Large Returns Research Articles

Performance Evaluation, Factor Models, and Portfolio Strategies: Evidence from Chinese Mutual Funds

Actively managed stock mutual funds in the Chinese A-share market offer good investment opportunities. In aggregate, they outperform stock market indexes. Individual funds show a wide cross-sectional dispersion in performance, with the best funds offering economically large risk-adjusted returns that persist over time. Performance persistence observed at the individual fund level is robust to various factor-model specifications. A portfolio of the top-performing funds offers an improved investment opportunity compared with a portfolio of all funds. Hedging out market risk in this portfolio increases the Sharpe ratio, lowers volatility, and reduces tail risk. These results suggest that, in the young and still-developing Chinese A-share market, mutual funds can add value for investors.

Bivariate statistics of floating offshore wind turbine dynamic response under operational conditions

FOWT (Floating offshore wind turbines) belong to the modern offshore wind energy industry generating green renewable energy. Accurate extreme loads and response prediction during power generation is an important design concern. More accurate and reliable estimations of extreme responses are significant for the offshore wind industry as it advances the design, manufacturing and deployment of large FOWTs in the coming decade. In this study, the OpenFAST code was used to model offshore wind turbine mooring line tension force and blade bending moment due to environmental loads, acting on a site-specific FOWT under realistic local environmental conditions. This paper presents an efficient Monte Carlo based method to study bivariate extreme dynamic response statistics. The ACER2D (bivariate average conditional exceedance rate) method is briefly discussed. The ACER2D method enables robust estimation of bivariate statistics, efficiently utilizing available data. Large return period 2D (two-dimensional) probability contours were obtained using the ACER2D method. Based on the studied performance of the presented methodology, it was seen that ACER2D provides accurate and efficient predictions of extreme return period contours.The described approach may be utilized at the design stage, defining optimal FOWT design values to minimize potential structural damage due to extreme environmental loads. It should be noted that the bivariate design point is less conservative than the classic univariate one; therefore, this study advocates a design method leading to lower structural production costs.

Optimal control strategy of global return power based on soft switching under triple phase-shift control

Return power and soft switching are important performance indicators for dual active bridge DC-DC converters (DAB). Aiming at the problem that the DAB converter has a large return power under the traditional control strategy, a control strategy that optimizes the return power in the full power range is proposed, and on this basis, the soft switching range of the switching device is increased. The control strategy not only ensures the minimum return power in the entire power range, but also increases the soft switching range, reduces the switching loss, and further improves the efficiency. Finally, an experimental platform is built for verification, and the experimental results verify the validity of the theoretical analysis.

Stock Market Reaction to Recessions and Buying the Dips

Using monthly stock-market data covering 150 years from 1871–2021, this article estimates the stock market’s reaction to recessions and analyzes whether recessions create buying opportunities. The stock market has overreacted to recessions. The overreaction is of large magnitude and fairly consistent. Buying stocks at the trough price, therefore, would produce a large above-normal return. Buying the dips based on a simple percentage-drop rule, however, fails to produce an above-normal return, because the peak-to-trough decrease in stock prices reflects enough market fundamentals to deny an easy profit. Whether a more sophisticated trading strategy can produce a sizable and consistent profit is an open question.

Crystal structure and microwave dielectric properties of garnet-type Ca2YZr2-xTixAl3O12 ceramics for dual-band bandpass filters

Microwave dielectric ceramics with a high-quality factor are vital materials for substrates, dielectric resonators, and filters in millimeter-wave communication systems. Here, a novel microwave dielectric ceramic based on a garnet-type Ca2YZr2Al3O12 compound for bandpass filter was prepared using the solid-state reaction method. Sintering the Ca2YZr2Al3O12 ceramics at 1600 ℃ for 5 h resulted in excellent microwave dielectric properties of εr = 10.81 ± 0.16, Qf = 87,628 ± 4000 GHz and τf = −34.3 ± 0.5 ppm/℃. Increasing the Ti4+ content of the Ca2YZr2-xTixAl3O12 ceramics significantly improved the sintering process. Superior microwave dielectric properties (εr = 11.93 ± 0.15, Qf = 121,930 ± 2600 GHz and τf = −30.8 ± 0.4 ppm/℃) were obtained for Ca2YZr2-xTixAl3O12 (x = 0.3) because of its dense microstructure, large grain size and high lattice energy. The Ca2YZr2-xTixAl3O12 (x = 0.3) ceramics were used to fabricate a dual-band bandpass filter with a hairpin structure that exhibited a large return loss (|S11| > 12 dB) and a small insertion loss (|S21| < 0.73 dB). The high performance of the Ca2YZr2-xTixAl3O12 ceramics and the corresponding bandpass filter makes this material a potential candidate for millimeter-wave devices.

Contactless Electrocatheter Tracing within Human Body via Magnetic Sensing: A Feasibility Study.

During surgical procedures, real-time estimation of the current position of a metal lead within the patient’s body is obtained by radiographic imaging. The inherent opacity of metal objects allows their visualization using X-ray fluoroscopic devices. Although fluoroscopy uses reduced radiation intensities, the overall X-ray dose delivered during prolonged exposure times poses risks to the safety of patients and physicians. This study proposes a potential alternative to real-time visualization of a lead inside the human body. In principle, by making a weak current flow through the lead and measuring the related magnetic field generated outside the body, it is possible to trace the position of the lead. This hypothesis was verified experimentally via two tests: one carried out on a curved copper wire in air and one carried out on a real pacemaker lead in a saline solution. In the second test, a pacemaker lead and a large return electrode were placed in a tank filled with a saline solution that reproduced the mean resistivity of the human torso. In both tests, a current flowed through the lead, which consisted of square pulses with short duration, to avoid any neuro-muscular stimulation effects in a real scenario. A small coil with a ferrite core was moved along a grid of points over a plastic sheet and placed just above the lead to sample the spatial amplitude distribution of the magnetic induction field produced by the lead. For each measurement point, the main coil axis was oriented along the x and y axes of the plane to estimate the related components of the magnetic induction field. The two matrices of measurements along the x and y axes were further processed to obtain an estimate of lead positioning. The preliminary results of this study support the scientific hypothesis since the positions of the leads were accurately estimated. This encourages to deepen the investigation and overcome some limitations of this feasibility study.

Innovation and Strategic Network Formation

Abstract We study a model of innovation with a large number of firms that create new technologies by combining several discrete ideas. These ideas are created via private investment and spread between firms. Firms face a choice between secrecy, which protects existing intellectual property, and openness, which facilitates learning from others. Their decisions determine interaction rates between firms, and these interaction rates enter our model as link probabilities in a learning network. Higher interaction rates impose both positive and negative externalities, as there is more learning but also more competition. We show that the equilibrium learning network is at a critical threshold between sparse and dense networks. At equilibrium, the positive externality from interaction dominates: the innovation rate and welfare would be dramatically higher if the network were denser. So there are large returns to increasing interaction rates above the critical threshold. Nevertheless, several natural types of interventions fail to move the equilibrium away from criticality. One effective policy solution is to introduce informational intermediaries, such as public innovators who do not have incentives to be secretive. These intermediaries can facilitate a high-innovation equilibrium by transmitting ideas from one private firm to another.

Time-varying risk of nominal bonds: How important are macroeconomic shocks?

I study the sufficiency of macroeconomic information to explain the time-variation in second moments of stock and bond returns, with a particular attention to stock-bond correlations. I propose an external habit model supplemented with realistic non-Gaussian fundamentals estimated solely from macroeconomic data. Intertemporal smoothing and precautionary savings effects – driven by consumption shocks – combine with a time-varying covariance between consumption and inflation to generate large positive and negative stock-bond return correlations. Macroeconomic shocks are most important in explaining second moments of stock and bond returns from the late 1970’s to mid-1990’s and during the Great Recession.

State Regulation of Housing and Communal Services of the Russian Federation: Centralization of Management or Market Self-Regulation

This article discusses the proposed measures of the Ministry of Construction and Housing and Communal Services of the Russian Federation, set out in the draft strategy for the development of the construction industry and housing and communal services, which received a disapproving response from some experts in the media. The article analyzes the regulatory documents regulating the activities of management organizations in the housing and communal services market. According to the results of the analysis carried out by the author, it was found that state regulation of the industry in question only through laws and by-laws is currently insufficient. The initiative of the Ministry of Construction of the Russian Federation related to the introduction of a regional operator (guaranteeing management organization) into business practice is justified by the author of the article from an organizational, managerial, and economic point of view. In particular, it is proposed to expand the subject-object relations between the state and the management organization in the management system to subject-subject relations between the regional operator (guaranteeing management organization) and consumers of housing and communal services. From an economic point of view, the proposals of the Ministry of Construction of Russia may be economically beneficial for both sides: the state receives a large return on budgets of different levels by changing the taxation system (from simplified to general) and the corresponding tax rate, and management organizations receive a large profit by increasing the profitability of their professional activities by 1.5–2 times. As a result, the author comes to the conclusion that the measures proposed by the Ministry of Construction of Russia are necessary and non-discriminatory, since the relationship between the management organization and consumers of housing and communal services is carried out on market principles and in a competitive environment, and the administration of processes by the state regarding the selection of management organizations for the provision of housing and communal services to the population does not infringe on the rights of economic entities to carry out any legitimate economic activity.

Long-term dynamics of forage base and food supply for nekton in the upper epipelagic layer of the western Bering Sea. Part 2. Food supply for nekton

Interannual dynamics of feeding conditions for nekton in the upper epipelagic layer of the western Bering Sea is considered for the summer and fall seasons of 2002–2020. In the summers, daily consumption by fish and squids ranged from 0.01 to 0.10 t/km2 in the deepwater basins and between 0.01–0.38 t/km2 in the shelf area at Cape Navarin. In the falls, the consumption increased to 0.03–0.14 t/km2 in the deep-water basins, and to 0.01–0.53 t/km2 in the Navarin area. Summary in the summer-fall periods, the fish and squids consumed 2–5 % of zooplankton production (up to 5–7 % in some years) in the deep-sea basins that is rather low degree of the zooplankton resources usage. In the Navarin area, the consumption is considerably higher and is estimated as 5 % in summer and 21 % in fall season, on average. In cases of heightened nekton biomass and reduced zooplankton biomass in some years, the grazing pressure on plankton increased, in particular on euphausiids, hyperiids and pteropods, while the intensity of salmon feeding decreased, with extension the portions of nektonic food and other zooplankton groups, as arrowworms, in their diet. On the other hand, the portion of juvenile fish and squids in the salmon diet increased in cases of high abundance of this prey, too. Weak correlation was detected both between the salmon feeding and abundance of their prey and between the salmon feeding and abundance of salmons. The feeding conditions for pink salmon during their offshore migration did not determine the rate of their returns. Strong year-classes of pink salmon had large returns in conditions of either poor or rich food supply in fall season, so the feeding in fall was not important for the pink salmon survival in the ocean in winter. Feeding of other fish and squids species did not change noticeably in the years with reduced food supply. In general, abundance and species composition of plankton and nekton communities were rather stable in the western Bering Sea in the 2000-2010s, and this current state of the ecosystem provides stable functioning of nekton communities both in the deepwater and Navarin areas.

Classification of brain tumours using artificial neural networks

&lt;p&gt;Magnetic Resonance (MR) brain Image is very important for medial analysis and diagnosis. These images are generally measured in radiology department to measure images of anatomy as well as the general physiological process of the human body. In this process magnetic resonance imaging measurement are used with a heavy magnetic field, its gradients along with radio waves to produce the pictures of human organs. MR brain image is also used to identify any blood clots or damaged blood veins in the brain. A counterfeit neural organization is a nonlinear information handling model that have been effectively used preparation models for tackling administered design acknowledgment assignments because of its capacity to sum up this present reality issues. Artificial Neural Networks (ANN) is used to classify the given MR brain image having Benign or Malignant tumour in the brain. Benign tumours are generally not cancerous tumours. These are also not able to grow or spread in the human body. In very rare cases they may grow very slowly. Once it is eliminated, they do not come again. On the other hand, Malignant tumours are cancer tumours. These tumour cells are grown and also easily spread to other parts of the human body. Benign also known as Harmless. These are not destructive. They either can't spread or develop, or they do as such leisurely. On the off chance that a specialist eliminates them, they don't by and large return. Premalignant In these growths, the cells are not yet harmful, however they can possibly become threatening. Malignant also known as threatening. Malignant growths are destructive. The cells can develop and spread to different pieces of the body. In our proposed framework initially, it distinguishes Wavelet Transform to separate the highlights from the picture. Subsequent to separating the highlights it incorporates tumour shape and power attributes just as surface highlights are distinguished. Finally, ANN to group the information highlights set into Benign or Malignant tumour. The main purpose as well as the objective is to identifying the tumours weather it belongs to Benign or Malignant.&lt;/p&gt;

Genetic Mean Reversion Strategy for Online Portfolio Selection with Transaction Costs

Online portfolio selection (OLPS) is a procedure for allocating portfolio assets using only past information to maximize an expected return. There have been successful mean reversion strategies that have achieved large excess returns on the traditional OLPS benchmark datasets. We propose a genetic mean reversion strategy that evolves a population of portfolio vectors using a hybrid genetic algorithm. Each vector represents the proportion of the portfolio assets, and our strategy chooses the best vector in terms of the expected returns on every trading day. To test our strategy, we used the price information of the S&amp;P 500 constituents from 2000 to 2017 and compared various strategies for online portfolio selection. Our hybrid genetic framework successfully evolved the portfolio vectors; therefore, our strategy outperformed the other strategies when explicit or implicit transaction costs were incurred.

Pakistan: a study of market's returns and anomalies

Purpose This paper aims to expand foreign investors' understanding of potential return enhancement and risk diversification advantages offered by equity market of Pakistan through comparing its performance to performances in other markets and investigating what matters for investing in Pakistan's market.Design/methodology/approachComparative analysis of Pakistan Stock Exchange is performed using data for 22 developed and 22 emerging markets over the period 1993–2019. Cross-sectional analysis is performed using data for 130 non-financial firms from Pakistan and Carhart (1997) and Fama and French (2015) models are applied. The role of liquidity with five-factor model is analyzed using turnover rate and Amihud (2002) illiquidity cost as liquidity measures.FindingsPakistan's equity offers substantial diversification benefits if added to developed market portfolios. However, observed large returns come together with inverted premia for most traditional factors indicating that investors may want to invest preferably in big stocks with low book-to-market and momentum. Finally, global investors can invest in high yielding stocks with low liquidity risk owing to positive connection between liquidity and returns.Practical implicationsThis study will provide investment model for foreign investors to enhance their portfolio returns. Policy makers in Pakistan must identify regulatory steps to facilitate foreign investments.Originality/valueTo the best of the authors' knowledge, this is the first study which identifies efficiency gains offered by Pakistan's equity for global investors.

Best practices for building and curating databases for comparative analyses.

Comparative analyses have a long history of macro-ecological and -evolutionary approaches to understand structure, function, mechanism and constraint. As the pace of science accelerates, there is ever-increasing access to diverse types of data and open access databases that are enabling and inspiring new research. Whether conducting a species-level trait-based analysis or a formal meta-analysis of study effect sizes, comparative approaches share a common reliance on reliable, carefully curated databases. Unlike many scientific endeavors, building a database is a process that many researchers undertake infrequently and in which we are not formally trained. This Commentary provides an introduction to building databases for comparative analyses and highlights challenges and solutions that the authors of this Commentary have faced in their own experiences. We focus on four major tips: (1)carefully strategizing the literature search; (2)structuring databases for multiple use; (3)establishing version control within (and beyond) your study; and (4)the importance of making databases accessible. We highlight how one's approach to these tasks often depends on the goal of the study and the nature of the data. Finally, we assert that the curation of single-question databases has several disadvantages: it limits the possibility of using databases for multiple purposes and decreases efficiency due to independent researchers repeatedly sifting through large volumes of raw information. We argue that curating databases that are broader than one research question can provide a large return on investment, and that research fields could increase efficiency if community curation of databases was established.

Gauging the effect of investor overconfidence on trading volume from the perspective of the relationship between lagged stock returns and current trading volume

AbstractIs investor overconfidence a major source of stock‐market trading volume? This study refers to the work of Grossman and Odean, introduces the assumption of investor overconfidence and empirically examines the influence of investor overconfidence on market trading volume in China's A‐share market through a vector autoregressive model estimation and Granger causality test. We find that overconfidence and self‐attribution exist in China's A‐share market. When the market is on an upswing, investors attribute large returns to the accuracy of their private information and the quality of their investment abilities; thus they trade more frequently, causing trading volume to increase more quickly. Conversely, when the market is on a downswing, investors attribute their investment losses to uncontrollable external factors; thus they become unwilling to trade, causing trading volume to shrink rapidly.

Extreme riser experimental loads caused by sea currents in the Gulf of Eilat

Risers are widely used in offshore industry and are subjected to dynamic environmental loads. Robust prediction of extreme riser external loading under the action of sea currents and subsequently VIV (vortex-induced vibrations) is an important safety concern for various offshore installations, for example TLP (Tension Leg Platform) and FPSO (Floating Production Storage and Offloading Unit). Excessive loading acting on riser may occur during offshore operations, posing an operational risk. In this paper, experimental results were used to study hydrodynamic current loads, acting on a riser under actual sea conditions.This paper presents methodology for estimating extreme loads, based on laboratory measurements. The ACER (averaged conditional exceedance rate) method has been briefly presented. Suggested methodology provides accurate extreme value predictions, utilizing available measured data efficiently. In this study estimated extreme value prediction, corresponding to a relatively large return period, was obtained by ACER method, based on the in situ sea current environmental statistics input. Based on the overall performance of the suggested method, it was concluded that ACER method can incorporate environmental input and provide robust and accurate prediction based on experimental measurements.Data de-clustering issue has been briefly addressed. Paper highlights ACER method ability to have environmental statistical distribution as an input, as required in long term statistical analysis. Described approach may be well used at the riser design stage, while defining optimal riser parameters that would minimize potential riser damage.

Non-equilibrium skewness, market crises, and option pricing: Non-linear Langevin model of markets with supersymmetry

This paper presents a tractable model of non-linear dynamics of market returns using a Langevin approach. Due to non-linearity of an interaction potential, the model admits regimes of both small and large return fluctuations. Langevin dynamics are mapped onto an equivalent quantum mechanical (QM) system. Borrowing ideas from supersymmetric quantum mechanics (SUSY QM), a parameterized ground state wave function (WF) of this QM system is used as a direct input to the model, which also fixes a non-linear Langevin potential. Using a two-component Gaussian mixture as a ground state WF with an asymmetric double well potential produces a tractable low-parametric model with interpretable parameters, referred to as the NES (Non-Equilibrium Skew) model. Supersymmetry (SUSY) is then used to find time-dependent solutions of the model in an analytically tractable way. Additional approximations give rise to a final practical version of the NES model, where real-measure and risk-neutral return distributions are given by three component Gaussian mixtures. This produces a closed-form approximation for option pricing in the NES model by a mixture of three Black–Scholes prices, providing accurate calibration to option prices for either benign or distressed market environments, while using only a single volatility parameter. These results stand in stark contrast to the most of other option pricing models such as local, stochastic, or rough volatility models that need more complex specifications of noise to fit the market data.

Does bitcoin liquidity resemble the liquidity of other financial assets?

Bitcoin is becoming a popular financial asset and means of transacting. However, little is known about an important aspect of the bitcoin market: its liquidity. We consider whether various dimensions of liquidity evident in other asset classes are present in bitcoin spot and futures liquidity. We find variations in spot liquidity across bitcoin exchanges and a strong commonality in bitcoin spot and futures market liquidity. The pricing of spot and futures bitcoin is relatively inefficient, and liquidity plays an important role. Deterioration in liquidity also contributes to bitcoin crash risk and large return declines. JEL Classification: G11, G23

Manufacturing-remanufacturing systems with uncertain return: production control with estimation-in-the-loop

Production control problem for failure-prone systems that utilize both manufacturing and remanufacturing in production processes and are subject to return uncertainty and variability is studied. Proposed feedback control policies are based on the imprecise measurements. The return flow is unknown and its rate is composed of seasonal and random components. To cope with measurement errors and return variability, estimation and forecasting modules are designed and incorporated into a control loop. Market demand is supposed to be constant although may contain an unknown component (much smaller than the return). Kalman filter technique is used for estimating inventory levels and return rate online from noisy inventory measurements. Obtained estimates are used in production control procedure ensuring that the policy continuously adapts to current market conditions. The system behavior under large return rate variations is studied and cost effectiveness of the proposed policies is demonstrated.

A trend factor in commodity futures markets: Any economic gains from using information over investment horizons?

AbstractThis paper identifies a trend factor that exploits the short‐, intermediate‐, and long‐run moving averages of settlement prices in commodity futures markets. The trend factor generates statistically and economically large returns during the post‐financialization period 2004–2020. It outperforms the well‐known momentum factor by more than nine times the Sharpe ratio and has less downside risk. The trend factor cannot be explained by the existing factor models and is priced cross‐sectionally. Finally, we find that the trend factor is correlated with funding liquidity measured by the TED spread. Overall, the results indicate that there are significant economic gains from using the information on historical prices in commodity futures markets.