As of June 17, 2024, the most shorted stock was for, the American holographic technology services provider, MicroCloud Hologram Inc., with 66.64 percent of their total float having been shorted. This is a change from mid-January 2021, when video game retailed GameStop had an incredible 121.07 percent of their available shares in a short position. In effect this means that investors had 'borrowed' more shares (with a future promise to return them) than the total number of shares available for public trading. Owing to this behavior of professional investors, retail investors enacted a campaign to drive up the stock price of Gamestop, leading to losses of billions when investors had to repurchase the stock they had borrowed. At this time, a similar – but less effective – social media campaign was also carried out for the stock price of cinema operator AMC, and the price of silver. What is short selling? Short selling is essentially where an investor bets on a share price falling by: borrowing a number of shares selling these shares while the price is still high; purchasing the same number again once the price falls; then returning the borrowed shares at a profit. Of course, a profit will only be made if the share price does fall; should the share price rise the investor will then need to purchase the shares back at a higher price, and thus incur a loss. Short selling can lead to some very large profits in a short amount of time, with Tesla stock generating over one billion dollars in short sell profits during the first week of March 2020 alone, owing to the financial crash caused by the coronavirus (COVID-19) pandemic. However, owing to the short-term, opportunistic nature of short selling, these returns look less impressive when considered as net profits from short sell positions over the full year. The risks of short selling Short selling carries greater risks than traditional investments, and for this reason financial advisors often recommend against this strategy for ‘retail’ (i.e. non-professional) investors. The reason for this is that losses from short selling are potentially uncapped, whereas losses from traditional investments are limited to the initial cost. For example, if someone purchases 100 dollars of shares, the maximum they can lose is the 100 dollars the spent on those shares. However, say someone borrows 100 dollars of shares instead, betting on the price falling. If these shares are then sold for 100 dollars but the price subsequently rises, the losses could greatly exceed the initial investment should the price rise to, say, 500 dollars. The risks of short selling can be seen by looking again at Tesla, with the company causing the greatest losses over 2020 from short selling at over 40 billion U.S. dollars.

Over the course of 2020, U.S. short sellers generated a net profits of around 1.28 billion U.S. dollars from short selling Exxon Mobil stock. While a very large number, this pales in comparison to the net annual losses of from short selling of over 40 billion U.S. dollars for Tesla stock. Short selling is a process whereby investors effectively borrow a certain number of shares for a period of time, with the aim of selling them when the price is high, then repurchasing at a lower price in order to return them.

In 2025, ** percent of adults in the United States invested in the stock market. This figure has remained steady over the last few years and is still below the levels before the Great Recession, when it peaked in 2007 at ** percent. What is the stock market? The stock market can be defined as a group of stock exchanges where investors can buy shares in a publicly traded company. In more recent years, it is estimated an increasing number of Americans are using neobrokers, making stock trading more accessible to investors. Other investments A significant number of people think stocks and bonds are the safest investments, while others point to real estate, gold, bonds, or a savings account. Since witnessing the significant one-day losses in the stock market during the financial crisis, many investors were turning towards these alternatives in hopes for more stability, particularly for investments with longer maturities. This could explain the decrease in this statistic since 2007. Nevertheless, some speculators enjoy chasing the short-run fluctuations, and others see value in choosing particular stocks.

The smooth functioning of the stock lending market is essential for enabling short selling and maintaining effective arbitrage. Yet, little is known about how this low-transparency market responds to acute disruptions such as short squeezes. Short selling plays a central role in price efficiency, without which prices would disproportionately reflect the beliefs of the optimist. Cheap access to shares from lending institutions facilitates this process. The January 2021 short squeeze – centered around GameStop but involving a wider array of highly shorted equities – created extreme market conditions. While regulatory and academic attention has largely been focused on the squeeze’s effect on price volatility and more visible metrics of market quality, the squeeze’s effects on the stock lending market have not been thoroughly explored. Through an OLS regression framework, this paper analyzes how borrowing costs behaved across the highly shorted segment of the market, as compared to the non-shorted, broader market segment. The results show that during the squeeze, borrow fees increased, but only in the highly shorted group. In the post-squeeze period, borrow fees fell significantly, but again only within the highly shorted group. The stability of control group metrics supports the idea that the observed effects were concentrated solely within highly shorted equities. These results contribute to the literature on short sale constraints, bringing further implications for inefficiencies beyond what the existing literature had shown. Furthermore, this paper provides evidence that the lending market distortions brought on by a short squeeze may persist beyond the event window, interfering with effective arbitrage.

This dataset contains 30,000 rows of synthetic but highly realistic financial time-series data representing approximately 15 years of trading days. Each row corresponds to a single business day and includes key variables used in real financial modeling, such as open and close prices, trading volume, daily percent returns, and intraday volatility.

In addition to core trading features, this dataset includes widely-used technical indicators such as the 20-day Simple Moving Average (SMA-20), 50-day Simple Moving Average (SMA-50), and the popular Relative Strength Index (RSI-14). These indicators enable advanced quantitative analysis and machine-learning workflows such as regression forecasting, classification of market movement, algorithmic trading simulations, and trend modeling.

This dataset is ideal for:

Stock price prediction Trend and volatility modeling Time-series machine learning (LSTM, Prophet, ARIMA, Transformers) Quantitative finance teaching and learning Algorithmic trading strategy development Market simulation and risk analysis

All values are simulated using realistic market distributions and stochastic processes to closely resemble authentic stock data. The dataset is fully synthetic and safe for public use.

COLUMN DESCRIPTIONS

Date — The trading day of the observation. Open_Price — Starting price at market open. Close_Price — Final price at market close; often used as the main forecasting target. High_Price — Highest intraday price. Low_Price — Lowest intraday price. Volume — Total number of shares traded that day, representing market interest. Daily_Return_Pct — Percentage change from previous close; used for Up/Down classification. Volatility_Range — Intraday price range (High − Low); represents market energy or risk. Market_Cap — Synthetic market capitalization based on price; helps model scaling effects. SMA_20 — 20-day moving average; short-term trend indicator. SMA_50 — 50-day moving average; medium-term trend signal commonly used by traders. RSI_14 — 14-day Relative Strength Index; momentum indicator showing buying or selling pressure.

Short-Term-Debt Time Series for Rexford Industrial Realty Inc. Rexford Industrial creates value by investing in, operating and redeveloping industrial properties throughout infill Southern California, the world's fourth largest industrial market and consistently the highest-demand with lowest-supply major market in the nation over the long term. The Company's highly differentiated strategy enables internal and external growth opportunities through its proprietary value creation and asset management capabilities. As of September 30, 2025, Rexford Industrial's high-quality, irreplaceable portfolio comprised 420 properties with approximately 50.9 million rentable square feet occupied by a stable and diverse tenant base. Structured as a real estate investment trust (REIT) listed on the New York Stock Exchange under the ticker REXR, Rexford Industrial is an S&P MidCap 400 Index member.

Lehman Brothers, the fourth largest investment bank on Wall Street, declared bankruptcy on the 15th of September 2008, becoming the largest bankruptcy in U.S. history. The investment house, which was founded in the mid-19th century, had become heavily involved in the U.S. housing bubble in the early 2000s, with its large holdings of toxic mortgage-backed securities (MBS) ultimately causing the bank's downfall. The bank had expanded rapidly following the repeal of the Glass-Steagall Act in 1999, which meant that investment banks could also engage in commercial banking activities. Lehman vertically integrated their mortgage business, buying smaller commercial enterprises that originated housing loans, which allowed the bank to expand its MBS holdings. The downfall of Lehman and the crash of '08 As the U.S. housing market began to slow down in 2006, the default rate on housing loans began to spike, triggering losses for Lehman from their MBS portfolio. Lehman's main competitor in mortgage financing, Bear Stearns, was bought by J.P. Morgan Chase in order to prevent bankruptcy in March 2008, leading investors and lenders to become increasingly concerned about the bank's financial health. As the bank relied on short-term funding on money markets in order to meet its obligations, the news of its huge losses in the third-quarter of 2008 further prevented it from funding itself on financial markets. By September, it was clear that without external assistance, the bank would fail. As its losses from credit default swaps mounted due to the deepening crash in the housing market, Lehman was forced to declare bankruptcy on September 15, as no buyer could be found to save the bank. The collapse of Lehman triggered panic in global financial markets, forcing the U.S. government to step in and bail-out the insurance giant AIG the next day on September 16. The effects of this financial crisis hit the non-financial economy hard, causing a global recession in 2009.