Algorithmic Trading with Apache Flink | Hands-on guide

Discover the system architecture of an algorithmic trading pipeline, from Python-generated events to Kafka or Red Panda, through Apache Flink processing and Slack notifications.

Install and configure Docker Desktop on Mac, Windows, and Linux, set seven CPUs, five GB memory, one GB swap, and a 64 GB disk, then create a new project.

Build a market news producer for algorithmic trading with Apache Flink, Python, and Alpaca, orchestrated in Docker compose with Red Panda Kafka clusters to stream news data.

Build a historical prices producer that streams minute stock bars from Alpaca data into a Kafka topic using the Red Panda client, with symbol AAPL and defined dates.

Use Docker and Flink SQL to orchestrate algorithm by creating market news and stock prices tables from Kafka topics, then join them on symbol and event time to generate signals.

Implement a custom algorithm in Flink SQL by computing SMA 20 and SMA 50 on stock prices, joining with market news sentiment to generate buy or sell signals.

Create a trading signals view from market news and prices using ddl. Use symbol, news time, close, and sma 20 to trigger buys or sells via sentiment and lag.

Create a Kafka sink that writes trading signals to a new trading signals topic, defining a sink table with symbol, news time, signal time, close, and buy/sell signals in json.

Restart the Flink job manager to restore Kafka consumption and verify signals flow. Prepare a signal handler to post Slack alerts and trigger trades on Alpaca.

Develop a PyFlink-based trading signals handler and consumer by installing PyFlink and the Kafka connector, configuring Kafka consumer properties, and streaming trading signals from a topic.

Decode incoming messages, extract symbol, signal time, and signal, then format a trading signal alert. Prepare to send alerts to Slack and place orders, with robust error handling.

Learn to send trading signals to Slack by configuring a channel, obtaining a bot token, and posting messages via Slack's chat.postMessage API; then integrate with Alpaca to trigger trades.

Trigger buy and sell signals by placing market orders via the Alpaca trade API, configuring symbol, quantity, side, and time in force in a paper trading workflow.

Discover the all weather trading strategy, a diversified portfolio approach across long-term bonds, stocks, intermediate bonds, commodities, and gold designed to perform across boom, recession, inflation, and deflation.

Use the golden cross with 50-day and 200-day moving averages to signal bullish buys, illustrated by a XYZ example with a 24% year-long gain and momentum strategy notes.

Capitalize on bullish momentum by riding uptrends until reversal, using six-month price performance to time entries, while back trading with historical data validates profits and losses.

Implement an all weather backtesting algorithm in backtrader, configuring weights across stocks, bonds, commodities, and gold, with alpaca integration and a rebalancing routine to test performance.

Finish the all-weather backtesting workflow by configuring a daily time-frame backtest with alpaca data, using cerebro and bt, and evaluating performance with sharpe ratio and portfolio returns.

Implement the golden cross backtesting strategy using SMA 20 and SMA 50 with the back tester API to trigger buy signals on crossovers and evaluate against the all weather strategy.

Implement a momentum strategy backtesting algorithm in the existing backtester, configuring a 12-period momentum and a 26-month exit, using EMA exit signals, and compare results with the golden cross.

Verify market trades by reviewing the Alpaca dashboard, past orders, and signals, and assess a month of portfolio performance from an initial $100,000 to current gains.

Verify trades triggered by alpaca in a paper trading environment using TradingView, inspect positions and market value, assess 13% returns, and consider setting trading alerts.

Apply paper trading to test your trading algorithm end to end before risking real money, using a paper trading API to open and reset positions while you fine-tune your strategy.