Double Sorting Research Articles

Does short-term momentum exist in China?

Medhat and Schmeling (2022) find significant short-term reversal among low-turnover stocks and short-term momentum among high-turnover stocks by double sorting on stocks’ previous month’s return and share turnover. We replicate their research in the Chinese stock market and find that there is no short-term momentum but only short-term reversal exists in that market. A lack of volume that affects the ability of realized returns to predict firms’ fundamentals or investor heterogeneity might cause the absence of short-term momentum in China.

Overreaction and momentum in the Vietnamese stock market

PurposeAlthough the solid empirical proof of momentum is documented in various stock markets, there are many debates among academics with respect to the source of momentum profit. The first aim of this paper is intensively re-examine the momentum profit in Vietnam, an important emerging market. Secondly, the authors study the return predictability of a measure of investors’ overreaction, then examine whether the momentum effect in Vietnam is explained by overreaction.Design/methodology/approachUsing the weekly data of more than 300 non-financial Vietnamese stocks during 2009–2019, the authors build a measure of investors’ overreaction, which is based on trading volume and the sign of stock returns. Consequently, to investigate whether momentum exits after controlling for overreaction, the authors carefully compare trading strategies based on overreaction with price momentum strategies using adjusted returns and double sorts on past returns and levels of overreaction.FindingsThe article makes three main findings. Firstly, the authors discover the empirical evidence of momentum in the Vietnamese equity market. Secondly, the measure of overreaction could be a predictor of Vietnamese stock returns. Stocks that have experienced a stronger upward overreaction provide a higher average return. Finally, returns on trading strategies based on overreaction are robust after adjusting for momentum, while returns on momentum portfolios become insignificant after adjusting for overreaction. By double-sorting, the authors document that holding past returns constant, the average returns of portfolios rise monotonically with their measure of overreaction. Hence, the momentum profit in Vietnam arises from investors’ overreaction.Originality/valueThe paper extends previous research on the behavioral explanation of momentum in emerging stock markets, which has not been fully exploited in the literature.

Fast Location and Recognition of Green Apple Based on RGB-D Image.

In the process of green apple harvesting or yield estimation, affected by the factors, such as fruit color, light, and orchard environment, the accurate recognition and fast location of the target fruit brings tremendous challenges to the vision system. In this article, we improve a density peak cluster segmentation algorithm for RGB images with the help of a gradient field of depth images to locate and recognize target fruit. Specifically, the image depth information is adopted to analyze the gradient field of the target image. The vorticity center and two-dimensional plane projection are constructed to realize the accurate center location. Next, an optimized density peak clustering algorithm is applied to segment the target image, where a kernel density estimation is utilized to optimize the segmentation algorithm, and a double sort algorithm is applied to efficiently obtain the accurate segmentation area of the target image. Finally, the segmentation area with the circle center is the target fruit area, and the maximum value method is employed to determine the radius. The above two results are merged to achieve the contour fitting of the target fruits. The novel method is designed without iteration, classifier, and several samples, which has greatly improved operating efficiency. The experimental results show that the presented method significantly improves accuracy and efficiency. Meanwhile, this new method deserves further promotion.

A Behavior Perspective of Distress Anomaly: Evidence From Overnight Returns

Using measurement of overnight returns, this article documents that trading behaviors due to information shocks and investor sentiments contribute to distress anomaly. We find that stocks with the highest (lowest) overnight returns are accompanied with the greatest (smallest) distress risk premium, and accordingly, a conditional distress probability portfolio composed with double sort of overnight returns and distress probability would yield significant profitability. The regression outcomes demonstrate that probability of default significantly interacts with average overnight returns in explaining the future stock returns. The conventional distress anomaly is subsumed by the conditional distress factor, but not vice versa; and only profits of conventional distress-probability portfolios, not of the conditional portfolios, mainly come from stocks with characteristics that are associated with stock mispricing. The empirical results indicate that investors hold distressed stocks longer than expected because positive information shocks occur with high level of information supply and good information quality.

Pairs trading and asset pricing

Existing work on pairs trading do not detail how the variables selected explain the cross section of stock returns. We evaluate whether these variables contribute to the dynamics of the equity risk premium for a broadly diversified portfolio of Chinese stocks. Based on pairs trading strategy, several arbitrage-related factors are proposed. In an equilibrium exchange economy, where the idiosyncratic component of the stock return is modeled as per the Ornstein-Uhlenbeck process, the equity risk premium is obtained from a consumption-based asset pricing model. Sorting individual stocks into portfolios based on a single factor, a long-short strategy is formed by buying and selling stocks in the highest and lowest quintiles, respectively. The differences in the subsequent extreme portfolio return are economically large and highly statistically significant. These differences remain significant after controlling for other documented firm characteristics and explanatory variables in the Fama-Macbeth regressions and double sorting.

Hematopoietic Stem Cell Potential within the Primary Sorted Lineage Positive Population: What Are We Losing with Hematopoietic Stem Cell Purification?

Lineage positive cells within murine whole bone marrow (WBM) are classically considered to be devoid of stem cell capacity. As such, lineage depletion prior to further selection for stem cell marker positive, lineage negative cells dominates virtually all hematopoietic stem cell (HSC) purification protocols. Here, we present data showing a significant population of long-term multi-lineage hematopoietic stem cells within the primary sorted lineage positive (Lin+) murine marrow population. Using limiting dilution competitive bone marrow transplantation assays, we found significant long-term multi-lineage engraftment capacity within the total primary sorted Lin+ population (cells positive for erythroid (TER119), myeloid (GR1, CD11b) or lymphoid (B220, CD4, CD8) markers). When 0.25 x 106 Lin+ cells were competed against 1 x 106 competitor WBM cells, average percent donor chimerism in recipient mice at 6 months post-transplant was 7.2% ± 2.9%. Donor chimerism was multi-lineage. There was still 1.9% ± 0.5% donor chimerism when only 62,500 primary sorted Lin+ cells were competed against 1 x 106 competitor WBM cells at 3 months post transplant, and further limiting dilution assays are ongoing to quantitate the stem cell compartment within the primary sorted Lin+ population. These levels of engraftment were similar to that found within un-separated donor WBM at the same dilutions, and multi-lineage engraftment capacity within the primary sorted Lin+ population persisted in secondary transplant. When further sub-fractionated into erythroid, myeloid or lymphoid sub-populations, every primary sorted individual sub-population contained long-term multi-lineage engraftment capacity at 6 months post transplant. Primary sorts were between 96-97.5% pure. When primary Lin+ sub-sets (B220+ cells, GR1+ cells, or CD11b+ cells) were double sorted, there was loss of engraftment potential within the double sorted persistently positive Lin+ subsets, but surprisingly high engraftment within those cells negative for only the single Lin+ marker on double sort (31%-59% donor chimerism at 6mo post-transplant; 1 x 105 donor cells + 3 x 105 competitor WBM cells). Immunophenotype analysis showed that these populations were not enriched in c-Kit+/Sca-1+/CD150+ cells. The high engraftment capacity of cells within the primary sorted Lin+ population, further isolated solely based on their being negative for a single Lin+ marker on the double sort prompted us to directly compare their engraftment capacity to that of purified Lineage negative (Lin-) cells. Interestingly, although isolated solely based on the presence or absence of GR1 on double sort, we found that the average percent donor chimerism at 6 months post-transplant was equal between purified Lin- cells (58.3% ± 17%) and the population of GR1 positive cells that became negative for GR1 on double sort (58.3% ± 26%; 1 x 105 donor cells + 3 x 105 competitor WBM cells). Using tritiated thymidine suicide, we found that the stem cell activity within these populations isolated from the primary sorted Lin+ fraction was due to actively cycling cells. These data further indicate that the engraftment capacity within the primary sorted Lin+ population is not simply due to conventionally purified quiescent HSCs contaminating our primary sort. In sum, there is a cycling population of stem cells within the primary sorted Lin+ fraction that appears to be distinct from quiescent highly purified HSCs. As primary sorted Lin+ cells, routinely discarded in most HSC studies, comprise up to 98% of WBM, engraftment capacity within this population represents a potentially large and understudied stem cell population within WBM worthy of further characterization. Work is currently underway to further quantitate and define this population, and delineate how cell cycle-related changes influence the phenotype and function of this cycling murine HSC population. DisclosuresNo relevant conflicts of interest to declare.

Short-term Momentum

Abstract We document a striking pattern in U.S. and international stock returns: double sorting on the previous month’s return and share turnover reveals significant short-term reversal among low-turnover stocks, whereas high-turnover stocks exhibit short-term momentum. Short-term momentum is as profitable and as persistent as conventional price momentum. It survives transaction costs and is strongest among the largest, most liquid, and most extensively covered stocks. Our results are difficult to reconcile with models imposing strict rationality but are suggestive of an explanation based on some traders underappreciating the information conveyed by prices.

A Data Encryption and Approximate Recovery Strategy Based on Double Random Sorting and CGAN

The measurement data in the power system may be attacked and tampered during the transmission. For this problem, a data encryption and approximate recovery strategy based on double random sorting and CGAN is proposed. The double random sorting encryption algorithm is proposed based on the form of measurement data in plaintext. The randomness of pseudo-random number, random sequence and random sequence insertion will ensure the uncertainty of data block number, sorting order and insertion location of random sequence, which will definitely improve the security of measurement data. Besides, an approximate recovery strategy used to approximately recovery abnormal samples is proposed on the base of CGAN, which can ensure the accuracy of decryption. Finally, the feasibility, and effectiveness of the proposed method are analyzed on wind power and photovoltaic power historical dataset.

Size selectivity and catch efficiency of bottom trawl with a double sorting grid and diamond mesh codend in the North-east Atlantic gadoid fishery

This study investigated the size selectivity and catch efficiency in the North-east Atlantic demersal trawl fishery targeting cod (Gadus morhua) and haddock (Melanogrammus aeglefinus). The use of a sorting grid followed by a size selective codend is compulsory in this fishery. Experimental fishing was conducted with a commercially rigged trawl, flexigrid section, and diamond-mesh codend. The flexigrid section is a dual sorting system and all fish that escaped from the two grids in the flexigrid system and the codend were retained in separate covers. This allowed us to estimate the combined size selectivity of the system, as well as the separate contributions from the first grid, second grid, and codend. The catch efficiencies for cod and haddock below and above the minimum reference length (MRL) were quantified by estimating the values for a set of exploitation pattern indicators. The results showed that most fish escaped from the flexigrid section. Only a few fish below the MRL entered the codend and nearly all of them subsequently escaped through the codend meshes. The probability of retaining undersized cod and haddock was low with the combined system. Furthermore, the results showed that the probability of escape was high through the second grid in the system for fish above the MRL, and this finding was supported by the exploitation pattern indicators. In particular, the estimated exploitation pattern indicators showed that using the current MRL and the fish size distributions encountered during the trials, no haddock and only 2.3 % of cod below the MRL were retained by the gear. However, 77.4 % of the haddock and 16.0 % of the cod above the MRL were found to escape, thereby indicating poor catch efficiency, especially for haddock. These results demonstrate the importance of supplementing size selectivity research with estimates of the actual catch efficiency using the gear employed, which were quantified using exploitation pattern indicators in this study.

Investor Attention and Growth Anomalies in NASDAQ Stocks-Evidence from Google Trend Volume

We study the effects of investor attention on the capital investment anomaly on NASDAQ stocks. Based on total asset growth, researchers find firms that substantially increase capital investments subsequently achieve negative benchmark-adjusted returns. On one hand, some scholars propose that investors incorrectly underreact to the empire building behavior of managers who aggressively increase investment expenditure. On the other hand, some scholars argue that investors appear to overreact to past firm growth rates. We aim to determine whether the growth anomaly is due to underreaction or overreaction in this research. We apply Google Search Volume Index as a new direct measure of investor attention to provide empirical evidence for under-reaction and over-reaction explanations of the total asset growth anomaly on NASDAQ stocks. We adopt double sorting and Fama-MacBeth regression and find the stock prices rise up when investors search actively of the underlying stock tickers. The anomaly is stronger when investors are extremely overreacting and underreacting. When investors are rational or calm down, this total asset growth effect disappears. Our empirical design disentangles the dilemma that whether the strand of growth anomalies is due to risk or mispricing. Within proponents of mispricing, our research innovatively tease out of the opposing explanations of under-reaction and over-reaction as the relevant driver of the growth anomalies.

A lottery-preference-based explanation of realized kurtosis puzzle in Chinese stock market

ABSTRACTHigh kurtosis corresponds to fat tails on both sides and under risk-aversion assumption investors’ dislike of left-tail loss outweighs their preference for right-tail gain. Therefore, high kurtosis characteristic of stock should predict high expected returns. However, the high-frequency-data-based empirical results on Chinese stock market are just the opposite, which we refer to as the ‘realized kurtosis puzzle’. Using the double sorts and firm-level cross-sectional regression methods, we further demonstrate investors’ preference for lottery-like stocks or lottery preference is key to solve the puzzle. Our further empirical research verifies stocks with higher retail investors’ shareholding proportion and unavailable for short show stronger ‘realized kurtosis puzzle’. In addition, the puzzle is particularly significant in high lottery preference periods while less apparent in low lottery preference times.

Volatility-of-volatility and the cross-section of option returns

This paper presents a robust new finding of a significant negative relation between equity option returns and the volatility-of-volatility (VOV). After controlling for numerous existing option and stock characteristics, the VOV effect remains significantly negative. It also survives many robustness checks. A conceptual model provided reveals the pricing mechanism behind the VOV effect. The high-low return spread on option portfolios sorted on VOV cannot be explained by standard risk factors, and survives double sorting using a variety of control variables.

Currency strategies based on momentum, carry trade and skewness

This paper documents that momentum, carry trade, and skewness strategies do not contain exactly the same information, which inspires us to construct a novel, triple-screen strategy and test its profitability. We first investigate the properties of payoffs to the above three currency speculation strategies. We then conduct double sorting and cross-sectional regression analyses to disentangle these strategies and find that they are not completely overlapping. Finally, we combine the momentum, carry trade, and skewness strategies to create a triple-screen strategy. The results show that triple-screen strategies generally perform better than single- and double-screen strategies. Our empirical findings are also robust to subsamples (advanced, emerging, non-Euro and Group of Twenty economies). Our research findings provide experimental investigation on the effectiveness of combining momentum, carry trade, and skewness strategies, as well as ways to bring more benefits to investors.

System for Double Sorting of Atoms by Quantum State for a Commercial Hydrogen Frequency Standard

The basic structural features of a system of double sorting of atoms by quantum states within the limits of given constraints are considered. The system is included in the hydrogen generator of a commercial hydrogen frequency standard. Results of calculations of the trajectories of the atoms in a double sorting system are presented and the selection of a method of creating an inversion region is evaluated.

Estimation of the Possible Reduction of the Limit Frequency Instability of a Hydrogen Generator Using an Atom Beam in One Quantum State

An assessment of possible reduction of the limit frequency instability of a hydrogen generator is conducted when using a system of double sorting of hydrogen atoms by energy states. It is shown that when receiving a hydrogen atom beam in one quantum state, reduction of the frequency instability by approximately a factor of 1.6 to the value 1.8510–14 τ–1/2 is possible.

HaDaap: A hotness‐aware data placement strategy for improving storage efficiency in heterogeneous Hadoop clusters

SummaryEnterprises increasingly use the Hadoop Distributed File System (HDFS) to manage and store big data for many applications. However, HDFS uses triple replication, leading to staggering data center storage costs. As big data increases in volume and its heat levels becomes more sensitive, there comes a point where storing so much cold data actually makes it less accessible and more expensive. Meanwhile, as data centers expand, the heterogeneity of nodes also becomes an issue. Rack‐aware data placement adopted by HDFS results in an unbalanced load and uneven resource allocation because it ignores the data nodes' heterogeneity. Here, we attempt to resolve these problems by proposing a hotness‐aware data placement strategy (named HaDaap). In HaDaap, the first step is to use a hotness‐aware data clustering algorithm to set the data's degree of heat. Then, cold data (with a redundancy of erasure code) are placed through a Double Sort Exchange algorithm to reduce storage costs and increase data availability. Finally, hot data are placed via a dynamic replication placement mechanism that comprehensively factors availability, load, and storage costs. Experimental results show that with these enhancements, HaDaap uses resources rationally and substantially reduces storage costs by considering the difference of data hotness in heterogeneous Hadoop clusters.

Gross profitability and momentum

PurposeThe purpose of this paper is to examine the combined performance of momentum and a gross profitability-based strategy. The motivation stems from the strong performance of momentum on the short side and profitability on the long side, suggesting a potentially superior combined strategy. Gross profitability is also a measure of firm quality, so that another motivation is to contribute to a growing literature on factor-based investing that includes momentum and quality as potential factors.Design/methodology/approachThe empirical approach employed in the paper is standard in the asset pricing literature. The firms are sorted into portfolios based on profitability and momentum, and the combined performance is studied through independent double sorting. Both value-weighted and equally weighted returns are reported in case of key empirical results.FindingsThe combined strategy results in superior performance. Specifically, the strategy produces results 2.75 greater than the momentum strategy, and about four times as high as the profitability strategy. The strategy also has much higher Sharpe ratio that improves further when combined with size and value strategies.Research limitations/implicationsThe research has significant implications for academics and practitioners alike. A new investment strategy that has not been explored in the literature is presented. The superior performance of the strategy presents a challenge for the market efficiency, and would be of interest to academics and practitioners working in the area of investment management.Practical implicationsThere has been a growing interest in multi-factor investing in recent years. The paper documents that superior performance is achieved by combining two of the popular factors, namely profitability and momentum.Originality/valueThe research is the first to study the combined performance of profitability and momentum, and provide evidence on the superiority of the combined strategy.

Deep Learning and the Cross-Section of Stock Returns: Neural Networks Combining Price and Fundamental Information

Traditional empirical finance research uses hand-engineering and trial-and-error to look for the anomalies in the cross-section of stock returns. In this paper, we take advantage of deep learning and utilize both the price and fundamental information to separate stocks’ winners from losers. For the first model, we used a 2-layer Long Short-Term Memory (LSTM) neural network with past 80 days’ return information as inputs to predict the next day’s return and find a before-trading-cost monthly return of 29.58% with a t-statistic of 26.81. The return of the stocks shows a strong short-term reversal pattern. For the second model, we design a novel 2-layer LSTM and Multi-layer Perceptron (MLP) hybrid neural network and utilize the monthly return and annual accounting data to predict the returns in the next month. We achieve a monthly return of 2.37% with a t-statistic of 8.97 before trading cost from 1993 through 2017. We use TAQ intraday data to explicitly estimate the trading cost and find that profits of the daily trading strategy in the first model turn negative. However, the trading strategy utilizing both the price and fundamental information in the second model keeps significantly positive with a monthly return of 1.57% and t-statistic of 6.03 after the trading cost. We show that the 2-layer LSTM and MLP hybrid model performs better than the MLP-only and the hand-engineering momentum and short-term reversal double sort trading strategy.

Short-term Momentum

We document a striking pattern in U.S. and international stock returns: double sorting on the previous month’s return and share turnover reveals significant short-term reversal among low-turnover stocks, whereas high-turnover stocks exhibit short-term momentum. Short-term momentum is as profitable and as persistent as conventional price momentum. It survives transaction costs and is strongest among the largest, most liquid, and most extensively covered stocks. Our results are difficult to reconcile with models imposing strict rationality but are suggestive of an explanation based on some traders underappreciating the information conveyed by prices.

Portfolio turnover activity and mutual fund performance

PurposeThe purpose of this paper is to propose a new measure of portfolio activity, the modified turnover (MT), which represents the portion of the portfolio that the manager changes from one quarter to the next. Compared with the traditional turnover, the MT measure has a distinct interpretation, relies on portfolio holdings, includes the effects of flows and ignores the effects of offsetting trades.Design/methodology/approachUsing quarterly holdings data, the authors examine the relationship between fund turnover, performance, and flows for a sample of 2,856 actively managed mutual funds over the period 1991-2012. The authors provide numerical examples to illustrate how the suggested measure, MT, is different from the traditional turnover measure. The authors use panel regressions, simple and double sorts to examine the predictability of performance.FindingsThe authors find evidence that high MT predicts lower performance. The comparison between the highest and lowest quintiles sorted based on MT reveals a difference of −2.41 percent in the annual risk-adjusted return. Furthermore, high MT predicts lower net flows. The authors also find that MT relates positively to other activeness measures while volatility, flows, size, number of stocks, and the expense ratio are significant determinants of MT. Overall, the results suggest that frequent churning of a portfolio is value destroying for investors and signals a manager’s lack of skill.Originality/valueThe authors offer a simple measure, namely, MT, for estimating the fraction of a portfolio that changes from one quarter to the next. Armed with this tool, the authors investigate whether funds deviate from their previous quarter’s holdings because of valuable or noisy information, and whether such signals are exploited by fund investors.