Gain-loss Ratio Research Articles

Star-shaped acceptability indexes

We propose the star-shaped acceptability indexes as generalizations of both the approaches of Cherny and Madan (2009) and Rosazza Gianin and Sgarra (2013) in the same vein as star-shaped risk measures generalize both the classes of coherent and convex risk measures in Castagnoli et al. (2022). We characterize acceptability indexes through star-shaped risk measures and star-shaped acceptance sets as the minimum of a family of quasi-concave acceptability indexes. Further, we introduce concrete examples under our approach linked to Value at Risk, risk-adjusted reward on capital, reward-based gain-loss ratio, and monotone reward-deviation ratio.

Parity-time symmetry breaking optical nanocircuit.

Gain and loss balanced parity-time (PT) inversion symmetry has been achieved across multiple platforms including acoustics, electronics, and photonics. Tunable subwavelength asymmetric transmission based on PT symmetry breaking has attracted great interest. However, due to the diffraction limit, the geometric size of an optical PT symmetric system is much larger than the resonant wavelength, which limits the device miniaturization. Here, we theoretically studied a subwavelength optical PT symmetry breaking nanocircuit based on the similarity between a plasmonic system and an RLC circuit. Firstly, the asymmetric coupling of an input signal is observed by varying the coupling strength and gain-loss ratio between the nanocircuits. Furthermore, a subwavelength modulator is proposed by modulating the gain of the amplified nanocircuit. Notably, the modulation effect near the exceptional point is remarkable. Finally, we introduce a four-level atomic model modified by the Pauli exclusion principle to simulate the nonlinear dynamics of a PT symmetry broken laser. The asymmetric emission of a coherent laser is realized by full-wave simulation with a contrast of about 50. This subwavelength optical nanocircuit with broken PT symmetry is of great significance for realizing directional guided light, modulator and asymmetric-emission laser at subwavelength scales.

Using partial sampled-data information for synchronization of chaotic Lur’e systems and its applications: an interval-dependent functional method

This paper is concerned with the synchronization problem of chaotic Lur’e systems by using partial sampled-data information. First, a useful lemma is established on the basis of discrete-time Lyapunov theory and interval estimate methods, which contributes to the stability of partial sampled-data control (PSC) systems. According to the features of the designed control scheme, a single-interval-dependent functional and a double-intervals-dependent functional are constructed by utilizing the corresponding interval information, respectively. Unlike the previous Lyapunov functional methods, the proposed functionals are essentially continuous and then some additional constraint conditions are removed. Then, based on several inequality methods, two sufficient criteria dependent on the controller gain, sampling period, and allowable data loss ratio (ADLR), are respectively developed to guarantee the global synchronization of Lur’e systems. Additionally, the quantitative analysis about the ADLR is discussed. Compared with the existing results, the developed interval-dependent functional techniques are beneficial to enlarging the ADLR. Finally, illustrative examples and an application to image encryption are given to demonstrate the advantages and effectiveness of the proposed control strategy.

A wireless power transfer system based on quasi‐parity–time symmetry with gain–loss ratio modulation

SummaryWireless power transfer (WPT) systems based on parity–time (PT) symmetry can realize robust power transfer against the fluctuation of distance. There is an exceptional point (EP) that partitions the PT‐symmetric and PT‐broken phase, and it is nonadjustable at the conventional system with unity gain–loss ratio unless changing circuit parameters, which limits the improvement of its transfer performance. This paper proposed a novel quasi‐PT‐WPT system based on gain–loss ratio modulation. The proposed system can operate under different gain–loss condition with constant transfer power and efficiency regardless of coupling coefficient variation at the PT‐symmetric phase, which can enhance either the maximum transfer efficiency or distance alternatively. The proposed system consists of a nonlinear gain with adjustable gain–loss ratio to enable the transfer performance control, which is implemented by the virtual impedance. Experimental results verified the correctness of the theoretic analysis and implied the inherent contradiction between the transfer efficiency and distance.

.Footnote Analysis Based upon Robert Larose’s Teleological Translation Model: Istanbul Trilogy

Çeviribilime katkıda bulunmak amacıyla yürütülen bu araştırmanın temelini Robert Larose’un önerdiği bütünleştirici nitelikteki teleolojik (erekbilimsel), amaç odaklı çeviri modeli oluşturmaktadır. Gisèle Durero Köseoğlu’nun Fransızca yazdığı eserlerin çevirileri İstanbul Üçlemesi I: İstanbul’dan Pencereler (2014), İstanbul Üçlemesi II: İstanbul’da Bir El Yazması (2006c), İstanbul Üçlemesi III: Sır Dolu İstanbul (2009b) araştırma nesnesini oluşturmaktadır. Aynı zamanda İstanbul Üçlemesi adlı eserler Gérard Genette’in öne sürdüğü yanmetinler kapsamında çözümlenmiştir. Genette’in metinsel aşkınlık, yanmetinsellik ve metinlerarasılık kavramları irdelenmiş, yanmetinsel öğelerin işlevi ele alınarak metinsel aşkınlık çerçevesinde tartışılmıştır. Larose’un üzerinde yoğunlaştığı metinsel yaklaşım bağlamında dipnot çevirileri değerlendirmeye alınmış, bütünleştirici model kapsamında çeviri için “ön koşullar” ve “sözceleme koşulları” belirlenmeye çalışılmıştır. Larose’un önerdiği Fransızca “traductométrie” ifadesine karşılık olarak “çeviriölçü” ifadesi benimsenmiş, bu tanımlamayla çeviriyi ölçen, değerlendiren bir modele gönderme yapılmıştır. Çeviriölçü yöntemi bağlamında eşdeğerlik kavramının asimetrik doğası, çevirinin benzerlik yapısı, çeviride kazanç-kayıp oranı gibi hususlar irdelenmiştir. Bu araştırma Larose’un teleolojik çeviri modeli temelinde dipnot ve çevirilerini çeviribilimsel sorgulamalarla bütünleştirme gayretinin bir yansıması olarak yürütülmüştür. Larose’un teleolojik çeviri olgusunun çeviri araştırmalarına uyarlanabileceğini kanıtlayan öncül bir araştırma sunma gayreti gösterilmiştir.

Performance measurement with expectiles

Financial performance evaluation is intimately linked to risk measurement methodologies. There exists a well-developed literature on axiomatic and operational characterization of measures of performance. Hinged on the duality between coherent risk measures and reward associated with investment strategies, we investigate representation of acceptability indices of performance using expectile-based risk measures that recently attracted a lot of attention inside the financial and actuarial community. We propose two purely expectile-based performance ratios other than the classical gain-loss ratio and the Omega ratio. We complement our analysis with elicitability of expectile-based acceptability indices and their conditional version accounting for new information flow.

Lightweight Path Recovery in IPv6 Internet-of-Things Systems

In an Internet-of-Things system supported by Internet Protocol version 6 (IPv6), the Routing Protocol for Low-Power and Lossy Networks (RPL) presents extensive applications in various network scenarios. In these novel scenarios characterized by the access of massive devices, path recovery, which reconstructs the complete path of the packet transmission, plays a vital role in network measurement, topology inference, and information security. This paper proposes a Lightweight Path recovery algorithm (LiPa) for multi-hop point-to-point communication. The core idea of LiPa is to make full use of the spatial and temporal information of the network topology to recover the unknown paths iteratively. Specifically, spatial and temporal information refer to the potential correlations between different paths within a time slot and path status during different time slots, respectively. To verify the effect of our proposal, we separately analyze the performance of leveraging temporal information, spatial information, and their composition by extensive simulations. We also compare LiPa with two state-of-the-art methods in terms of the recovery accuracy and the gain–loss ratio. The experiment results show that LiPa significantly outperforms all its counterpart algorithms in different network settings. Thus, LiPa can be considered as a promising approach for packet-level path recovery with minor loss and great adaptability.

Expectile regression via deep residual networks

Expectile is a generalization of the expected value in probability and statistics. In finance and risk management, the expectile is considered to be an important risk measure due to its connection with gain–loss ratio and its coherent and elicitable properties. Linear multiple expectile regression was proposed in 1987 for estimating the conditional expectiles of a response given a set of covariates. Recently, more flexible nonparametric expectile regression models were proposed based on gradient boosting and kernel learning. In this paper, we propose a new nonparametric expectile regression model by adopting the deep residual network learning framework and name it Expectile NN. Extensive numerical studies on simulated and real datasets demonstrate that Expectile NN has very competitive performance compared with existing methods. We explicitly specify the architecture of Expectile NN so that it is easy to be reproduced and used by others. Expectile NN is the first deep learning model for nonparametric expectile regression.

Design and Analysis of LT Codes With a Reverse Coding Framework

In this paper, an improved LT code with a reverse coding framework is designed to reduce the error floor caused by low-degree information nodes. For the proposed coding scheme, a well-designed threshold is used to mark the information nodes whose degrees are less than the threshold, and these nodes will be coded reversely to connect to enough candidate check nodes. To design the optimal threshold, firstly, the information degree distribution and the check degree distribution of the improved LT code are deduced. Then, the parameter extrinsic information gain-loss-ratio (GLR) is designed to evaluate the convergence behavior of the improved LT code. Finally, the ‘slow increase region’ of the GLR is set, and the boundary value of this region is used to deduce the optimal threshold which matches with the channel state information (CSI) and decoding overhead. To make the proposed LT code not limited to a fixed code rate, we further modify the proposed scheme. The segment coding method is used to generate a redundant generator matrix, and the check nodes corresponding to this matrix can be transmitted independently and are not limited to a fixed number. Furthermore, the connection relationship between information nodes and check nodes can be easily recorded, which improves the decoding efficiency. The advantages of the improved LT code are that the degree distributions can be formulated, the convergence behavior can be predicted, and the lowest information degree can be adjusted. Simulation results show that the improved LT code can reduce the error floor by up to 4 orders of magnitude. Besides, the designed LT code outperforms the existing LT codes in literature in terms of bit error rate (BER) performance.

Generation and enhancement of sum sideband in a parity-time-symmetric optomechanical system

This paper studies sum sideband generation in a parity-time ()-symmetric optomechanical system, where an active cavity is coupled to the passive cavity of a general optomechanical system. We find that the upper and lower sum sideband generation efficiencies can be greatly enhanced by the introduction of the gain cavity. Furthermore, when the coupling coefficient and gain–loss ratio are near the exceptional point, the upper sum sideband amplitude is larger than that of the probe fields. This paper also investigates the optimal matching conditions for upper and lower sum sideband generation in the -symmetric phase, the broken -symmetric phase and at the exceptional point, respectively. As a result, new matching conditions are discovered and the appearance of these new matching conditions is ascribed to eigenfrequency splitting. The enhanced sum sideband can be applied to coherent light manipulation, quantum information processing and sensitive quantum metrology.

Analytical analysis of and quasi- symmetry in thick diffraction gratings using coupled-wave theory

The concept of parity-time () symmetry in optics could potentially provide emerging solutions to exploit the benefits of optical gain in optical processing. With this regard, and quasi- symmetry were studied in thick optical diffraction gratings by derivation of explicit analytical expressions using the coupled-wave theory and verified by numerical calculations. The conditions to observe and quasi- symmetry were discussed in terms of the gain-loss ratio and the refractive index modulation amplitudes for both reflective and transmissive gratings. The results show that the criterion to attain quasi- symmetry for the reflective and transmissive gratings is in reverse in terms of the ratio of the modulation amplitude of the imaginary to that of the real part of the refractive index (). According to the model, a grating with fringes parallel to the surface experiences broken symmetry for a wide range of gain-loss ratios. Furthermore, by varying the gain-loss ratio or , some extrema could be observed in the normalized transmission power of the diffraction orders, while operating in the quasi- symmetry regime. The analytical solutions could predict and justify the positions of those extrema which could be advantageous to the design purposes.

3D-ReG

Deep neural network (DNN) models are being expanded to a broader range of applications. The computational capability of traditional hardware platforms cannot accommodate the growth of model complexity. Among recent technologies to accelerate DNN, resistive memory (ReRAM)-based processing-in-memory (PIM) emerged as a promising solution for DNN inference due to its high efficiency for matrix-based computation. We face two major technical challenges in extending the use of ReRAM-based accelerators for training: (1) full-precision data is essential in back-propagation; (2) the need to support both feed-forward and back-propagation aggravates the data-movement burden. We propose a heterogeneous architecture named as 3D-ReG, which leverages full-precision GPU to ensure training accuracy and low-overhead 3D integration to provide low-cost data movements. Moreover, we introduce conservative and aggressive task-mapping schemes, which partition the computation phases in different ways to balance execution efficiency and training accuracy. We evaluate 3D-ReG implemented with two 3D integration technologies, through-silicon vias (TSVs) and monolithic inter-tier vias (MIVs), and compare them with GPU-only and PIM-only counterparts. Various GPU-only platforms using two main-memory technologies (DRAM, ReRAM) and three interconnect technologies (2D, TSV, MIV) are evaluated as well. Experimental results show that 3D-ReG can achieve on average 5.64× training speedup and 3.56× higher energy efficiency compared with the GPU with DRAM as main memory, at the cost of 0.05%–3.39% accuracy drop. We define a new metric, gain-loss ratio (GLR), which quantitatively evaluates the capability of a DNN training hardware in terms of the model accuracy and hardware efficiency. The results of our comparison show that the aggressive task-mapping scheme on MIV-based 3D-ReG outperforms the other methods.

Study on Energy Spectrum Instability in the Processes of Propagating and Breaking of Focusing Waves

Based on phase focusing theory, focusing waves with different spectral types and breaking severities were generated in a wave flume. The time series of surface elevation fluctuation along the flume were obtained by utilizing 22 wave probes mounted along the mid-stream of the flume. Based on the wave spectrum obtained using fast Fourier transform (FFT), the instability characteristics of the energy spectrum were reported in this paper. By analyzing the variation of total spectral energy, the total spectral energy after wave breaking was found to clearly decrease, and the loss value and ratio gradually increased and tended to stabilize with the enhancement of breaking severity for different spectral types. When wave breaking occurred, the energy loss was primarily in a high-frequency range of f/fp>1.0, and energy gain was primarily in a low-frequency range of f/fp<1.0. As the breaking severity increased, the energy gain-loss ratio decreased gradually, which demonstrates that the energy was mostly dissipated. For plunging waves, the energy gain-loss ratio reached 24% for the constant wave steepness (CWS) spectrum, and was slightly larger at approximately 30% for the constant wave amplitude (CWA) spectrum, and was the largest at approximately 42% for the Pierson-Moskowitz (PM) spectrum.

小尺寸环形气体激光器增益损耗比特性

小尺寸环形气体激光器增益损耗比特性

Tunable Fano resonances via optomechanical effect and gain–loss ratio in coupled microresonators

We propose a system consisting of two coupled optical whispering-gallery-mode (WGM) microresonators to investigate the Fano resonances of the output probe field. The WGM microresonators are driven coherently by a strong pump field and a weak probe field via tapered fibers (Peng et al 2014 Nat. Phys. 10 394). By making one of the resonators optomechanical and properly adjusting the coupling strength between the microresonators, we tune the Fano line shapes by varying the optomechanical strength. It is found that Fano line shapes appear on introducing optomechanical effects into the system. Interestingly enough, the gain–loss ratio in the proposed system has a key role in tuning a single Fano line shape to double. For the -symmetric phase, we investigate a more prominent double Fano line shape. The adjustment from single Fano line shape to double via the gain–loss ratio is the major part of this work. Our results can be used for all-optical switching and high-sensitivity sensing.

Computing the Substantial-Gain–Loss-Ratio

The Substantial-Gain–Loss-Ratio (SGLR) was developed to overcome some drawbacks of the Gain–Loss-Ratio (GLR) as proposed by Bernardo and Ledoit (J Polit Econ 108(1):144–172, 2000). This is achieved by slightly changing the condition for a good-deal, i.e. on the most extreme but at the same time very small part of the state space. As an empirical performance measure the SGLR can naturally handle outliers and is not easily manipulated. Additionally, the robustness of performance is illuminated via so-called $$\beta $$ -diagrams. In the present paper we propose an algorithm for the computation of the SGLR in empirical applications and discuss its potential usage for theoretical models as well. Finally, we present two exemplary applications of an SGLR-analysis on historic returns.

An Improvement of Gain-Loss Price Bounds on Options Based on Binomial Tree and Market-Implied Risk-Neutral Distribution

This paper investigates the approximated arbitrage bounds of option prices in an incomplete market setting and draws implications for option pricing and risk management. It gives consideration to periods of global financial crisis and European sovereign debt crisis. To this end, we employ the gain-loss ratio method combined with the market-implied risk-neutral distribution calculated by binomial tree to investigate the options price bounds. Our implied gain-loss bounds of option prices are preference-free and parametric-free to avoid the misspecification error of subjective choice on the benchmark model of gain-loss ratio, and consequently, greatly reduce model risk and market risk. The empirical results show that there are option prices breaking the gain-loss bounds, even after taking into account the market information. This means that a good risk management technique and good-deal investment opportunities exist if the implied binomial tree is used as a benchmark model in the gain-loss bounds.

Multi-criteria robust optimization framework for bridge adaptation under climate change

In order to adapt civil infrastructure to changing climate conditions, quantifiable and deep uncertainties must be integrated into the decision-making process. The quantifiable uncertainties, i.e. variability for which a likelihood can be defined, are typically integrated into the management process by considering the reliability or risk level of a structure. The deep uncertainties, i.e. the variability for which a likelihood cannot be defined, are beginning to be integrated in the decision making process as a few robust decision making procedures have been proposed. However, the deep uncertainty associated with the multiple feasible future climate scenarios also provokes a “wait and see” mentality for some decision makers, causing the flexibility of a strategy to be valued. This paper introduces the Gain-Loss Ratio (GLR) as a metric that systematically quantifies what may be gained by postponing adaptation while also considering what is lost with the delay. Additionally, bi-objective optimization models for optimizing bridge adaptation strategies under deep uncertainties are proposed; the advantages and disadvantages of each are highlighted as they pertain to the management of a typical riverine bridge. Two rivers are considered that have comparable climate change trends as those predicted for the Columbia and Mississippi Rivers. It is demonstrated that the desire for flexibility may be justified for certain locations, but may be detrimental in others.

The Escalation of Commitment and Disposition Effect in Securities Trading: An Experimental Study

This paper investigates the relationship between disposition effect and escalation of commitment in securities trading. First, we developed an investment simulation system, that manipulated five stocks' price during thirty-six periods to test investors' behavioral patterns in securities trading. Then, we investigate whether the gain ratio or loss ratio impacts on disposition effect and escalation of commitment after controlling other variables. The results summarized as follow: First, investors are exhibited disposition effect and escalation of commitment in securities trading. Second, sex, education, duration of securities trading, and investment amount did not affect the disposition effect and escalation of commitment. Third, disposition effect and escalation of commitment has negative impact on performance. Finally, we find individual investors with stronger disposition effect are more likely to be escalated in securities trading.

A commuter departure-time model based on cumulative prospect theory

With a focus on planning of departure times during peak hours for commuters, an optimal arrival-time choice is derived using cumulative prospect theory. The model is able to explain the influence of behavioral characteristics on the choice of departure time. First, optimal solutions are derived explicitly for both early and late-arrival prospects. It is shown that the optimal solution is a function of a subjective measure, namely, the gain–loss ratio (GLR), indicating that the actual arrival time of a commuter depends on his or her attitude to the deviation between gains and losses. Some properties of the optimal solution and the GLR are discussed. These properties suggest that the more that the pleasure of gain exceeds the pain of loss, the greater the correlation between actual and preferred arrival times. Finally, a sensitivity analysis of the results is performed, and the use of the model is illustrated with a numerical example based on a skew-normal distribution.