Algorithmic trading

Algorithmic trading is the execution of trading decisions by a program that reads market data and sends, modifies or cancels orders according to predefined instructions; the term covers execution algorithms that work a large order as well as strategies that decide when to trade.

Senzoukria · Glossary · Updated September 2026

Two meanings of the word

In institutional usage, an algorithm is often an execution tool: a program that slices a large order into smaller ones to reduce market impact, tracks a benchmark such as VWAP, or rests orders and adjusts them as the book changes. It does not decide whether to buy; a human or another system already did.

In retail usage, algorithmic trading usually means a strategy that both decides and executes: the program evaluates a rule on incoming bars and places orders when the rule fires. The two meanings share the mechanics of order handling but differ in who owns the decision.

Relation to systematic and quantitative trading

  • A systematic strategy is a fully specified rule set; it can be executed by hand or by a program.
  • Quantitative trading is the research discipline: forming a testable hypothesis, testing it on data with costs, validating out of sample.
  • Algorithmic trading is the execution layer. A rule that was never tested can be automated, and a well-tested rule can be traded manually.
  • In practice the three overlap, and a research result on its own does not justify automation on a live account.

What automation changes and what it does not

Automation removes hesitation and fatigue, and it guarantees that the rule is applied the same way at 09:31 and at 15:45. It does not remove slippage, connection risk, rejected orders or the difference between a bar-based test and a live queue. It adds failure modes of its own: a disconnect with an open position, a strategy that keeps firing after a data gap, a size parameter left at the wrong value. Those are the reasons a live automation needs hard limits and a manual stop that flattens.

In Senzoukria

Strategies written in the Scripts editor run on the simulated account or in replay by default. The optional autopilot is the desktop's live automation: it is armed explicitly by typing the arming word in the Autopilot panel, requires a compatible Rithmic account with order routing enabled, a mounted chart and the running desktop, and applies Max contracts and Max daily loss limits. STOP disarms the strategy and requests flattening; the broker response and actual positions still have to be checked. There is no automatic re-arming after a disconnect. Crypto feeds in the desktop are analysis-only, with no Binance or Bybit order routing. The AI assistant can read the autopilot's state but is read-only: it never sends an order and never changes a script.

Common mistakes

  • Equating "automated" with "tested". The program executes whatever it was given.
  • Running a live automation without confirming the account's and the prop firm's rules on automated orders.
  • Assuming a flatten request is a fill. A request is sent; the position is what the broker reports.
  • Leaving a strategy armed while stepping away, with no procedure for a disconnect.

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Frequently asked questions

Is algorithmic trading the same as high-frequency trading?
No. High-frequency trading is a subset defined by very short holding periods and a dependence on latency, typically with co-located infrastructure. Most algorithmic trading, including a scripted strategy on 1-minute or tick bars, is not high-frequency and does not compete on speed.
Does a backtest in the desktop arm the autopilot?
No. A backtest, a walk-forward run and a replay are analysis steps on historical or simulated data. Arming is a separate, deliberate action in the Autopilot panel, and it requires account permissions and configured limits. A favourable research result does not change any of that.
What data does an algorithmic strategy in Senzoukria read?
The footprint data of the mounted chart: executed bid and ask volume per price level, the delta derived from them, and the bar prices, on the bar construction the chart uses. Market data comes from the provider the trader subscribes to and is billed by that provider; the strategy sees the same feed the chart displays.

Keep reading

Strategy researchTest a trading strategy, from observation to challenge rulesDefine an observation, question it with the copilot, write a rule and explore costs, drawdown and fictional challenge limits in an interactive example.Quant · Start hereQuant trading for beginners: from idea to backtestDefine a testable rule, choose suitable data and evaluate later periods after costs.Order flow · HubOrder flow trading: the complete guideThe hub. What order flow is, what it shows — aggression, delta, imbalance, absorption, liquidity — and the tools that read it, each linked to a full guide.