--- icon: piano-keyboard description: >- The dataset provides a comprehensive analysis of institutional investment behaviors, strategies, and portfolio dynamics assist professional investors in making informed decisions. --- # Institutional Trading > **Data Notice**: This dataset provides academic research access with a 6-month data lag. > For real-time data access, please visit [sov.ai](https://sov.ai) to subscribe. > For market insights and additional subscription options, check out our newsletter at [blog.sov.ai](https://blog.sov.ai). ```python from datasets import load_dataset df_institute = load_dataset("sovai/institutional_trading", split="train").to_pandas().set_index(["ticker","date"]) ``` Data is updated quarterly as data arrives after market close US-EST time. `Tutorials` are the best documentation — [`Insitutional Trading Tutorial`](https://colab.research.google.com/github/sovai-research/sovai-public/blob/main/notebooks/datasets/Insitutional%20Holdings.ipynb)
CategoryDetails
Input Datasets13F Filings, Market Data
Models UsedSimple Calculations, Aggregations
Model OutputsStandardized Ratios
## Description This dataset provides comprehensive analysis of institutional investment behaviors, including metrics on fund ratios, growth, derivative usage, and portfolio dynamics. It offers investors valuable insights into market trends, risk profiles, investment strategies, and fund flows, enabling informed decision-making in institutional trading. ## Data Access #### Latest Data ```python import sovai as sov df_institute = sov.data("institutional/trading") ```
#### All Data This data is around 1GB if you download the entire dataset. ```python import sovai as sov df_institute = sov.data("institutional/trading", full_history=True) ``` #### Filtered Data ```python import sovai as sov df_institute = sov.data("institutional/trading", start_date="2004-04-30", tickers=["MSFT"]) ``` ## Reports ### Grouped ranking ```python import sovai as sov sov.report("institutional/flow_prediction", report_type="ranking") ```
## Plots ### Institutional Flow Prediction ```python import sovai as sov sov.plot("institutional", chart_type="prediction") ```
### Grouped Plot ```python import sovai as sov sov.plot("institutional", chart_type="flows") ```
## Data Dictionary
NameDescriptionType
std_percentoftotal_fund_medianRolling standard deviation of 'percentoftotal' over the last 4 quarters for each investor.float64
std_put_call_ratio_fund_medianRolling standard deviation of the put-call ratio over the last 4 quarters for each investor.float64
std_derivative_ratio_fund_medianRolling standard deviation of the derivative ratio over the last 4 quarters for each investor.float64
derivative_ratio_fund_medianRatio of the sum of put value and call value to share value for each investor.float64
put_call_ratio_fund_medianPut-call ratio calculated as the difference between put value and call value divided by their sum for each investor.float64
fund_ratio_fund_medianRatio of fund value to share value for each investor.float64
debt_ratio_fund_medianRatio of debt value to share value for each investor.float64
preferred_ratio_fund_medianRatio of preferred stock value to share value for each investor.float64
totalvalue_medianMedian of the total value of holdings for each investor.float64
percentoftotal_medianMedian of the percentage of total holdings for each investor.float64
shrholdings_growth_medianMedian of the percentage growth in shareholdings for each investor.float64
totalvalue_growth_medianMedian of the percentage growth in total value for each investor.float64
put_call_ratio_fund_growth_medianMedian of the percentage growth in put-call ratio for each investor.float64
derivative_ratio_fund_growth_medianMedian of the percentage growth in derivative ratio for each investor.float64
market_tilt_pca_medianMedian of the market tilt component calculated through PCA for each investor.float64
sector_tilt_pca_medianMedian of the sector tilt component calculated through PCA for each investor.float64
strategy_tilt_pca_medianMedian of the strategy tilt component calculated through PCA for each investor.float64
quantitative_tilt_pca_medianMedian of the quantitative tilt component calculated through PCA for each investor.float64
instrument_tilt_pca_medianMedian of the instrument tilt component calculated through PCA for each investor.float64
weight_variability_medianMedian of the variability in weightings for each investor's portfolio.float64
weight_mean_medianMedian of the mean weights of holdings in each investor's portfolio.float64
weight_coff_variance_medianMedian of the coefficient of variance of weights in each investor's portfolio (variability relative to mean weight).float64
weight_max_medianMedian of the maximum weight in each investor's portfolio.float64
weight_kurtosis_medianMedian of the kurtosis of weights in each investor's portfolio (measure of the 'tailedness' of the distribution of weights).float64
weight_skew_medianMedian of the skewness of weights in each investor's portfolio (measure of asymmetry of the distribution of weights).float64
num_investments_medianMedian number of investments in each investor's portfolio.float64
new_investments_medianMedian ratio of new investments to total investments in each investor's portfolio.float64
divestments_medianMedian ratio of divestments to total investments in each investor's portfolio.float64
new_investments_to_divestments_medianMedian ratio of new investments to divestments in each investor's portfolio.float64
portfolio_turnover_medianMedian portfolio turnover, measuring changes in portfolio composition, for each investor.float64
net_change_to_investments_medianMedian of the net change to investments, indicating the net inflow or outflow, in each investor's portfolio.float64
uncorrelated_percentile_medianMedian of the uncorrelated percentile, indicating the degree of uncorrelation in each investor's portfolio components.float64
flow_percentage_mean_medianMedian of the mean flow percentage, indicating the average flow relative to the value, in each investor's portfolio.float64
performance_value_mean_medianMedian of the mean performance value, indicating the average value of performance, in each investor's portfolio.float64
fund_return_quarter_medianMedian return of funds for each investor, calculated quarterly.float64
fund_flows_percent_quarter_medianMedian percentage of fund flows for each investor, calculated quarterly.float64
std_percentoftotal_fund_stdStandard deviation of the rolling standard deviation of 'percentoftotal' over the last 4 quarters for each investor.float64
std_put_call_ratio_fund_stdStandard deviation of the rolling standard deviation of the put-call ratio over the last 4 quarters for each investor.float64
std_derivative_ratio_fund_stdStandard deviation of the rolling standard deviation of the derivative ratio over the last 4 quarters for each investor.float64
derivative_ratio_fund_stdStandard deviation of the derivative ratio for each investor.float64
put_call_ratio_fund_stdStandard deviation of the put-call ratio for each investor.float64
fund_ratio_fund_stdStandard deviation of the fund ratio for each investor.float64
debt_ratio_fund_stdStandard deviation of the debt ratio for each investor.float64
preferred_ratio_fund_stdStandard deviation of the preferred stock ratio for each investor.float64
totalvalue_stdStandard deviation of the total value of holdings for each investor.float64
percentoftotal_stdStandard deviation of the percentage of total holdings for each investor.float64
shrholdings_growth_stdStandard deviation of the growth in the number of shareholdings for each investor.float64
totalvalue_growth_stdStandard deviation of the growth in the total value of holdings for each investor.float64
put_call_ratio_fund_growth_stdStandard deviation of the growth in the put-call ratio for each investor.float64
derivative_ratio_fund_growth_stdStandard deviation of the growth in the derivative ratio for each investor.float64
market_tilt_pca_stdStandard deviation of the market tilt principal component analysis (PCA) for each investor.float64
sector_tilt_pca_stdStandard deviation of the sector tilt principal component analysis (PCA) for each investor.float64
strategy_tilt_pca_stdStandard deviation of the strategy tilt principal component analysis (PCA) for each investor.float64
quantitative_tilt_pca_stdStandard deviation of the quantitative tilt principal component analysis (PCA) for each investor.float64
instrument_tilt_pca_stdStandard deviation of the instrument tilt principal component analysis (PCA) for each investor.float64
weight_variability_stdStandard deviation of the variability of weights of holdings in each investor's portfolio.float64
weight_mean_stdStandard deviation of the mean weights of holdings in each investor's portfolio.float64
weight_coff_variance_stdStandard deviation of the coefficient of variance of weights in each investor's portfolio.float64
weight_max_stdStandard deviation of the maximum weight in each investor's portfolio.float64
weight_kurtosis_stdStandard deviation of the kurtosis of weights in each investor's portfolio.float64
weight_skew_stdStandard deviation of the skewness of weights in each investor's portfolio.float64
num_investments_stdStandard deviation of the number of investments in each investor's portfolio.float64
new_investments_stdStandard deviation of the ratio of new investments to total investments in each investor's portfolio.float64
divestments_stdStandard deviation of the ratio of divestments to total investments in each investor's portfolio.float64
new_investments_to_divestments_stdStandard deviation of the ratio of new investments to divestments in each investor's portfolio.float64
portfolio_turnover_stdStandard deviation of portfolio turnover, measuring changes in portfolio composition, for each investor.float64
net_change_to_investments_stdStandard deviation of the net change to investments, indicating the net inflow or outflow, in each investor's portfolio.float64
uncorrelated_percentile_stdStandard deviation of the uncorrelated percentile, indicating the degree of uncorrelation in each investor's portfolio components.float64
flow_percentage_mean_stdStandard deviation of the mean flow percentage, indicating the average flow relative to the value, in each investor's portfolio.float64
performance_value_mean_stdStandard deviation of the mean performance value, indicating the average value of performance, in each investor's portfolio.float64
fund_return_quarter_stdStandard deviation of quarterly fund returns for each investor.float64
fund_flows_percent_quarter_stdStandard deviation of quarterly fund flows percentage for each investor.float64
totalvalueTotal value of holdings for each investor.float64
total_derivativesTotal value of derivative holdings (puts and calls) for each investor.float64
percentoftotalPercentage of total holdings for each investor.float64
growth_totalvalueGrowth rate of the total value of holdings for each investor.float64
growth_shrholdersGrowth rate of the number of shareholders for each investor.float64
growth_shrvalueGrowth rate of the share value for each investor.float64
growth_percentoftotalGrowth rate of the percentage of total holdings for each investor.float64
growth_shrholder_value_divergenceDivergence between growth rates of share value and shareholders for each investor.float64
diversification_score_tickerScore indicating the level of diversification in the portfolio based on the presence of different types of investments.float64
derivative_ratio_tickerRatio of derivative holdings to share value for each ticker.float64
derivative_holder_ratioRatio of derivative holders to total shareholders for each ticker.float64
derivative_holder_value_divergenceDivergence between derivative holder ratio and derivative ratio for each ticker.float64
short_interestValue of short interest (put value minus share value) for each ticker.float64
security_concentrationConcentration of security, calculated as share value divided by total value, for each ticker.float64
put_call_ratio_tickerPut-call ratio for each ticker, calculated as the difference between put and call values divided by their sum.float64
put_call_holder_ratioPut-call holder ratio for each ticker, calculated as the difference between put and call holders divided by their sum.float64
put_holder_value_sentiment_divergenceDivergence between put-call holder ratio and put-call ratio, indicating sentiment divergence for each ticker.float64
value_per_holderAverage value per holder for each ticker.float64
debt_equity_ratioRatio of debt value to equity value for each ticker.float64
historical_high_sharevalueHistorical highest share value for each ticker.float64
percentage_from_high_sharevaluePercentage difference from historical high share value for each ticker.float64
previous_high_sharevaluePrevious highest share value for each ticker.float64
percentage_above_previous_highPercentage above the previous highest share value for each ticker.float64
overweightIndicator of overweight investment in a particular ticker.float64
allocation_pressure_percentilePercentile rank of allocation pressure for each ticker, indicating the degree of pressure on allocation.float64
net_flows_sumSum of net flows for each ticker over the given period.float64
net_flows_maxMaximum net flow for each ticker over the given period.float64
net_flows_stdStandard deviation of net flows for each ticker over the given period.float64
net_flows_meanMean of net flows for each ticker over the given period.float64
net_flows_inflow_outflow_value_ratioRatio of inflows to outflows in terms of value for each ticker.float64
net_flows_inflow_outflow_count_ratioRatio of the number of inflows to outflows for each ticker.float64
appreciation_value_sumSum of appreciation value for each ticker over the given period.float64
new_value_sumSum of new value for each ticker over the given period.float64
turnover_percentage_medianMedian of turnover percentage for each ticker over the given period.float64
quarter_returnReturn for each ticker in the quarter.float64
quarter_flowsFlows for each ticker in the quarter.float64
derivative_overloadedIndicator of high derivative concentration for each ticker.float64
put_overloadedIndicator of high put option concentration for each ticker.float64
### Feature Descriptions 1. **Standard Deviation Metrics (Columns 0-38)** * **Purpose:** These metrics provide insights into the volatility and risk associated with various investment strategies and portfolio compositions. * **Usage:** Investors can use these metrics to assess the risk profile of different funds and compare the stability of their investment strategies. 2. **Growth Metrics (Columns 75-79)** * **Purpose:** These metrics track the growth or decline in the value of investments, the number of shareholders, and their share value over time. * **Usage:** Useful for identifying trends in investment preferences and shareholder behaviors. 3. **Diversification Score (Column 80)** * **Purpose:** Indicates the level of diversification in a portfolio based on different types of investments. * **Usage:** Investors can evaluate the risk mitigation strategies of different funds based on their diversification scores. 4. **Derivative and Put-Call Metrics (Columns 81-88)** * **Purpose:** Provide insights into the use of derivatives and options in investment strategies. * **Usage:** These metrics help in understanding the risk appetite and hedging strategies of investors. 5. **Historical Highs and Debt-Equity Ratio (Columns 90-94)** * **Purpose:** Offers a historical perspective on share values and assesses the leverage used by funds. * **Usage:** Useful for long-term investment analysis and understanding the use of debt in investment strategies. 6. **Allocation Pressure and Flow Metrics (Columns 96-107)** * **Purpose:** These metrics assess the inflows and outflows from funds, alongside the allocation pressure on investments. * **Usage:** Essential for understanding market liquidity, investor sentiment, and pressure on asset allocation. 7. **Overloaded Indicators (Columns 108-109)** * **Purpose:** Indicate high concentrations in derivatives and puts. * **Usage:** Investors can gauge the level of speculation and potential overexposure to certain investment instruments. ## Use Cases This dataset provides a comprehensive analysis of institutional investment behaviors, strategies, and portfolio dynamics. It covers various aspects like fund ratios, growth metrics, derivative concentrations, shareholder dynamics, and more. The data is designed to assist professional investors in understanding market trends, evaluating investment strategies, and making informed decisions. * **Market Trend Analysis:** Understand broad market trends by analyzing growth metrics and standard deviations. * **Risk Assessment:** Evaluate the risk profiles of different funds and strategies using volatility and diversification metrics. * **Strategy Evaluation:** Assess and compare the effectiveness of different investment strategies. * **Investment Decision Making:** Utilize historical data and flow metrics to make informed investment decisions. ***