Oyamori Learning
Learn systematic trading.
Guides, explainers, and tutorials on systematic trading, market edges, AI sentiment signals, and quantitative strategy. Written by the team behind Oyamori.
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Trading Edges
Every edge in the Oyamori catalog — what it is, why it works, and how to deploy it.
▶Getting Started
From idea to live algo: CLI tutorials, workflow guides, and platform setup.
⬡Risk Management
Position sizing, drawdown limits, backtesting reality, and portfolio-level protection.
⬟Sentiment & AI
How Newsvibe sentiment data integrates with systematic strategies to sharpen signals.
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Oyamori
Oyamori Cognitive Framework: DNA, Pulse & Score Explained
The Oyamori Cognitive Framework organizes market intelligence into three layers — DNA, Pulse and Score — answering what it is, what's happening, what to do.
7 min read →Onboarding
The Developer's Guide to Quantitative Trading
If you can write a function, you can understand quant trading. Finance concepts translated into software engineering terms — without the jargon or the hype.
7 min read →Getting Started
How Oyamori Works — A Technical Overview for Skeptical Developers
What does Oyamori do, how does it connect to your brokerage, and what happens when a trade goes wrong? Answers for developers who will not accept a black box.
7 min read →Fundamentals
What Is a Trading Edge? (And Why Most Traders Don't Have One)
An edge is a repeatable market condition where the odds tilt in your favor. Most investors trade on hope. Here's the difference — and how to find one.
7 min read →All Articles
Showing 84 of 84 articles
Edges
Open Interest Explained: How to Read Futures and Options Positioning
Open interest explained — what OI means, how it differs from volume, and how to read price and OI together in futures and options to spot real positioning.
Edges
Oyamori Contract Score™: The Greek Efficiency Method for Options
Oyamori Contract Score™ ranks options contracts by Greek efficiency: normalize Delta, Gamma, Theta, and Vega to 0–100, then weight by GammaTheta Ratio.
Edges
Trend-Filtered DCA vs Standard DCA: The Calmar Ratio Test
Trend-filtered DCA exits to cash when EMA(10) turns bearish, then redeploys in a lump sum — cutting max drawdown from 52% to 19% at the cost of 0.8% CAGR.
Edges
0DTE Scalping Tickers: The 7 Most Liquid Underlyings Ranked for Speed
0DTE scalping tickers ranked by spread, gamma, and best window — SPY, QQQ, SPX, IWM, TSLA, NVDA, AAPL — for the very-short scalper who lives on fills.
Sentiment & AI
Machine-Readable Market Data: From Candlesticks to Market State
Machine-readable market data turns 200 years of candlestick knowledge into executable intelligence — how Oyamori reads market states instead of charts.
Sentiment & AI
The Oyamori Thesis™: From Predicting Markets to Measuring Market Energy
Market energy trading measures whether price will move — not which way. Oyamori reads momentum, volume, and volatility expansion to time options entries.
Getting Started
Market Structure: 13 Levels of Capital Flow From Fed to Your P&L
Map the market structure hierarchy from the Fed to your P&L across 13 levels. See where capital enters, how orders route, and exactly where you sit.
Oyamori
Oyamori Cognitive Framework: DNA, Pulse & Score Explained
The Oyamori Cognitive Framework organizes market intelligence into three layers — DNA, Pulse and Score — answering what it is, what's happening, what to do.
Getting Started
Call, Put, Long, Short: The 2×2 Mental Model for Options
Call, put, long, short explained with one simple 2×2 mental model. Decode any option position in a single breath — right vs obligation, bullish vs bearish.
Edges
Open Interest in Options: How Traders Use OI to Read the Market
Open interest reveals how many active options contracts exist, giving traders a direct read on conviction, positioning, and where institutional money flows.
Edges
Options Flow Trading Strategies: 5 Playbooks That Use Unusual Activity
Options flow signals where institutional money moves — these 5 playbooks show exactly how traders turn unusual activity into high-conviction entries with defined risk.
Getting Started
OptionStrat Guide: Visualize Options Strategies Before You Trade
OptionStrat is the go-to options visualizer for retail traders — risk graphs, break-evens, probability of profit, and scenario testing in one place.
Getting Started
How to Read an Option Chain: Strikes, Greeks & Expirations
How to read an option chain explained: decode strikes, delta, gamma, theta from a real AAPL snapshot, and discover who actually sets strike prices.
Edges
Volume vs Open Interest: Powering an Options Alert Scanner
Volume vs open interest in options: the ratio that flags unusual activity, plus a scoring engine that ranks contracts into three alert tiers automatically.
Developer
Options Chain Data Providers: Free and Real-Time Sources
Options chain data providers for traders: free delayed feeds, real-time APIs, screeners, historical data, charting platforms, and volatility tools compared.
Edges
Options Flow: Reading the Smart Money Signal
Options flow tracks real-time institutional options orders — large premiums, sweeps, and dark pool prints that reveal where Smart Money is placing bets before price moves.
Getting Started
Options Leverage by Moneyness: ITM, ATM, OTM Fully Compared
Options leverage shifts dramatically across moneyness. Deep OTM gives 116x leverage with lottery-like risk; ATM is where day traders find the best balance.
Getting Started
Options Trading Cheat Sheet: 252 Terms by Priority Level
Master 252 options trading terms organized by priority level — from call/put basics to Greeks, implied volatility, and professional strategy jargon.
Edges
Options Price Target Timing: 11 Methods to Estimate When Price Arrives
Options price target timing has 11 quant methods — from Black-Scholes 1σ time to Monte Carlo. This guide maps which engine fits your asset, horizon, and data.
Edges
Trendlines: Reading Market Direction with Diagonal Lines
Trendlines reveal market direction by connecting swing highs or lows with a diagonal line. Learn to draw, read, and trade uptrends, downtrends, channels, and reversals with chart examples.
Edges
Options Chain API: AlphaVantage vs Alpaca for Quant Traders
Options data API comparison: AlphaVantage provides 15 years of history; Alpaca gives live greeks, OI via contract endpoint. Real AAPL and SPY data compared.
Edges
Cross-Exchange Crypto Arbitrage: Real Math, Real Friction, Real Edge
Cross-exchange crypto arbitrage between Binance, Kraken, and Bitkub promises risk-free profit. The real math on fees, slippage, and withdrawal costs tells a different story.
Options Trading Terminology: The Complete Jargon Guide
Master every options trading term — from calls and puts to Greeks, IV crush, and spread strategies — with an interactive reference guide.
Getting Started
Pre-Order Checklist: From Novice to Pro Before You Place a Trade
A tiered pre-order checklist for stock traders — 3 checks for beginners, 5 gates for intermediates, and the full pro system before any scalp entry.
Getting Started
Backtesting a Trading Strategy: What the Results Actually Mean
Learn how backtesting a trading strategy works, what metrics matter, how to spot overfitting, and why out-of-sample validation is non-negotiable.
Edges
Gap and Go Strategy: A Systematic Edge in the Opening 30 Minutes
The gap and go trading strategy turns pre-market momentum into a structured intraday edge. Learn the qualification criteria, entry rules, and backtested stats.
Getting Started
How to Read Stock Charts: The Systematic Trader's Framework
Learn how to read stock charts as a systematic trader — candlestick anatomy, support and resistance, trend structure, volume, and when to use each chart type.
Risk Management
Kelly Criterion: Size Your Positions for Maximum Long-Run Growth
Learn how Kelly Criterion calculates the optimal position size for your trading edge — with formula, Python, live calculator, and fractional Kelly explained.
Reference
Markdown Components Reference
Live reference for every supported markdown component on Oyamori Learning — callouts, syntax highlighting, charts, tables, and standard formatting.
Sentiment & AI
News Sentiment Trading: How to Profit Before the Market Reacts
Learn how news sentiment trading works, how AI scores headlines before prices move, and how to build a signal-to-trade pipeline that acts faster than the crowd.
Edges
Price Action Trading: Structure, Conviction, and When It Lies
Price action reads structure — but structure can be faked. Ten real manipulation scenarios plus the mental model for scalp, day trade, and swing timeframes.
Risk Management
Risk of Ruin: The Hidden Math That Destroys Trading Accounts
Risk of ruin is the probability your account hits zero before reaching your goal. Learn the formula, how position size drives it, and how to protect yourself.
Getting Started
Trading Bot Stale Data: Why It Happens and How to Fix It
Trading bot stale data causes bad fills and edge erosion. Learn why IEX feeds lag, how to detect staleness, and which data feed to upgrade to for your strategy.
Edges
Market Data for Algo Traders: IEX, NBBO, and SIP
What every algorithmic trader must know about US market fragmentation — why IEX-only feeds break scalp bots and how NBBO and SIP data change execution.
Edges
US Stock Trading Lifecycles: Scalper vs. Daily Trader vs. Options Trader
How scalpers, daily traders, and options traders each enter, manage, and exit positions — with win rates, capital requirements, and time-at-screen compared.
Fundamentals
Algorithmic Trading Without a Hedge Fund
Quant infrastructure once required institutional AUM and a fund structure. Here's what changed, what's now accessible to retail investors, and what hasn't gotten easier.
Getting Started
API-First Trading Platform — Why Architecture Determines Strategy Scope
API-first trading platforms are built for automation from day one. That architecture determines which systematic strategies are even possible to run.
Risk Management
Backtesting Is Not Prediction — The Honest Guide to Results
Backtesting a trading strategy does not predict live performance — and a beautiful backtest is often the most dangerous thing in systematic trading.
Onboarding
The Developer's Guide to Quantitative Trading
If you can write a function, you can understand quant trading. Finance concepts translated into software engineering terms — without the jargon or the hype.
Sentiment & AI
Black-Box AI vs. Transparent Sentiment — How to Know What You're Getting
Black-box AI signals are unverifiable. A signal you cannot inspect is one you cannot validate — and a signal you cannot validate is a risk you cannot manage.
Newsvibe
Building a News-Aware Algo — A Python Tutorial with Newsvibe API
End-to-end tutorial: authenticate with Newsvibe API, parse sentiment signals, define entry logic, execute trades via Alpaca, and log results — all in Python.
Getting Started
Why CLI-First Trading Is the Developer's Competitive Advantage
GUI trading hides state, slows iteration, and treats automation as an afterthought. For developers, the CLI is not a preference — it is a structural edge.
Getting Started
CLI vs. GUI for Algo Trading — What You Lose When You Click
Every GUI click cannot be scripted, audited, or repeated exactly. For systematic traders, that is not inconvenience — it is structural friction that compounds.
Tutorial
Connecting Alpaca to Your Trading Strategy — A Developer's Guide
Authentication, market data streaming, order management, and error handling — everything needed to wire a trading strategy to Alpaca's API reliably.
Risk Management
Drawdown Limits — How to Build a Kill Switch Into Your Algorithm
Drawdown limits and kill switches are the one safeguard most algo traders skip — until a strategy crosses its statistical validity boundary and keeps running.
Tutorial
Your First Live Trade via API — A CLI Tutorial with Alpaca and Oyamori
From authenticated API client to confirmed paper trade in under 50 lines of Python. The execution layer, demystified — before adding any strategy logic on top.
Edges
Gap Trading Strategy — How Overnight News Creates Morning Opportunities
Gap trading turns overnight news into a morning signal — stocks that gap on volume exhibit predictable short-term behavior that a prepared algo can exploit.
Newsvibe
How Newsvibe Works — From News Ingestion to Trading Signal
Newsvibe is a sentiment engine you can inspect and validate. Here is how raw news becomes a scored, structured trading signal with tier classification.
Getting Started
How Oyamori Works — A Technical Overview for Skeptical Developers
What does Oyamori do, how does it connect to your brokerage, and what happens when a trade goes wrong? Answers for developers who will not accept a black box.
Tutorial
How to Backtest a Strategy — And What the Numbers Actually Mean
Backtesting is not prediction — it is hypothesis testing. Here is how to run a backtest correctly and, more importantly, how to interpret the results honestly.
Fundamentals
How to Find Your Trading Edge — A Systematic Approach
Finding a trading edge starts with a testable hypothesis, not a backtest. Here's the systematic process for discovering a genuine market inefficiency.
Fundamentals
Hugging Face for Trading Strategies — The Category Oyamori Is Building
Hugging Face built a model hub that democratized AI. Trading strategies need the same model: shared, vetted, executable. Here's what that category looks like.
Risk
Is Algorithmic Trading Legitimate? — How to Spot Real vs. Scam
Algorithmic trading ranges from rigorous systematic strategies to outright fraud. Here's how to tell the difference — and five questions to ask any platform.
Edges
Mean Reversion Explained — How Price Reverts and How to Trade It
Mean reversion is one of the most persistent market phenomena — and one of the most misunderstood. Here's how price reverts, why it works, and how to code it.
Edges
Momentum + Volume — The Edge That Works in Trending Markets
Momentum trading without volume confirmation is noise. Here is why volume makes momentum signals tradeable and how to build the filter in Python.
Getting Started
How to Monetize a Trading Algorithm Without Selling Your Edge
You built a validated trading algorithm. Monetizing it doesn't mean handing over the code or running a fund. Here's the model that lets you earn without either.
Sentiment
News-Driven Gap Trading — Using Overnight Sentiment to Predict Open Gaps
Gap trading meets sentiment scoring — overnight news predicts the morning gap direction if you weight recency, urgency, and volume correctly.
Sentiment & AI
Why News Sentiment Changes Everything in Algo Trading
News sentiment is not a soft signal — it is a structural information advantage. Here is why sentiment-blind algos fail around high-impact news events.
Edges
Options Theta Decay — Harvesting Time Premium Systematically
Theta decay puts time on the seller's side — every day options lose value you never bought. Here's how to harvest it without getting steamrolled.
Edges
Order Flow Imbalance — Reading What the Market Is Actually Doing
Order flow imbalance signals price direction before the chart shows it. Here is how to build a usable proxy from Level 1 data and where the edge decays.
Risk Management
Overfitting vs. Robust Strategies — How to Know the Difference
Overfitting a trading strategy looks perfect on paper and fails immediately in production. Here is how to tell the difference before you go live.
Tutorial
The Oyamori CLI Workflow — From Edge Selection to Live Execution
The complete Oyamori CLI workflow — selecting an edge, configuring risk, connecting your account, and running a live systematic trading strategy.
Edges
The Oyamori Edge Catalog — Market Inefficiencies Explained
A structured inventory of validated market inefficiencies — what each edge exploits, when it performs, and how long positions typically hold.
Edges
Pairs Trading Explained — How Correlation Breaks Create Profit
Pairs trading profits from temporary divergences between correlated assets, market-neutral by design. Here is how cointegration makes it work in practice.
Getting Started
Paper Trading vs. Live Trading — How to Know When You're Ready
Paper trading and live trading feel identical until the moment they don't. A measurable framework for knowing when your strategy is ready for real capital.
Risk Management
Portfolio-Level Risk — Running Multiple Algos Without Blowing Up
Individual strategy limits fail when algos are correlated. Portfolio-level risk is what separates multi-algo accounts that survive from those that don't.
Risk Management
Position Sizing for Algo Traders — From Fixed Dollar to Volatility-Adjusted
Position sizing determines whether a strategy survives long enough to profit. Sizing kills more strategies than bad signals do — here is how to fix it.
Risk Management
Quant Trading vs. Gambling — The Real Difference
Quant trading and gambling share math and uncertainty. The difference is edge: a quantified probability advantage executed consistently, without emotion.
Sentiment & AI
Regime Detection with Sentiment — When to Run Your Algo and When to Pause
Sentiment regime detection is the best signal for when not to trade — aggregate negative sentiment across a broad basket marks risk-off conditions reliably.
Risk Management
The Retail Algo Trader Checklist — Before You Go Live
Most algos fail at deployment, not strategy design. This checklist gives you specific, measurable pass/fail criteria before your strategy touches live capital.
Workflow
Scheduling Trading Algorithms — Cron, Docker, and Serverless
Cron, Docker, and serverless — three approaches to scheduling a trading algorithm. Trade-offs, setup instructions, and when each breaks in production.
Edges
Sector Rotation — Following Institutional Money with Automation
Sector rotation moves predictably through economic cycles as institutional capital reallocates. Here is how to follow that flow systematically with Python.
Sentiment & AI
Sentiment + Momentum — How to Combine News Signals with Technical Edges
Signal fusion cuts false positives: one signal has noise, two calibrated uncorrelated signals have less. Here is the implementation and the math.
AI
Signal Fusion Explained — Why One Signal Is Never Enough
Signal fusion cuts false positives: a single signal has noise, two calibrated uncorrelated signals have less. Here is the math and the architecture behind it.
Edges
Statistical Arbitrage for Retail Traders — Edge, Limits, and Implementation
Statistical arbitrage exploits temporary divergence between correlated assets. Here's the mechanics, the limits, and a Python implementation for retail scale.
Fundamentals
Strategy as a Service: The New Model for Algorithmic Trading
Strategy as a service separates trading logic from capital. Investors access proven algorithms on subscription without code ownership, fund minimums, or custody transfer.
Risk
Strategy Decay — Why Your Edge Stopped Working and What to Do
Every trading edge has a lifespan. Strategy decay ends most algos — here is how to detect regime change, crowding, and structural shifts early.
Tutorial
Setting Up Your Trading Development Environment
A reproducible Python trading environment from scratch — pyenv, core libraries, Alpaca API credentials, and a smoke test that confirms everything works.
Workflow
From Trading Idea to Live Algorithm — The Complete Workflow
Most trading ideas die between hypothesis and deployment. This is the end-to-end workflow — from a market observation to a live, monitored systematic strategy.
Fundamentals
Trading Strategy Marketplace: What It Is and Why It Matters
A trading strategy marketplace lets investors access proven algorithmic strategies without building from scratch. Here's how it works and why it changes retail quant trading.
Risk Management
Transparent Trading Signals — What They Show and Why It Matters
Transparent trading signals show their inputs, timing, and logic — not just the output. Here's what signal transparency looks like and why it matters for risk.
Risk Management
What Makes a Trading Strategy Verifiable — And Why Most Aren't
Most backtests prove a strategy fit historical data — not that it has an edge. Here's the difference between a fitted result and a verifiable trading strategy.
Edges
Volatility Skew Trading — The Options Edge Most Retail Traders Miss
Volatility skew exists because institutions pay a structural premium for downside protection. Here is how to measure it and harvest it systematically.
Fundamentals
What Is a Trading Edge? (And Why Most Traders Don't Have One)
An edge is a repeatable market condition where the odds tilt in your favor. Most investors trade on hope. Here's the difference — and how to find one.
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