Small-cap Stocks Research Articles

Separating the predictable part of returns with CNN-GRU-attention from inputs to predict stock returns

The noise and high randomness of the stock market are primary obstacles to profitability. These factors cause stock returns to consist of short-term predictable and stock-specific residual parts. Therefore, it is beneficial to separate and model the two items for forecasting returns in the randomness environment. On this basis, we propose a novel Temporal Return Separation and Restore Forecasting (TRSRF) method. TRSRF first extracts price- and relation-based features from historical stock inputs and uses them to decompose and restore predictable and residual elements of historical returns , respectively. Then it forecasts these components based on historical values. We conducted experiments on the Chinese small and mid-cap, blue-chip, and large-cap indexes over ten years to compare with seven proposed baselines. On the three Chinese indexes our method separately exceeds 6%, 16%, and 22% absolute annualized returns than our baseline. The ablation study also proves the necessity of return decomposition and inter-stock relation modeling. We find that modeling inter-stock relations on small-cap stocks works better than on large-cap stocks. Furthermore, we prove our method might be an implicit ensemble model of the predictable and residual parts, which is why it works stability under various market conditions.

Fraud risk implications of celebrity SPACs

Purpose The purpose of this study is to extend the Fraud Diamond Theory to celebrity Special Purpose Acquisition Companies (SPACs) and investigate their post-Initial Public Offering (IPO) stock market performance. Design/methodology/approach After obtaining a sample of celebrity SPACs from the Spacresearch.com database, fraud risk characteristics were obtained from Lexis Nexus searches. Buy and hold abnormal returns were calculated for celebrity SPACs versus a small-cap equity benchmark for time intervals after IPO, and multiple regression analysis was performed to examine the relationship between fraud risk features and post-IPO returns. Findings Celebrity SPACs exhibit Fraud Diamond characteristics and significantly underperform a small-cap stock portfolio on a risk-adjusted basis after IPO. Research limitations/implications This study only examines celebrity SPACs that conducted IPOs on the NYSE and NASDAQ/AMEX and does not include those that are traded on the Over the Counter Bulletin Board (OTCBB). Practical implications Celebrity endorsement of SPAC vehicles attracts investors who may not be properly informed regarding the risk characteristics of SPACs. Accordingly, investors should be warned that celebrity SPACs underperform a small-cap equity portfolio and exhibit significant elements of fraud risk. Social implications The use of celebrity endorsement as a marketing device to attract investment in SPACs has regulatory implications. Originality/value To the best of the authors’ knowledge, this paper is the first to examine the fraud risk characteristics and post-IPO performance of celebrity SPACs.

Can Investor Sentiment Explain the Abnormal Returns of Volatility-Managed Portfolio Strategy? Evidence from the Chinese Stock Market

ABSTRACT This study develops a theoretical model to capture volatility-managed portfolios’ risk-adjusted returns affected by investor sentiment, and uses Chinese A-share market data to analyze the volatility-managed effect based on the small-minus-big (SMB) factor and explain the abnormal returns of volatility-managed portfolios from the investor sentiment perspective. Our results show that the Sharpe ratio of the SMB factor significantly increases after volatility management, especially in low-sentiment periods. Moreover, the mechanism analysis shows that in low-sentiment periods, small-cap stock investors overreact to volatility compared to large-cap stock investors, making the SMB factor significantly positively correlated with lagged volatility. Additional analyses show that volatility-managed portfolios constructed through stocks with gambling characteristics can achieve higher abnormal returns, and the abnormal returns of volatility-managed portfolios cannot be corrected by arbitrage traders as arbitrage is ineffective, reflecting the immaturity of China’s emerging capital market.

Can the Sell in May effect be enhanced by a size tilt?

PurposeThe authors evaluate the Sell in May effect in the Canadian context to comprehensively explore the Sell in May effect as well as its interactions with the size effect and risk and with multiple indices.Design/methodology/approachThe authors use ordinary least squares (OLS) regressions to examine the Sell in May effect and Huber M-estimation to handle potential outliers. They also use the generalized autoregressive conditional heteroskedasticity (GARCH) models to explore the role of risk in the Sell in May effect.FindingsThe results demonstrate that the Sell in May effect is present in all three main Canadian stock market indices. More telling, the anomaly is strongest in small cap indices and in indices that give equal weighting to small and large cap stocks. They do not find that the effect is driven by risk.Originality/valueWhile several papers have explored the Sell in May phenomenon in several countries, little scholarly attention has been paid to this effect in Canada and to its interaction with the size effect. The authors contribute to the literature by examining of the interactions between Sell in May and the size effect in Canada. They examine the Sell in May effect using CFMRC value-weighted and equally weighted indices of all Canadian companies. They also incorporate in their analysis the role of risk.

Unveiling Social Traders' Herding Mentality: A Focus on Small-Cap Stocks within a Leading Social Trading Platform (STP)

Unveiling Social Traders' Herding Mentality: A Focus on Small-Cap Stocks within a Leading Social Trading Platform (STP)

Research on Optimizing Pension Planning Allocations

This article examines two ways of pension allocation, choosing the best opportunity mix based on Fama and the French three-factor model to maximize returns while satisfying each portfolio category and other investment conditions. The database used by the author is based on the excess returns of 8 different stocks from October 2018 to January 2022. This article studies the relationship between different stocks by calculating the variance, standard deviation and covariance of different stocks, and divides stocks into large-cap stocks, small-cap stocks, value stocks, and growth stocks. The author calculated the optimal Sharpe ratio. Empirical results show that the sharpe ratio value obtained from the investment portfolio can be concluded that when people live for more than 20 years after retirement, they can choose to receive pensions every year. If your life expectancy after retirement cannot reach 20 years, it is recommended to withdraw your pension in one lump sum. However, this article shows that results change when using different portfolio approaches because of data limitations.

Comparative Analysis on Small Caps Tailored Portfolio on Indian Stock Market: An Empirical Analysis

This study emphasizes on high-risk investment in Indian Stock Market especially on Small Cap Stocks. It will help the high-risk taking investors to minimize their risk and can get a positive return. In this study seventy-seven small cap stocks have been taken into consideration based on Automobile, Bank, Biotech and Pharmacy, Electronics, Finance, Food and Beverage, Information Technology and Metal & Chemical sectors. From each sector eight stocks have been taken and been used to develop a tailored portfolio. Altogether ten portfolios have been developed taking one stocks from each sector. The first attempt made here was to develop ten different portfolios with the help of machine learning through random number generations with the help of python. Later, concept of minimum standard deviations of each stock was taken and four portfolios are made based on “lower the standard deviation, lower is the risk” and a comparative analysis was done with the machine-driven portfolio. Comparative analysis was performed, and it was found that though machine driven portfolios are giving good results, but man-made portfolios are better than machine driven portfolios. Random Forest regression, Convolution Neural Network and LSTM(RNN) has been taken for forecasting of both type of portfolios. Errors were measured with MADP, MSEP, RMSEP and MAPEP. The historical prices of stocks are taken from Yahoo finance, NSE and BSE.

The journey is the reward: A study of corporate site visits and mutual fund performance

Institutional investors often visit corporate sites to conduct first-hand assessments of firms' business operations and management quality. We find that corporate site visits contribute significantly to mutual fund performance in China. Our results indicate that corporate site visiting is an important part of mutual funds' stock selection process. Fund managers utilize these visiting activities as a verification channel to affirm their selection of outperforming stocks. The impact on fund performance is stronger when funds are active, have more concentrated equity holdings or invest in small-cap stocks. Performance enhancement is more profound when mutual funds visit firms with high information disclosure quality, and when fund managers have an alumni connection with corporate executives.

Stock price momentum modeling using social media data

Alternative data has rapidly gained popularity as a means of observing investor reactions to current stock market events, analyzing sector movements, and developing investment strategies. Signals observed from alternative data may add valuable information to conventional market analysis, especially when there exists some information asymmetry in the market, to which small-cap stocks are particularly sensitive. Our research uses alternative textual data obtained from social media to predict the price momentum of small-cap stocks, which are known to be sensitive to market events and retail investors’ reactions. We directly address the challenges in the analysis of texts, especially in the Korean language, such as the use of jargon, acronyms, and typos, by taking a two-fold approach to preprocessing. Then, we extract the social keywords and label them by two standards: word momentum and correlation with stock price movement. Using these social keywords as social indicators derived from the retail investors trading small-cap stocks, in addition to the conventional technical indicators, we propose a price momentum forecast model which classifies whether the closing price of a given small-cap stock will increase by more than 10% in the next 5 business days. Experimental results show that our approach successfully extracts social keywords that play a significant role in determining the price momentum in the market, and our selected social indicators are intuitive to human understanding. Furthermore, we consider example investment scenarios and run tests by training various classifiers with the social indicators and computing cumulative returns. Our results are very promising and show that the investment scenarios with social indicators outperform the benchmark considerably. We anticipate that our work will expand the scope of using alternative data for stock market analysis and price momentum forecasts by incorporating social indicators extracted from social media.

The Dynamic Return and Volatility Spillovers among Size-Based Stock Portfolios in the Saudi Market and Their Portfolio Management Implications during Different Crises

This study contributes to the ongoing debate on the size effect and size-based investment styles by investigating the return and volatility spillovers and time-varying conditional correlations among Saudi large-, mid-, and small-cap indices. To this end, we utilize the weekly returns on the MSCI Saudi large-, mid-, and small-cap indices over a long sample period, spanning several crises. The econometric approach that we use is a VAR-asymmetric BEKK-GARCH model which accounts for structural breaks. On the basis of the VAR-asymmetric BEKK-GARCH model estimation results, we calculate portfolio weights and hedge ratios, and discuss their risk management implications. The empirical results confirm the presence of unilateral return spillovers running from mid- to small-cap stocks, while multilateral volatility spillovers are documented, albeit substantially weakened when accounting for structural breaks. The time-varying conditional correlations display clear spikes around crises, which translate to higher hedge ratios, increasing the cost of hedging during turbulent times. The optimal portfolio weights suggest that investors generally overweight large caps in their portfolios during uncertain times to minimize risk without lowering expected returns. The main takeaway from our results is that passively confining fund managers to a particular size category regardless of the prevailing market conditions may lead to suboptimal performance.

Impact of Geopolitical Risks on the Stock Market : Evidence from Large, Mid, and Small-Cap Stocks

Impact of Geopolitical Risks on the Stock Market : Evidence from Large, Mid, and Small-Cap Stocks

The effect of prospect theory value on asset returns on the Borsa Istanbul

The goal of this study is to test the validity of the prospect theory in the Borsa Istanbul (BIST) over the sample period September 2009 to December 2019. The prospect theory values of the stocks are generated from their historical return distributions following the method by Barberis et al. (2016). Panel data analysis is implemented in six different models with market and nonmarket factors for three different data sets of stocks listed on the BIST. We employed control variables, such as Fama and French (2015) five-factor model (FF5M) factors as well as past return and skewness indicators, in the models in addition to the prospect theory value and test whether prospect theory can predict subsequent stock returns. The results show that the prospect theory value has a statistically significant effect on the asset returns and its impact is seen in particular on small-cap stocks in the Turkish stock market.

Whether to Invest in Luxury goods based on Risk, Background, and Market

The luxury goods industry, the aviation industry, and the hotel industry all fall into the category of discretionary goods in people's lives. However, in the last 3 years, the spread of Covid-19 has affected all three sectors to a greater or lesser extent. Through the method of comparison, we can intuitively show the differences in the investment of financial stocks in these three industries. LVMH, AAR.Corp and Marriott International are representatives of luxury goods, aerospace, and hotels respectively, among which AAR.Corp is a small-cap stock with more characteristics. Analyse from a risk perspective, risk: LVMH<Marriott International<AAR.Corp.Analyse from a profitability perspective, profitability: AAR.Corp<Marriott International<LVMH.Analyse from a market perspective: value investors will invest in AAR.Corp.PEG investors may invest in Marriott, and LVMH would be on their watch list until its PEG ratio is under 2. Income investors won't invest in these three stocks since their dividend yield is less than 3%. This paper can make investors more clear about the stock market situation of non-essential goods, to help them choose suitable stocks.

The contrarians: Are they really the winner?

Several new global issues information (including the COVID-19 pandemic) tends to have an impact on the capital market in Indonesia but big-cap stocks show good performance compared to small-cap stocks. Employing 766 listed firms as sample with 246 market days, this study examines whether the contrarians are really the winner. This study finds that the contrarians succeed to beat the market by violating the efficient market hypothesis. However, the success of the contrarian strategy does not seem to indicate that they are the real winners as they are only thin-winning.

IMPACT OF FIRM PERFORMANCE ON STOCK RETURNS: EVIDENCE FROM LARGE-CAP, MID-CAP AND SMALL-CAP STOCKS

In this article, we analyse the impact of firm specific factors, namely, total income, net profit, and earnings per share (EPS) on stock returns of companies from the large cap, mid-cap and small- cap (LMS) categories using the panel quantile regression. We also use the ordinary least square method to compare our panel regression results. We select companies from NSE Large Cap100, NSE Mid Cap 100 and NSE Small Cap 100 Indices and each index is composed of 100 companies. These indices reflect the overall state of the Indian stock market. Our empirical analysis based on quarterly data from June 2010 to March 2022 shows some important findings. First, net sales significantly and negatively affect stock returns across the large, mid, and small cap stocks. Second, net profit and EPS have a substantial and positive impact on companies from all the categories. However, the coefficients are not significant across all quantiles. In short, the impact of firm specific factors on stock returns is not homogeneous across the LMS stocks implying that these factors do not influence stocks in a uniform way. The plausible reason may be that large, mid, and small cap companies share differences in terms of market capitalisation, growth potential and volatility.

It Depends On When You Search

Existing studies have found that online search is a revealed measure for investor attention and a useful predictor of stock returns. We study the heterogeneity in retail investor attention by comparing search conducted on weekdays vs. weekends and investigate the price pressure channel and information processing channel for stock return predictability. According to the information processing channel, weekends afford retail investors more time for the intensive cognitive analysis necessary to make better predictions. Alternatively, weekend search might better capture the price pressure from retail investors’ trading activities. We provide empirical results that support the information processing channel. We first show that weekend search, rather than weekday search, predicts large-cap stock returns in both the cross-section and time series. Additionally, our findings on retail trading activity contradict the price pressure channel in that weekday search, rather than weekend search, leads to a subsequent retail order imbalance. Overall, our study contributes to the literature on the predictive power of online search on stock returns, which has mainly focused on the price pressure channel, which yields significant results for small-cap stocks only.

Price behavior of small-cap stocks and momentum: A study using principal component momentum

This study analyzes why the negative momentum effect appears in Asian (China, Japan, Korea) stock markets, contrary to the U.S. market. We use principal component momentum (PMOM), a newly devised momentum measure. The PMOM is constructed by extracting commonalities from traditional momentum measures using principal component analysis. The results show evidence of positive and negative momentum profits in the U.S. and Asian markets, respectively. Negative momentum profits in Asian markets are attributable to the strong performance reversal of small stocks in the loser portfolio. Conversely, the positive momentum profits of the U.S. market are driven by the performance continuity of small stocks in the winner portfolio. The PMOM strategy is significantly more advantageous than traditional momentum strategies, based on the economic and statistical perspectives of momentum profits. These results are robust to changes in empirical designs.

Discount‐Rate Risk in Private Equity: Evidence from Secondary Market Transactions

ABSTRACTMeasures of private equity (PE) performance based on cash flows do not account for a discount‐rate risk premium that is a component of the capital asset pricing model (CAPM) alpha. We create secondary market PE indices and find that PE discount rates vary considerably. Net asset values are too smooth because they fail to reflect variation in discount rates. Although the CAPM alpha for our index is zero, the generalized public market equivalent based on cash flows is large and positive. We obtain similar results for a set of synthetic funds that invest in small cap stocks. Ignoring variation in PE discount rates can lead to a misallocation of capital.

Analysis of financial development and open innovation oriented fintech potential for emerging economies using an integrated decision-making approach of MF-X-DMA and golden cut bipolar q-ROFSs

The purpose of the paper is to identify the factors of financial development that have the greatest impact on open innovation in 7 emerging countries. The analysis was performed featuring the MF-X-DMA method, as well as its further verification for autocorrelation and heteroscedasticity. The time period covers years from 2002 to 2020. The article states that the main indicators to improve financial development should enhance the process of bank lending and equity market development. An important area is the development of competition by providing equal access to information to all market participants in a continuously refining technical infrastructure. Regression analysis with the MF-X-DMA method confirms the statistical significance of this influence. The article fills the knowledge gap into the link between open innovations and the relatively low capitalization of the modern emerging countries’ financial market, low liquidity in small cap stocks at the financial market and concentration of the banking sector, as well as risks arising in the process of globalization. Another analysis has also been conducted by generating a novel fuzzy decision-making model. In the first stage, the determinants of open innovation-based fintech potential are weighted for the emerging economies. For this purpose, M-SWARA methodology is taken into consideration based on bipolar q-ROFSs and golden cut. The second stage of the analysis includes evaluating the emerging economies with the determinants of open innovation-based fintech potential. In this context, emerging seven countries are examined with ELECTRE methodology. It found the most significant factor is the open innovation-based fintech potential.

Impact of economic policy uncertainty on Indian stock market returns: evidence from large-cap, mid-cap and small-cap stocks

Impact of economic policy uncertainty on Indian stock market returns: evidence from large-cap, mid-cap and small-cap stocks