# Platform Architecture Overview

### **Overview**

Our execution models process real-time and historical market data to generate optimal trade signals, execute orders efficiently, and minimize transaction costs. The core architecture follows this structured flow:

#### **Market Data + Trade Data → Signal Generator → Execution Algorithm → Order Routing**

<figure><img src="/files/Oxt29ipJmcUOY0azBsdc" alt=""><figcaption></figcaption></figure>

By leveraging advanced data ingestion, signal processing, and execution algorithms, our system ensures your orders are executed with minimal market impact while optimizing for liquidity, price improvement, and efficiency.

***

### **Market Data & Trade Data Ingestion**

We aggregate and normalize both **market data (quotes, order book updates, transactions)** and **trade data (historical fills, trade sizes, execution slippage)** in real time to provide the most accurate execution decisions.

#### **Preprocessing & Normalization**

* **Data Cleaning & Standardization:** We remove anomalies, reconstruct missing values, and align timestamps across multiple venues.
* **Trend Adjustments & Seasonality Corrections:** Using advanced filtering techniques (e.g., Kalman filtering), we adjust for market seasonality.
* **Order Book Reconstruction:** Multi-level order books are reconstructed using resampling techniques:
  * **Time-based resampling** (e.g., 100ms intervals for market microstructure studies)
  * **Tick-based resampling** (e.g., per N trades to analyze liquidity shifts)
  * **Order Flow Imbalance resampling** (to dynamically adjust granularity based on activity levels)

These preprocessing steps allow for cleaner and more actionable data, reducing noise and improving execution precision.

**Processing Latency:** X **μs**

***

### **Signal Generation**

Once the data is preprocessed, we compute multiple classes of trading signals to **predict short-term price movements and market impact**, ensuring optimal execution.

#### **Key Indicators & Signal Classes**

1. **Momentum-Based Indicators:**
   * Short-term price trends derived from volume-weighted momentum metrics.
   * Adaptive filters to detect shifts in buying/selling pressure.
2. **Correlated Asset Flow Indicators:**
   * Cross-asset flow relationships to detect liquidity imbalances.
   * Proprietary correlation models trained on historical slippage patterns.
3. **Order Flow Imbalance Indicators:**
   * Real-time monitoring of bid-ask spread pressure.
   * Tracking hidden liquidity signals across multiple venues.

These indicators **dynamically adjust trading parameters** within our execution algorithms, ensuring optimal trade timing and placement.

**Signal Computation Latency:** X **μs**

***

### **Execution Algorithms**

When an order is placed via our API, our **execution algorithms** leverage real-time market data and trading signals to determine **the optimal speed, order size, and routing strategy.**

We offer two primary execution algorithms:

#### **1. Block Timer**

* **Optimized Execution Schedule:** Determines the best time and size to trade while minimizing impact.
* **Superior to TWAP/VWAP:** Unlike traditional algorithms, it adapts to market conditions rather than following static time-based execution.
* **Designed for Institutional Blocks:** Ideal for large trades that require careful market participation.

#### **2. Block Router**

* **Venue & Order Type Selection:** Determines the optimal venue and order type (e.g., limit, market, iceberg) based on market depth.
* **Liquidity-Optimized Routing:** Routes trades to the deepest liquidity pools with minimal slippage.
* **Multi-Asset Execution:** Supports execution across Equities, Fixed Income, Options, and Crypto markets.

Clients can **select their preferred execution algorithm** via our API and customize trading parameters to suit their objectives.

**Order Routing Decision Latency:** X **μs**

***

### **Order Placement & Execution**

Once an execution decision is made, our system routes the order through **integrated EMS/OMS APIs** to ensure seamless placement and confirmations.

#### **Supported Trading Venues**

* **Fixed Income:** Tradeweb
* **Crypto:** Binance, Kraken, Coinbase
* **Equities:** NYSE, Nasdaq, CBOE
* **Equity Options:** Cboe, BOX, ISE
* **Futures:** CME, ICE, Eurex

All order fills are logged and returned via our FIX API, ensuring clients receive full **order confirmations and trade analytics**.

**Order Placement & Execution Latency:** X **μs**

***

### **Ultra-Low Latency Execution**

Our proprietary execution engine ensures that **market data ingestion, signal processing, and order execution occur in less than X μs**—delivering a speed advantage for latency-sensitive trading strategies.

**"From analytics to execution in less than X μs."**


---

# Agent Instructions: Querying This Documentation

If you need additional information that is not directly available in this page, you can query the documentation dynamically by asking a question.

Perform an HTTP GET request on the current page URL with the `ask` query parameter:

```
GET https://blockhouse-app.gitbook.io/blockhouse/core-product/platform-architecture-overview.md?ask=<question>
```

The question should be specific, self-contained, and written in natural language.
The response will contain a direct answer to the question and relevant excerpts and sources from the documentation.

Use this mechanism when the answer is not explicitly present in the current page, you need clarification or additional context, or you want to retrieve related documentation sections.
