetic (but versatile) data.

Time-Varying Conditional Profitability of Momentum Strategies in Commodity Futures Market: Evidence from India

ABSTRACT Manuscript type: Research paper Research aim: This study aims to provide fresh evidence on the presence of momentum profitability in the Indian commodity futures market. Design/Methodology/Approach: This study is based on a sample of highly traded commodity future contracts of the Indian commodity market over the period from 2006 to 2017. It applies the conditional multi-factor model to test the time-varying performance of momentum strategies. Research findings: This study confirms the existence of exceptionally high abnormal momentum profitability in the commodity futures market despite the presence of transaction costs. However, the application of conditional multi-factor model suggests that momentum profits are basically time-varying. The low and insignificant correlation of momentum portfolios with stocks and bonds confirm that relative strength momentum portfolios of commodity futures can be effectively used to create a well-diversified portfolio. Theoretical contribution/Originality: This study analyses the time-varying conditional profitability of momentum strategies for the commodity market of emerging economies such as India. It enriches the small group of studies conducted on commodity futures in the Indian context. The major contribution of the study is the use of conditional multi-factor model to assess the possible role of time-varying conditional alpha and beta to define the momentum payoffs in commodity futures market for the Indian context. Policy implications: Policymakers should design more lucrative policies so as to attract the institutional investors for investment in the Indian commodity market. This is because domestic and foreign institutional investors are central to the enhancement and stability of the financial market. Research implications/Limitations: The study uses the 13 highly traded commodity futures contract to design the momentum strategies. The robustness of the high abnormal returns given by these strategies can be investigated further by the use of extended study period and expanded cross section of commodity futures contract.