Studio Aletheia · The Aletheian Investments and Trading Institute
Algorithmic Trading
Trading Lab 101 · Lesson 5
Algorithmic trading trades reaction for rules. Today you learn to turn a trading idea into a clear signal, test it against years of data, and automate the decision so emotion never touches the trade.
Learning Targets and Success Criteria
Build the vocabulary and judgment needed to prove a rule before you trust it.
What I will learn
- I can explain how algorithmic trading uses rules, backtesting, and automation to make decisions.
- I can identify a signal and the filters that confirm it before a trade is allowed.
- I can explain why backtesting matters before a strategy goes live.
- I can design a complete algorithmic strategy blueprint built on rules rather than reaction.
What success looks like
- I define a clear signal and name at least one filter that must also be true.
- I describe a backtesting plan that includes a time period and a way to judge results.
- I explain how automation protects the strategy from emotion and bias.
- My plan uses today's vocabulary, backtesting, signal, slippage, latency, and execution speed, with accuracy.
The language of today's session.
These five terms carry through the reading, the strategy lab, and the trading session that follows.
Backtesting
Testing a strategy using past market data to see how it would have performed.
Signal
A condition that tells the algorithm to buy or sell, for example a moving average crossover.
Slippage
The difference between the expected price of a trade and the price actually received.
Latency
The delay between sending an order and having it executed in the market.
Execution Speed
How quickly an algorithm can process data and send orders.
Meeting The Rule Before The Trade
Algorithmic trading rewards proof over instinct. Before any rule runs live, a trader needs to know it actually works.
Algorithmic trading uses computer programs to execute trades automatically based on predefined rules. These rules might involve indicators such as moving averages, price thresholds, or statistical patterns.
Algo traders use backtesting, testing a strategy on past market data to determine whether it would have been profitable. Once a strategy performs well in backtesting, it can be automated to run live without human emotion interfering. Algorithmic trading ranges from simple moving average systems to highly complex models, but at every level the core idea is the same: translate a clear rule into code, then let the algorithm follow it consistently.
Scenario: A Moving Average Crossover Bot
You design an algorithm that buys a stock whenever price crosses above the twenty day moving average and sells when it crosses back below. You test this rule on three years of historical data and discover it performs extremely well during trending markets but poorly when price moves sideways.
- A clear signal defined before a single trade is placed.
- A backtest across years of data, not a single lucky week.
- A filter added after the first test to remove weak conditions.
You revise the rules to include a volume filter, only taking trades when volume is above average. After re-running the backtest, the strategy avoids many choppy periods and performs more consistently. Only after this process do you deploy the algorithm live.
Materials for the session.
- A. Historical price data
- B. A defined signal and filters
- C. A backtesting tool or spreadsheet
- D. A risk and position sizing rule
- E. A plan for live or simulated deployment
Every strategy: define the rule, backtest it honestly, add filters that earn their place, and deploy only after the numbers hold up.
Design Before You Deploy
We build the blueprint before we trust the machine. A written blueprint forces the mind to define what proof would look like.
The Trading Session
You have a live rule to prove. Your job is to define, translate, backtest, optimize, and deploy only when the numbers hold up.
Trader's Journal
Accountability Checklist
What happens to a rule that is never backtested?
A rule that has never been tested is a guess wearing a strategy's clothes. Explain what happens when a trader automates a rule without backtesting it. Use the word discipline in your answer.