Big Fish in a Small Pond: Institutional Trading of Penny Stocks

There has been a steady increase in institutional ownership of penny stocks over the past decades. Nevertheless, we show that penny stocks bought by institutional investors significantly underperform other penny stocks in subsequent four quarters. This poor performance is mainly driven by quasi-indexers, i.e., institutions with passive and widely diversified investment strategies. In comparison, dedicated institutions, i.e., those with low turnover but large average investments in portfolio firms and a commitment to “relationship investing”, have marginally significant ability in trading penny stocks.

Recommending System for Penny Stock Trading

Penny stocks at times makes the investors wealthy by turning to be a multi-bagger stocks or erode the wealth of the investors with poor performance in volatile conditions. While there are many machine learning-based prediction models that are used for stock price evaluation, very few studies have focused on the dynamics to be considered in penny stock conditions. Though the pattern might remain the same for normal stocks and the penny stock classification, still some of the parameters to be evaluated in the process needs changes. The model discussed in this report is a comprehensive solution discussed as scope for evaluation of the penny stock pick, using trading and reporting financial metrics. Experimental study of the test data indicates that the model is potential and if can be used effectively with reinforcement learning pattern, it can turn to be sustainable solution.

Post Model Correction in Risk Analysis and Management

This work focuses on Value at Risk (VaR) and Expected Shortfall (ES) in conjunction with the so called, low price effect. In order to improve forecasts of risk measures like VaR or ES when low price effect is present, we propose the low price correction which does not involve additional parameters and instead of returns it relies on asset prices. The forecasting ability of the proposed methodology is measured by appropriately adjusted popular evaluation measures, like MSE and MAPE as well as by backtesting methods. For illustrative and comparative purposes a real example from the Athens Stock Exchange as well as a number of penny stocks from Nasdaq, NYSE and NYSE MKT are fully examined. The proposed technique is always applicable, but its superiority and effectiveness is evident in extreme economic scenarios and severe stock collapses. The proposed methodology that pays attention not only to the asset return but also to the asset price, provides sufficient evidence that prices could contain important information which could if taken under consideration, results in improved forecasts of risk estimation.

Contrarian and Momentum Investment Strategies in Pakistan Stock Exchange

This study examines several aspects of the momentum strategies, such as profitability, risk-based explanation, and decomposition of the momentum profits. For this purpose, we use weekly and monthly data of 581 firms listed at the Pakistan Stock Exchange (PSX) for the period 2004-2014. We found the presence of momentum profits over short and long-horizons, while majority of the contrarian profits were observed only in the presence of penny stocks that have share prices of PKR 10 or less. As a robustness check, we computed returns through the weighted relative strength scheme (WRSS) procedure and average cumulative abnormal returns (ACARs). Interestingly, the results reported through WRSS have shown a similar pattern to that obtained through average cumulative abnormal returns (ACARs). Further, to know which factor contributes more to momentum and contrarian profits, we used the model proposed by Lo and MacKinlay (1990). Our findings show that the overreaction effect is the largest contributing factor of contrarian profits in PSX, while cross-sectional risk is the second largest factor and negatively affects the contrarian profits. Moreover, the lead-lag effect contributes positively to the contrarian profits. Similarly, the largest contributing factor for momentum profits is the underreaction effect, whereas cross-sectional risk is the second largest factor that positively affects momentum profits. Unlike contrarian profits, lead-lag effect reduces the momentum profits in the PSX.