Trading Indicators Python Download

Python code to get nyse intraday and daily stocks all tickers historical data download for free downloading

you have 4 days to do

acceptance criteria i can do it by myself on my computer
each day new indicators for last 5 years data save to csv file

all indicators for all nyse tickers will be downloaded by provided by you python file
without lost days and without lost indicators
list of all nyse current tickers will be provided by you and used in code
****** intraday and daily historical stock data ******

1 ) fundamentals
2) corporate actions

3) s&p500 constituents
4) daily metrics
5) equity prices
6) fund prices
7) price based metrics
8) tickers and metadata
9) insiders
10) institutional investors
11) institutional investors (by investor)
12) institutional investors (by ticker)




use
https://findl.Com/free-data
https://www.usfundamentals.com/
https://www.stockdata.org/
https://www.simfin.com/en/fundamental-data-download/

it will be nice to have order flow(trade data), but not must
order flow or trade data can provide several valuable insights into market behavior, and various indicators can be calculated to analyze buying and selling pressure, liquidity, and price action. Here are some key indicators and visualizations derived from order flow data that can help you understand market sentiment and momentum.
1. Volume Profile (Histogram)
• Description: Shows the distribution of trading volume across different price levels, indicating where the most trading activity occurred.
• Usage: Identifies support and resistance levels based on high volume zones.
• Calculation: Use a histogram of trade volume (size) grouped by price levels.
2. Delta (Buy vs. Sell Volume Difference)
• Description: Measures the net difference between buy and sell volumes over a specific period. Positive delta suggests buying pressure; negative delta indicates selling pressure.
• Usage: Useful for understanding market bias and short-term sentiment.
• Calculation: Calculate the difference between buy and sell trade sizes, where trades executed at the ask are buys and trades at the bid are sells.
3. Cumulative Volume Delta (CVD)
• Description: The running total of the delta (buy-sell volume difference) over time, showing accumulated buying or selling pressure.
• Usage: Tracks longer-term buying or selling pressure trends.
• Calculation: Sum of delta values over the day or chosen period.
4. Trade Count Histogram
• Description: A histogram showing the number of trades occurring at each price level within a period, indicating levels of interest or liquidity.
• Usage: High trade counts at certain price levels can reveal areas of strong interest or significant liquidity.
5. Volume-Weighted Average Price (VWAP)
• Description: The average price of a security adjusted for volume, reflecting the true average cost of buying or selling over time.
• Usage: Commonly used as a benchmark for assessing trade execution quality and market bias.
Period.
6. Order Imbalance
• Description: The ratio of buy to sell volume, which can indicate dominant buying or selling interest at certain times.
• Usage: Can signal potential reversals or momentum shifts.
Buy Volume
7. Liquidity Heatmap
• Description: Visual representation of volume or trade density over price levels and time. Hot spots on the heatmap highlight areas with high trading volume.
• Usage: Useful for identifying strong support/resistance zones and areas with intense trading interest.
• Calculation: Generate a heatmap where the x-axis is time, the y-axis is price, and the color intensity represents volume or trade size.
8. Market Depth Analysis
• Description: Shows the number of orders or volume available at different price levels on the order book (outside pure trade data but often combined).
• Usage: Measures liquidity and the potential impact of trades on price.