Data for Investments - November Week-3
2nd Edition
Open in browser to view tables. You are not a paid subscriber and have received this report 1-day late. Next week we will add the clinical trial dataset.
Key Insights
Financial Health:
CVAC demonstrates strong financial stability with high Cash Flow (CF) and Liquidity (LIQ) scores, positioning it for medium-term growth despite recent stock declines.
PRTA exhibits concerning financial metrics, particularly in Profitability and Solvency, indicating deteriorating health despite buoyant stock performance.
Insider Flow Pressure:
AMP and GM present promising buying opportunities in the Financial Services and Consumer Cyclical sectors, respectively.
NKLA and BZH show significant selling pressures in the Industrials and Consumer Cyclical sectors, signaling potential risks.
Short Interest Analysis:
ARBB is heavily overshorted, making it a potential short squeeze candidate.
CYCC's declining short interest suggests bearish trends, while CCIX and FTS indicate shifting short volumes that could impact market movements.
Earnings Surprise Prediction:
ZIM is likely to exceed earnings expectations, whereas ACM faces substantial downside risk.
Breakout Prediction:
EVRI shows strong potential for upward price movement, while RILY and FFNW indicate possible downward pressures.
Sentiment Modelling:
TT experiences the most positive news sentiment, contrasted by AIN, which faces significant negative media coverage.
Additional tools included in the report track congressional trading, government spending, corporate lobbying, Wikipedia search interest, and factor model analyses, providing a multifaceted view of market dynamics.
This information is for general purposes only and does not constitute financial, investment, tax, or legal advice. Nothing here should be taken as a recommendation to buy or sell any securities or financial instruments. All content is provided "as is" without warranties, and may not suit your personal circumstances or financial objectives.
Financial Ratio Radar
This is a financial early-warning system that monitors changes in ratios to identify critical positive and negative trends in companies' relative performance. It focuses on 8 key areas:
Composite (Comp): Combines all 6 measures into one number
Cash Flow (CF): Change in how well the company manages its cash
Efficiency (EF): Change in how well they use their resources
Liquidity (LIQ): Change in how easily they can pay short-term bills
Profitability (Prof): Change in how much money they're making
Solvency (Solv): Change in how well they can handle their debts
Valuation (Value): Change in how fair their stock price is
Factor (Fac): A measure of statistical change (can ignore)
We supply 650+ of the the largest positive and negative moving ticker ratios from the week.
CVAC demonstrated strong financial health with high scores across multiple metrics, particularly in CF (49) and Liquidity (24), outperforming peers in overall financial stability. Despite the stock's decline, being mostly a result of its German and an mRNA association, it is well positioned for medium term advances.
PRTA showed concerning financial metrics, with notably weak scores in Profitability (-50) and Solvency (-30), indicating deteriorating financial health compared to industry peers. The stock is suprisingly boyant for its level of deteriorating health.
Key Trends to Watch:
Positive: Companies improving in both Cash Flow and Profits (top right of the plot) often make great investments—they’re getting better at making and retaining money. Keep your eye on SGMO!
Negative: Companies struggling with both Cash Flow and Profits (bottom left) indicate potential issues. Watch out for ATEX!
Insider Flow Pressure
This model forecasts insider trading behavior, the idea is to predict when insiders will buy and sell stocks and to ‘front-run’ them. This model self-improves over time using machine learning. The tables focus on the top 20 stocks with the highest buying pressure and the top 20 stocks with the highest selling pressure.
Shows how a stock's predicted pressure compares to similar companies, ranked as a percentage
AMP shows the most promising flow prediction indicating a potential buying opportunity within the Financial Services sector.
NKLA has appeared twice as the most concerning flow prediction suggesting significant selling pressure in the Industrials sector.
Looking at the change in a prediction from one week to another gives you a second-order output that is often a better leading indicator to stock price movements.
GM shows a promising change in flow prediction of 31.39, indicating a potential buying opportunity within the Consumer Cyclical sector.
BZH shows a concerning change in flow prediction of -46.85, suggesting significant selling pressure in the Consumer Cyclical sector.
Short Interest Analysis
We identify stocks whose short interest significantly deviates from comparable companies, refreshed every two weeks. The table focuses on the top and bottom 60 overshorted stocks. Red is undershorted and Blue is overshorted
ARBB is heavily overshorted (+10.2% change) with 0.8% vs expected 45.5% - potential squeeze candidate.
CYCC shows declining short interest (-24.7% change) at 20.0% vs expected 58.2% - this is bearish given that future shorts could catch on.
By the time the short-interest file becomes available, the market may have already reacted. Monitoring changes in short volume, however, could provide an earlier indication of shifts in short sentiment. Displays top and bottom 150 stocks by short volume ratio changes.
CCIX shows rising short volume (+100.0% change) to 100.0% vs previous 0.0% and is a potentially concerning trend.
FTS has declining short volume (-62.0% change) to 10.5% vs previous 72.5% and could signal covering with upside potential.
Earnings Surprise Prediction
Predicts earnings surprise for companies reporting in the next two weeks. By anticipating unexpected earnings results, you can position yourself ahead of market movements.
The table only shows company that are reporting in the next two weeks from the date indicated at the top of the table.
The earnings surprise predictions are bounded between -50% and +50% to filter out statistical outliers and maintain focus on meaningful variations.
ZIM is predicted to potentially outperform expectations with a 46.3% likelihood of earnings surprise. The consensus EPS estimate is $7.05 for the quarter ending 2024-09-30.
ACM shows potential downside risk with a -49.9% earnings surprise probability. Analysts expect EPS of $1.24 for the quarter ending 2024-09-30.
Breakout Prediction
Using machine learning models, we track the predicted change in price breakouts and slope. The implication of a change is that a stock has become more or less likely to go up in price. We deliver the 80 tickers with the largest and smallest predicted changes in breakout and slope.
EVRI shows the strongest breakout prediction signal, suggesting potential upward movement.
RILY displays the weakest breakout prediction signal, indicating possible downward pressure.
LARK demonstrates the largest positive change in breakout prediction, suggesting improving momentum.
FFNW shows the largest negative change in breakout prediction, indicating deteriorating momentum.
EVRI exhibits the steepest positive change in breakout slope, suggesting accelerating upward momentum.
JJSF shows the steepest negative change in breakout slope, indicating accelerating downward pressure.
Sentiment Modelling
Tracking news-based sentiment for individual companies allows us to aggregate sentiment to the sectorial level. We first deliver the 280 tickers with the largest and smallest predicted changes in sentiment. The aggregated data is then presented on a sectorial and thematic basis.
News sentiment for TT articles was most positive this week with a 55.972 change in sentiment score, suggesting favorable coverage.
Meanwhile, AIN faced the most negative news sentiment shift of -77.241, indicating negative media coverage.
The chart above tracks the sentiment at a sectorial level which is helpful to assess weekly sectorial sentiment shifts. An increasing percentile indicates improving sentiment for a given sector/theme relative to others.
We also track numerous themes that we aggreagate in a handful of main themes, the detailed themes are available in the SDK. An increasing percentile indicates improving sentiment for a given sector/theme relative to others.
Congressional Trading Tracker
This tool tracks filings and records in both the House and Senate, based on the premise that members of Congress may be more informed than the average investor. The table shows trades performed in a given week.
Government Spending
This data tracks recent government contract announcements. Given that the government accounts for over 40% of national expenditures, these contracts are an important source of revenue for many companies and are a reliable predictor of quarterly revenue. We deliver all the tickers with new government contracts for the associated week.
Size indicates the size of the contract in USD millions. Obligation is the contractual amount the government ought to pay the company.
Awards corresponds to the number of contracts awarded in the associated week. Previous indicates the number of contracts previously awarded to the same company.
Corporate lobbying tracker
Lobbyists have important roles to play in the American political system and are often responsible for the passage of bills and implementation of policies.
Anomaly corresponds to a change in lobbying behavior compared to historical lobbying patterns. It could indicate that it is a companies first lobbying contract, or a large contract compared to their historical average.
Wikipedia Search Interest
This model uses an algorithm to discover early search interest on Wikipedia pages. This signal is stronger than most retail indicators as it suggests the beginning of a research process. We deliver the 100 tickers with the largest and smallest predicted changes in search behaviour.
Interest in EVRI, based on Wikipedia searches, increased 32.92% this week, showing strong positive attention.
Meanwhile, CVD experienced a significant decline of -32.09% in search interest, indicating reduced market attention.
Factor Model Coefficients
This analysis shows percentile rankings of factor model coefficients across stocks. Higher percentile coefficients indicate stronger factor sensitivity relative to peers. We deliver approximately 1000 tickers and their associated factor scores
Factor Model Error Analysis
Stocks with high R², negative AIC, and strong t-statistics provide reliable factor exposure for long-term systematic investing, while those with lower statistical significance and model fit offer alpha potential through market inefficiencies but demand sophisticated trading strategies.
Thank you for reading and subscribing. We aim to add a new screen every month and make it available to you on Mondays.