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This paper presents a three-period model featuring a short-term investor in the over-the-counter bond market. A short-term investor stores cash because of a need to pay cash at some future date. If a short-term investor buys bonds, then a deadline for retrieving cash lowers the resale price of bonds for the investor through bilateral bargaining in the bond market. Ex-ante, this holdup problem explains the use of a repo by a short-term investor, the existence of a haircut, and the vulnerability of a repo market to counterparty risk. This result holds without any uncertainty about bond returns or asymmetric information.

We document that an increase in short-horizon investors is associated with cuts to long-term investment and increased short-term earnings. This leads to temporary boosts in equity valuations that reverse over time. To estimate these effects, we use difference-in-differences regressions around firms’ additions to the Russell 2000, comparing firms with large and small increases in short-term ownership. We proxy for the presence of short-term investors using ownership by transient institutions. Our results suggest that short-term pressures by investors can lead to myopic firm behavior. This paper was accepted by Shiva Rajgopal, accounting .

PurposeAlthough investigating the factors influencing technological diversification is essential to understanding research and development (R&D) strategies, studies from the perspective of corporate ownership structure are limited. This study examines the effect of heterogeneous institutional investors on technological diversification strategies.Design/methodology/approachThe sample consists of 33,124 firm-year observations of USA manufacturing firms from 1981 to 2008. Data were extracted from US Patent Data, Thomson Reuters' 13f and the Compustat database. A panel regression analysis was used to test the hypothesis. Moreover, the two-stage least squares (2SLS) approach using instrumental variables (IVs) and generalized method of moments (GMM) were also applied to address the endogeneity issue.FindingsThe empirical findings indicate that short-term (long-term) institutional investors positively (negatively) affect technological diversification. That is, short-term institutional ownership hampers R&D diversification, suggesting that firms are forced to make myopic investments to meet short-term goals instead of diversifying corporate R&D projects. Meanwhile, long-term institutional ownership enhances technological diversification to achieve long-term value.Research limitations/implicationsBy differentiating between institutional investment horizons, the authors produce empirical evidence that institutional investors with short-term and long-term perspectives have different views on technological diversification. This study is based on data between 1981 and 2008, due primarily to patent data availability and data on institutional investors. However, this limitation does not diminish the importance of the empirical findings, as the study's focus is on discovering antecedent evidence of corporate technological diversification rather than addressing recent trends in firm decisions.Practical implicationsIn finding that long-term institutional investors are likely to encourage technological diversification at firms, the paper carries an important practical implication that can help inform decision-making by policymakers and investors.Originality/valueThis research contributes to a more comprehensive understanding of institutional investors' role in technological diversification strategies. Additionally, by challenging the assumption that all institutional owners share the same perspective, this study is the first to confirm the existence of heterogeneous effects of institutional investors on technological diversification strategies.

The article analyses the business of business and comes to the view that the role of business is to balance all stakeholders’ interests while giving relative dominance to the interests of investors, over those of other stakeholders. Based on this understanding, we propose an economic model, which describes the nexus and interactions between the interests of stakeholders, and develops a set of functions aimed at achieving better management of risk through corporate socially responsible (i.e. CSR) investment. The model takes into account the utilities of the corporate officers, short term and long term investors. All three functions are considered by the Board of Directors, who are deemed the final arbiters with respect to firm decision-making and the body to whom executive management owes fiduciary duties. Finally, a decision rule is developed that defines the circumstances under which the Board of Directors will consider to invest corporate funds in CSR.

Stock returns unexplained by \"fundamentals,\" such as cash flow news, are more likely to reverse in the short run than those linked to fundamental news. Making novel use of analyst forecast revisions to measure cash flow news, a simple enhanced reversal strategy generates a risk-adjusted return four times the size of the standard reversal strategy. Importantly, isolating the component of past returns not driven by fundamentals provides a cleaner setting for testing existing theories of short-term reversals. Using this approach, we find that both liquidity shocks and investor sentiment contribute to the observed short-term reversal, but in different ways: Specifically, the reversal profit is attributable to liquidity shocks on the long side because fire sales more likely demand liquidity, and it is attributable to investor sentiment on the short side because short-sale constraints prevent the immediate elimination of overvaluation. This paper was accepted by Brad Barber, finance.

We study optimal government debt maturity in a model where investors derive monetary services from holding riskless short-term securities. In a setting where the government is the only issuer of such riskless paper, it trades off the monetary premium associated with short-term debt against the refinancing risk implied by the need to roll over its debt more often. We extend the model to allow private financial intermediaries to compete with the government in the provision of short-term money-like claims. We argue that, if there are negative externalities associated with private money creation, the government should tilt its issuance more toward short maturities, thereby partially crowding out the private sector's use of short-term debt.

Pressure from institutional money managers to generate profits in the short run is often blamed for corporate myopia. Theoretical research suggests that money managers’ shortterm focus stems from their career concerns and greater fund transparency can amplify these concerns. Using a difference-in-differences design around a regulatory shock that increased the transparency of fund managers’ portfolio choices, we examine whether increased transparency encourages myopic corporate investment behavior. We find that corporate innovation declines following the regulatory shock. Moreover, evidence from mutual fund trading behavior corroborates that the increased short-term focus of money managers drives the results.

In today’s society, investment wealth management has become a mainstream of the contemporary era. Investment wealth management refers to the use of funds by investors to arrange funds reasonably, for example, savings, bank financial products, bonds, stocks, commodity spots, real estate, gold, art, and many others. Wealth management tools manage and assign families, individuals, enterprises, and institutions to achieve the purpose of increasing and maintaining value to accelerate asset growth. Among them, in investment and financial management, people’s favorite product of investment often stocks, because the stock market has great advantages and charm, especially compared with other investment methods. More and more scholars have developed methods of prediction from multiple angles for the stock market. According to the feature of financial time series and the task of price prediction, this article proposes a new framework structure to achieve a more accurate prediction of the stock price, which combines Convolution Neural Network (CNN) and Long–Short-Term Memory Neural Network (LSTM). This new method is aptly named stock sequence array convolutional LSTM (SACLSTM). It constructs a sequence array of historical data and its leading indicators (options and futures), and uses the array as the input image of the CNN framework, and extracts certain feature vectors through the convolutional layer and the layer of pooling, and as the input vector of LSTM, and takes ten stocks in U.S.A and Taiwan as the experimental data. Compared with previous methods, the prediction performance of the proposed algorithm in this article leads to better results when compared directly.

The complexities of stock price data, characterized by its nonlinearity, non-stationarity, and intricate spatiotemporal patterns, make accurate prediction a substantial challenge. To address this, we propose the DCA-BiLSTM model, which combines dual-path convolutional neural networks with an attention mechanism (DCA) and bidirectional long short-term memory networks (BiLSTM). This model captures deep information and complex dependencies within time-series data. First, wavelet packet decomposition extracts high- and low-frequency features, followed by DCA for robust deep feature extraction, and finally, BiLSTM models bidirectional dependencies. Validated on datasets from Yahoo Finance, including Apple, Google, Tesla stocks, and the Nasdaq index, the model consistently outperforms traditional approaches. The DCA-BiLSTM achieves an R 2 of 0.9507 for Apple, 0.9595 for Google, 0.9077 for Tesla, and 0.9594 for the Nasdaq index, with significant reductions in error metrics across all datasets. These results demonstrate the model’s robustness and improved predictive accuracy, offering reliable insights for stock price forecasting.

We show that the positive relation between institutional ownership and future stock returns documented in Gompers and Metrick (2001) is driven by short-term institutions. Furthermore, short-term institutions' trading forecasts future stock returns. This predictability does not reverse in the long run and is stronger for small and growth stocks. Short-term institutions' trading is also positively related to future earnings surprises. By contrast, long-term institutions' trading does not forecast future returns, nor is it related to future earnings news. Our results are consistent with the view that short-term institutions are better informed and they trade actively to exploit their informational advantage.