Introduction to Algorithmic Trading

1. Convert an idea into exact rules

1.1 Inputs, decisions and timing

A rule such as “buy when momentum improves” cannot be implemented consistently until its inputs, calculation, observation time and action are defined. A paper crossover experiment might use a 20-observation and 50-observation simple average of adjusted daily closes. Specify a signal only when the short average moves from at or below the long average to above it, using completed data. These illustrative lengths are research choices, not proven optimal settings.

1.2 State and exception handling

Define target exposure, maximum holdings, cash treatment, exit conditions and what happens when data is missing or a security is suspended. A signal should produce an intended position, not repeated buy orders every time the program checks the same condition. Keep model versions and human overrides in an audit trail. Automation shifts emotion into rule selection and override decisions; it does not eliminate human judgement or behavioural bias.

Step-by-step method

1. Write input fields, calculation and exact crossover conditions.
2. Set observation time and earliest feasible execution time.
3. Define position state, missing-data policy and exit conditions.

2. Establish data lineage and a fair backtest

2.1 Point-in-time observations

A backtest is a controlled reconstruction, not a screenshot of a profitable chart. Store source, retrieval date, adjustments, calendar and transformation steps. Corporate actions require consistent prices, quantities and cash-flow treatment. Point-in-time universe selection means including companies that were then eligible, including later failures or delistings. Using today’s index constituents throughout history introduces survivorship bias.

2.2 Universe, corporate actions and splits

An index level can test a market-timing signal but is not automatically a tradeable share with the same return. A five-year KSE-100 study must explain whether it uses a price or total-return series, how an investable implementation would be obtained and how distributions are treated. Signal calculation and execution timestamps must prevent look-ahead. A final close cannot generate a signal and then guarantee a fill at that same already-observed close.

Step-by-step method

1. Record data provenance and adjustment conventions.
2. Construct the universe known at each historical date.
3. Separate signal data from feasible execution and cash accounting.

3. Validate beyond one attractive history

3.1 Development and untouched testing

Use development data to design rules, a validation segment to assess revisions and an untouched final segment for evaluation. Walk-forward tests repeatedly fit using past data and evaluate later data. Log all parameter trials: trying hundreds of settings and displaying only the best creates selection bias. One poor year does not prove permanent failure, and one profitable period does not prove a durable advantage.

3.2 Costs, capacity and benchmarks

Model commission, taxes where applicable, spreads, slippage, order-size constraints and unfilled orders. Calculate net returns, drawdown, turnover and exposure against an appropriate benchmark with consistent dividends and cash returns. Stress delayed fills, missing sessions and wider costs. A strategy whose paper edge disappears after modest friction should not be rescued by assuming perfect execution. Historical measurements remain estimates of a particular experiment, not promised future outcomes.

Step-by-step method

1. Lock rules before final testing and record unsuccessful trials.
2. Apply explicit costs and plausible capacity restrictions.
3. Compare net outcomes and stress cases with a consistent benchmark.

4. Separate execution algorithms from investment signals

4.1 TWAP, VWAP and participation

A signal algorithm decides desired exposure; an execution algorithm works a given instruction through time. TWAP divides activity across time intervals. VWAP-oriented execution follows an expected volume profile, while participation algorithms seek a share of observed market volume. These are benchmarks and scheduling ideas, not guarantees of a particular price. Urgency, thin liquidity and price movement create a trade-off between market impact and non-completion.

4.2 Order state, permissions and access

A FIX gateway is a communication facility within an authorised market-access structure, not evidence of public retail API entitlement. Obtain current documentation, provider permission, account/product eligibility and required approvals before any live integration. The SECP May 2025 concept paper is a proposal, not by itself an enacted universal approval rule. This topic supplies no live credentials, bypass instructions or assertion that JISPL supports automated retail orders.

Step-by-step method

1. Distinguish the target-position engine from the execution scheduler.
2. Verify written access permission and applicable current rules.
3. Model acknowledgement, rejection, partial fill and cancellation states.

5. Engineer controls and accountable operation

5.1 Pre-trade limits and safe failure

Controls should constrain order quantity, price deviation, exposure, submission rate and total loss tolerance under an approved policy. Reject stale prices, invalid symbols and impossible quantities. Unique instruction identifiers and persistent order state reduce duplicate orders after a timeout. A failed connection means the result is unknown until reconciled, not that the exchange never received an order. Test these controls in a disconnected or authorised simulation environment.

5.2 Reconciliation, shutdown and recovery

A kill switch should stop new submissions and invoke a documented process for existing orders and positions; merely closing the program does not cancel exchange orders. Assign an accountable operator, monitor alerts and reconcile broker records with internal state. Recovery requires confirmation of live orders, fills and holdings before restarting. Periodic review should cover model drift, system changes and permissions. A profitable backtest cannot compensate for a system that cannot establish its actual exposure.

Step-by-step method

1. Test stale data, duplicate messages, rejections and interrupted connections.
2. Specify who can halt activity and how open orders are resolved.
3. Reconcile independently before restart and preserve incident logs.

Research does not bypass the permission and control gates

Reference table

Glossary of key terms

Algorithm

A specified sequence of rules for processing inputs and producing actions.

Backtest

A historical reconstruction under explicit data and execution assumptions.

FIX

A financial messaging protocol used within authorised connectivity arrangements.

Kill switch

A control and procedure for halting activity and managing outstanding instructions.

Participation rate

Intended trading quantity as a fraction of relevant market volume.

Point-in-time data

Information represented as it was available at the decision date.

TWAP

Time-weighted average price; also an execution scheduling reference.

VWAP

Volume-weighted average price; also an execution benchmark.

Frequently asked questions

Common pitfalls