Build Alpha

Build Alpha Trading Software creates, tests and codes trading strategies with the click of a button. Demos:

[Build Alpha @buildalpha]

@BitDealer_ 🙏

[Build Alpha @buildalpha]

hard to believe this was almost ten years ago. Approach remains the same 💪https://t.co/zZErAgtn13

Escaping Randomness and turning to data for an edge

[Build Alpha @buildalpha]

All of this with NO coding.

Automated strategy discovery and validation have been and still are the future of trading. Much more to come soon...

[Build Alpha @buildalpha]

How Build Alpha works in 3 steps

1. Set Constraints
2. Set Filters/Robustness gates
3. Automatically generates strategies and exports code

Here's how 👇

[Build Alpha @buildalpha]

3. Generates Strategies and Code - results window shows strategy candidates that pass your metrics using only your constraints/inputs.

Export fully automate-able code for
· TradeStation
· MultiCharts
· Ninjatrader8
· TradingView
· Metatrader4/5
· Python
· ProRealTime

[Build Alpha @buildalpha]

Genichi Taguchi was a famous quality control engineer whose methods were adopted by Toyota, Ford, and NASA.

He focused on processes that survived noise and uncertainty, not ones that performed best in optimal conditions.

Quant traders should build strategies like this.

Build Alpha's Noise Test and automated strategy filtering are largely inspired by Taguchi's work.

[Build Alpha @buildalpha]

https://t.co/gHQ3qep9ZH

[Build Alpha @buildalpha]

Citadel pays atmospheric scientists $1M+ a year.

Why: weather moves natural gas, heating oil, and electricity demand before charts ever react.

30 years of the same US weather data ships with Build Alpha. The big desks model on it. Now so can you.

[Build Alpha @buildalpha]

https://t.co/r8jHqznnoK

[Build Alpha @buildalpha]

Timothy Masters runs one test before approving any backtest:

Monte Carlo Permutation Test

Your edge has to hold across 1,000 alternate paths. Same statistics, different sequence.

Most retail quants skip it. Build Alpha automates it.

[Build Alpha @buildalpha]

https://t.co/euvQ6tFOgh

[Build Alpha @buildalpha]

Jaffray Woodriff runs every trading signal at his $1B Hedge Fund QIM through one test before it ever sees live capital:

Vs Random Benchmarking

It answers could a coin flip have done this?

Most traders have never run this test once. Build Alpha can run it automatically on every strategy it generates.

[Build Alpha @buildalpha]

https://t.co/Hts3ul0kb4

[Build Alpha @buildalpha]

Pre-simulation synthetic data, not just post-validation. Write-up with the "how" and visuals here: https://t.co/MUOjURXitz

[Build Alpha @buildalpha]

Most systematic traders are training on a coincidence.
The historical price chart is one path the market took. It is not the path. The future could land on any of a thousand others and if your strategy only survives the one timeline you trained on, you do not have an edge.
You have memory.

Backtesting on the historical OHLC is an already known limit. The fix the industry settled on: Monte Carlo, walk-forward, noise testing - all happen AFTER the strategy is built.

By the time you run them, your search algorithm has already memorized the noise. You're mostly checking how badly.

"Do not optimize for the known past. Optimize for the unknown futures."

Robustness is the only thing that compounds in this game. Everything else is one regime away from going to zero.

The fix: train your models and build your strategies on synthetic data not just the historical data. Link below 👇

[Build Alpha @buildalpha]

ICYMI:

Pooling trading signals together: https://t.co/Jwy669Cs6D

Monte Carlo Permutation Testing: https://t.co/zBdUCkW1WF

Portfolio Testing: https://t.co/DpweAL91WP

[Build Alpha @buildalpha]

https://t.co/KV9XQ9eGMg

[Build Alpha @buildalpha]

https://t.co/euvQ6tFOgh

[Build Alpha @buildalpha]

https://t.co/50o63WL7QB

[Build Alpha @buildalpha]

Good distinction. I’d just add that different robustness tests are probing different failure modes. Some address randomness, some parameter sensitivity, some regime dependence, some execution sensitivity, and some persistence through time. So asking why may matter, but robustness testing still matters because not every test is trying to answer the same question. The example in the write up is simply for market noise - other tests for other purposes.

[Build Alpha @buildalpha]

Engineering legend Genichi Taguchi's methods were adopted by NASA, Ford Motor Company, 3M and many others.

He aimed to minimize product variability even under adverse conditions - similar to robust trading system development.

See metrics and workflows to discover more robust systems.

[Build Alpha @buildalpha]

https://t.co/gHQ3qep9ZH

[Build Alpha @buildalpha]

@D_Antiohos thank you 🙏