Hasil untuk "Capital. Capital investments"

Jiajie Cheng, Jiaxin Wang, Caijiao Li et al.

In the context of the rapid development of digital supply chain networks, dealing with the increasing cybersecurity threats and formulating effective security investment strategies to defend against cyberattack risks are the core issues in supply chain management. Cybersecurity investment decision-making is a key strategic task in enterprise supply chain manage-ment. Traditional game theory models and linear programming methods make it challenging to deal with complex problems such as multi-party par-ticipation in the supply chain, resource constraints, and risk uncertainty, re-sulting in enterprises facing high risks and uncertainties in the field of cy-bersecurity. To effectively meet this challenge, this study proposes a nonlin-ear budget-constrained cybersecurity investment optimization model based on variational inequality and projection shrinkage algorithm. This method simulates the impact of market competition on security investment by intro-ducing market share variables, combining variational inequality and projec-tion shrinkage algorithm to solve the model, and analyzing the effect of dif-ferent variables such as budget constraints, cyberattack losses, and market share on supply chain network security. In numerical analysis, the model achieved high cybersecurity levels of 0.96 and 0.95 in the experimental sce-narios of two retailers and two demand markets, respectively, and the budget constraint analysis revealed the profound impact of budget constraints on cybersecurity investment. Through numerical experiments and comparative analysis, the effectiveness and operability of this method in improving sup-ply chain network security are verified.

Zhe Fei, Scott Robertson

We consider an equity market subject to risk from both unhedgeable shocks and default. The novelty of our work is that to partially offset default risk, investors may dynamically trade in a credit default swap (CDS) market. Assuming investment opportunities are driven by functions of an underlying diffusive factor process, we identify the certainty equivalent for a constant absolute risk aversion investor with a semi-linear partial differential equation (PDE) which has quadratic growth in both the function and gradient coefficients. For general model specifications, we prove existence of a solution to the PDE which is also the certainty equivalent. We show the optimal policy in the CDS market covers not only equity losses upon default (as one would expect), but also losses due to restricted future trading opportunities. We use our results to price default dependent claims though the principal of utility indifference, and we show that provided the underlying equity market is complete absent the possibility of default, the equity-CDS market is complete accounting for default. Lastly, through a numerical application, we show the optimal CDS policies are essentially static (and hence easily implementable) and that investing in CDS dramatically increases investor indirect utility.

Luis Rodrigo Arnabal, Santiago Camara, Cecilia Dassatti

This paper studies how shocks to global banks' net worth transmit to Emerging Market Economies. Using the identification strategy of Ottonello and Song (2022), which isolates high-frequency surprises to banks' credit supply capacity, we show that positive shocks appreciate local currencies, lower external borrowing costs, increase capital flows to domestic banking sectors, and raise investment, credit, and real activity across EMEs. These effects are highly robust across specifications and samples. Using administrative credit-registry data from Uruguay, we find that better capitalized banks transmit global credit easing more strongly. At the firm level, responses are weaker for more leveraged firms, especially those with foreign-currency debt, short maturities, or collateral not priced to market.

Arno Geimer, Beltran Fiz Pontiveros, Radu State

Federated Learning (FL) is a collaborative machine learning paradigm which allows participants to collectively train a model while training data remains private. This paradigm is especially beneficial for sectors like finance, where data privacy, security and model performance are paramount. FL has been extensively studied in the years following its introduction, leading to, among others, better performing collaboration techniques, ways to defend against other clients trying to attack the model, and contribution assessment methods. An important element in for-profit Federated Learning is the development of incentive methods to determine the allocation and distribution of rewards for participants. While numerous methods for allocation have been proposed and thoroughly explored, distribution frameworks remain relatively understudied. In this paper, we propose a novel framework which introduces client-specific tokens as investment vehicles within the FL ecosystem. Our framework aims to address the limitations of existing incentive schemes by leveraging a decentralized finance (DeFi) platform and automated market makers (AMMs) to create a more flexible and scalable reward distribution system for participants, and a mechanism for third parties to invest in the federation learning process.

Luca Santosuosso, Sonja Wogrin

This study addresses the investment planning problem of a virtual power plant (VPP), formulated as a mixed-integer linear programming (MILP) model. As the number of binary variables increases and the investment time horizon extends, the problem can become computationally intractable. To mitigate this issue, time series aggregation (TSA) methods are commonly employed. However, since TSA typically results in a loss of accuracy, it is standard practice to derive bounds to control the associated error. Existing methods validate these bounds only in the linear case, and when applied to MILP models, they often yield heuristics that may even produce infeasible solutions. To bridge this gap, we propose an iterative TSA method for solving the VPP investment planning problem formulated as a MILP model, while ensuring a bounded error in the objective function. Our main theoretical contribution is to formally demonstrate that the derived bounds remain valid at each iteration. Notably, the proposed method consistently guarantees feasible solutions throughout the iterative process. Numerical results show that the proposed TSA method achieves superior computational efficiency compared to standard full-scale optimization.

Nicola Borri, Yukun Liu, Aleh Tsyvinski et al.

We organize existing empirical regularities of cryptocurrencies into seven stylized facts and analyze cryptocurrencies through the lens of empirical asset pricing. We find important similarities with traditional markets--risk-adjusted performance so far is broadly comparable, and the cross-section of returns can be summarized by a small set of factors. However, cryptocurrency also has its own distinct character: jumps are frequent and large, and blockchain information helps drive prices. This common set of stylized facts provides evidence that cryptocurrency is emerging as an investable asset class. Additionally, we discuss potential data quality issues and possible changes in future regulations and the cryptocurrency environment.

Samidh Pal

This paper investigates the inter-regional intra-industry disparity within selected Indian manufacturing industries and industrial states. The study uses three measures - the Output-Capital Ratio, the Capital-Labor Ratio, and the Output-Labor Ratio - to critically evaluate the level of disparity in average efficiency of labor and capital, as well as capital intensity. Additionally, the paper compares the rate of disparity of per capita income between six major industrial states. The study finds that underutilization of capacity is driven by an unequal distribution of high-skilled labor supply and upgraded technologies. To address these disparities, the paper suggests that policymakers campaign for labor training and technology promotion schemes throughout all regions of India. By doing so, the study argues, the country can reduce regional inequality and improve economic outcomes for all.

Jiasheng Zhu, Luyao Zhang

Gamification is an effective strategy for motivating and engaging users, which is grounded in business, marketing, and management by designing games in nongame contexts. Gamifying education, which consists of the design and study of educational games, is an emerging trend. However, the existing classroom games for understanding macroeconomics have weak connections to the microfoundations of individual decision-making. We design an educational game on cryptocurrency investment for understanding macroeconomic concepts in microeconomic decisions. We contribute to the literature by designing game-based learning that engages students in understanding macroeconomics in incentivized individual investment decisions. Our game can be widely implemented in online, in-person, and hybrid classrooms. We also reflect on strategies for improving the user experience for future educational game implementations.

Ke Fu, Ximin Rong, Hui Zhao

This paper studies the optimal investment problem for a hybrid pension plan under model uncertainty, where both the contribution and the benefit are adjusted depending on the performance of the plan. Furthermore, an age and time-dependent force of mortality and a linear maximum age are considered to capture the longevity trend. Suppose that the plan manager is ambiguity averse and is allowed to invest in a risk-free asset and a stock. The plan manager aims to find optimal investment strategies and optimal intergenerational risk-sharing arrangements by minimizing the cost of unstable contribution risk, the cost of unstable benefit risk and discontinuity risk under the worst-case scenario. By applying the stochastic optimal control approach, closed-form solutions are derived under a penalized quadratic cost function. Through numerical analysis and three special cases, we find that the intergeneration risk-sharing is achieved in our collective hybrid pension plan effectively. And it also shows that when people live longer, postponing the retirement seems a feasible way to alleviate the stress of the aging problem.

Agnes Marjorie Nakiganda, Shahab Dehghan, Petros Aristidou

The integration of the frequency dynamics into Micro-Grid (MG) investment and operational planning problems is vital in ensuring the security of the system in the post-contingency states. However, the task of including transient security constraints in MG planning problems is non-trivial. This is due to the highly non-linear and non-convex nature of the analytical closed form of the frequency metrics (e.g., frequency nadir) and power flow constraints. To handle this issue, this paper presents two algorithms for decomposing the MG investment planning problem into multiple levels to enhance computational tractability and optimality. Furthermore, the sensitivity of the decisions made at each level is captured by corresponding dual cutting planes to model feasible secure regions. This, in turn, ensures both the optimal determination and placement of inertia services and accelerates the convergence of the proposed decomposition algorithms. The efficient and effective performance of the proposed algorithms is tested and verified on an 18-bus Low Voltage (LV) network and a 30-bus Medium Voltage (MV) network under various operating scenarios.

Shweta Gaonkar, Angelo Mele

How do inter-organizational networks emerge? Accounting for interdependence among ties while studying tie formation is one of the key challenges in this area of research. We address this challenge using an equilibrium framework where firms' decisions to form links with other firms are modeled as a strategic game. In this game, firms weigh the costs and benefits of establishing a relationship with other firms and form ties if their net payoffs are positive. We characterize the equilibrium networks as exponential random graphs (ERGM), and we estimate the firms' payoffs using a Bayesian approach. To demonstrate the usefulness of our approach, we apply the framework to a co-investment network of venture capital firms in the medical device industry. The equilibrium framework allows researchers to draw economic interpretation from parameter estimates of the ERGM Model. We learn that firms rely on their joint partners (transitivity) and prefer to form ties with firms similar to themselves (homophily). These results hold after controlling for the interdependence among ties. Another, critical advantage of a structural approach is that it allows us to simulate the effects of economic shocks or policy counterfactuals. We test two such policy shocks, namely, firm entry and regulatory change. We show how new firms' entry or a regulatory shock of minimum capital requirements increase the co-investment network's density and clustering.

Anthony E. Brockwell

We review some fundamental concepts of investment from a mathematical perspective, concentrating specifically on fractional-Kelly portfolios, which allocate a fraction of wealth to a growth-optimal portfolio while the remainder collects (or pays) interest at a risk-free rate. We elucidate a coherent continuous-parameter time-series framework for analysis of these portfolios, explaining relationships between Sharpe ratios, growth rates, and leverage. We see how Kelly's criterion prescribes the same leverage as Markowitz mean-variance optimization. Furthermore, for fractional Kelly portfolios, we state a simple distributional relationship between portfolio Sharpe ratio, the fractional coefficient, and portfolio log-returns. These results provide critical insight into realistic expectations of growth for different classes of investors, from individuals to quantitative trading operations. We then illustrate application of the results by analyzing performance of various bond and equity mixes for an investor. We also demonstrate how the relationships can be exploited by a simple method-of-moments calculation to estimate portfolio Sharpe ratios and levels of risk deployment, given a fund's reported returns.

Huirong Liu

This paper employs the survey data of CHFS (2013) to investigate the impact of housing investment on household stock market participation and portfolio choice. The results show that larger housing investment encourages the household participation in the stock market, but reduces the proportion of their stockholding. The above conclusion remains true even when the endogeneity problem is controlled with risk attitude classification, Heckman model test and subsample regression. This study shows that the growth in the housing market will not lead to stock market development because of lack of household financial literacy and the low expected yield on stock market.

Plamen Nikolov, Md Shahadath Hossain

Economists have mainly focused on human capital accumulation rather than on the causes and consequences of human capital depreciation in late adulthood. To investigate how human capital depreciates over the life cycle, we examine how a newly introduced pension program, the National Rural Pension Scheme, affects cognitive performance in rural China. We find significant adverse effects of access to pension benefits on cognitive functioning among the elderly. We detect the most substantial impact of the program on delayed recall, a cognition measure linked to the onset of dementia. In terms of mechanisms, cognitive deterioration in late adulthood is mediated by a substantial reduction in social engagement, volunteering, and activities fostering mental acuity.

Xue Dong He, Xianhua Peng

The regulator is interested in proposing a capital adequacy test by specifying an acceptance set for firms' capital positions at the end of a given period. This set needs to be surplus-invariant, i.e., not to depend on the surplus of firms' shareholders, because the test means to protect firms' liability holders. We prove that any surplus-invariant, law-invariant, and conic acceptance set must be the set of capital positions whose value-at-risk at a given level is less than zero. The result still holds if we replace conicity with numeraire-invariance, a property stipulating that whether a firm passes the test should not depend on the currency used to denominate its assets.

Liurui Deng, Traian A. Pirvu

In this article, inspired by Shi, et al. we investigate the optimal portfolio selection with one risk-free asset and one risky asset in a multiple period setting under cumulative prospect theory (CPT). Compared with their study, our novelty is that we consider a stochastic benchmark, and portfolio constraints. We test the sensitivity of the optimal CPT-investment strategies to different model parameters by performing a numerical analysis.

Huy N. Chau, Andrea Cosso, Claudio Fontana et al.

We consider the problem of optimal investment with intermediate consumption in a general semimartingale model of an incomplete market, with preferences being represented by a utility stochastic field. We show that the key conclusions of the utility maximization theory hold under the assumptions of no unbounded profit with bounded risk (NUPBR) and of the finiteness of both primal and dual value functions.

Sergey Nadtochiy, Michael Tehranchi

This paper is concerned with the axiomatic foundation and explicit construction of a general class of optimality criteria that can be used for investment problems with multiple time horizons, or when the time horizon is not known in advance. Both the investment criterion and the optimal strategy are characterized by the Hamilton-Jacobi-Bellman equation on a semi-infinite time interval. In the case when this equation can be linearized, the problem reduces to a time-reversed parabolic equation, which cannot be analyzed via the standard methods of partial differential equations. Under the additional uniform ellipticity condition, we make use of the available description of all minimal solutions to such equations, along with some basic facts from potential theory and convex analysis, to obtain an explicit integral representation of all positive solutions. These results allow us to construct a large family of the aforementioned optimality criteria, including some closed form examples in relevant financial models.

Masahiko Egami, Kazutoshi Yamazaki

Sustaining efficiency and stability by properly controlling the equity to asset ratio is one of the most important and difficult challenges in bank management. Due to unexpected and abrupt decline of asset values, a bank must closely monitor its net worth as well as market conditions, and one of its important concerns is when to raise more capital so as not to violate capital adequacy requirements. In this paper, we model the tradeoff between avoiding costs of delay and premature capital raising, and solve the corresponding optimal stopping problem. In order to model defaults in a bank's loan/credit business portfolios, we represent its net worth by Levy processes, and solve explicitly for the double exponential jump diffusion process and for a general spectrally negative Levy process.

Enrico Scalas

On June 26th, 2004, Central bank governors and the heads of bank supervisory authorities in the Group of Ten (G10) countries issued a press release and endorsed the publication of "International Convergence of Capital Measurement and Capital Standards: a Revised Framework", the new capital adequacy framework commonly known as Basel II. According to Jean Claude Trichet, Chairman of the G10 group of central bank governors and heads of bank supervisory authorities and President of the European Central Bank: ``Basel II embraces a comprehensive approach to risk management and bank supervision. It will enhance banks' safety and soundness, strengthen the stability of the financial system as a whole, and improve the financial sector's ability to serve as a source for sustainable growth for the broader economy.'' The negotial process is likely to lead to the adoption of the new rules within 2007. In 1996, after the "Amendment to the capital accord to incorporate market risks", a new wave of physicists entered risk management offices of large banks, that had to develop internal models of market risk. Which will be the challenges and opportunities for physicists in the financial sector in the years to come? This paper is a first modest contribution for starting a debate within the Econophysics community.