Books, indicators, data sources, podcasts, and channels that have shaped the methodology behind the lab. Not a comprehensive list — a curated one. Everything here has earned its place through repeated use and demonstrated relevance to the work.
Six books that have had the most direct influence on the methodology, philosophy, and frameworks behind the lab. Each one changed something about how markets, money, or human action is understood here.

The magnum opus of Austrian economics — a complete treatise on praxeology and human choice. Foundational for understanding how markets emerge from individual action, why central planning fails, and how price signals carry irreplaceable information.
Austrian Economics
A sweeping essay on how Bitcoin represents a return to sound money and the conditions that enabled Renaissance-era commercial flourishing. Bridges economic history, monetary philosophy, and the case for Bitcoin as foundational infrastructure.
Bitcoin, Economics & Philosophy
The definitive book on trader psychology — why a strong methodology fails without mental discipline. Douglas's framework for accepting probabilistic outcomes, defining risk before entry, and operating without attachment to individual trade results is the psychological backbone every wizard on the Trader Study page implicitly converges on.
Behavioral Finance & Psychology
A deep examination of the 18-year real estate cycle and its relationship to banking, credit, and macroeconomic rhythms. Essential background for understanding the cyclical frameworks that inform the confluence matrix.
Monetary History & Banking
Mandelbrot's frontal challenge to modern finance theory. Markets exhibit fat tails, long-range dependence, and multifractal scaling — properties Black-Scholes and modern portfolio theory cannot capture. Crashes happen far more often than Gaussian models predict. The intellectual foundation for taking tail risk seriously, sizing positions defensively, and treating standard volatility metrics as systematically understated.
Economic Theory & Policy
Booth's central thesis — that technology is inherently deflationary while central banks fight deflation with inflation — is the key framework for understanding the macro tension between monetary policy and technological progress.
Technological Change & Future of AbundanceBuilt on TradingView using Pine Script. These indicators are direct expressions of the lab's methodology — each one measuring a specific component of velocity, structure, or confluence that informs the screening and matrix systems.
Plots horizontal dashed lines at the closing prices of 7, 14, 21, and 27 days ago, each in a distinct color with a price label. Daily-anchored via security calls so the levels stay constant across any chart timeframe. Each lookback toggleable, label side and size configurable. Useful for identifying short-term mean-reversion targets and prior-cycle resistance.
Tags the chart when price comes within a configurable percentage of four key reference levels: All-Time High, 52-Week Low, 50 EMA, and 200 EMA. Color-coded labels (green for ATH, red for 52W Low, orange for EMAs) plus alertcondition events for ATH and 52W Low proximity. Default near-threshold uses weekly ATR percentage of price.
Compact top-right table showing 1-month, 3-month, 6-month, and 1-year percentage change in close, plus a verdict column: UP if all four are positive, DOWN if all four are negative, MIXED otherwise. Confirms or denies dominant trend at a glance. Color-coded green/red/orange against the lab's dark-theme palette.
The full screening engine on-chart. Combines weekly V% velocity (range / ATR) with MA stack classification, RSI, and proximity to ATH/52W Low to label every qualifying weekly bar with its setup type — REV, PBK, EXT, EXTP and their bearish mirrors. Optional relative-volume gate and forward-return labels showing what happened in the N weeks after each historical signal.
The V% metric isolated as a standalone indicator. Plots weekly (high − low) / ATR(14) and highlights the chart background green when V% exceeds threshold on an up week, red on a down week. Threshold dashed at 1.2 by default. Use this to inspect velocity history on a single ticker without the full screener overlay.
Flags green candles where volume is at least 1.76× (configurable) the trailing 90-bar average, marking each with an HRG label and faint background highlight. Optional EMA filters (10/20/50/200) let you require price above or below each EMA before the candle qualifies. Includes all four EMAs plotted plus an optional RVOL line in a separate pane. Alertcondition fires on every qualifying candle.
The V% Screener takes a wide basket of liquid stocks and refines it by velocity, volatility, and aggression. To work properly, it needs the right data exported from a TradingView screener configured with the columns and filters below. Pre-filtering for setups in TradingView limits the screener's discriminatory power — your job is to export liquidity, the screener's job is to discriminate by velocity.
Set only three filters in TradingView: Price > $2 (excludes penny stocks where data and execution are unreliable), Market Cap $2B – $10T (institutional-grade liquid names), and Average Volume 90-day > 3M (tradeable liquidity). Do not filter for RSI, percentage change, EMA position, or any signal the screener will compute. Those are output classifications, not input filters.
Save the screener with a clear label (suggested: Simplest Lab — V% Screener Export) so you can re-run it weekly. Export the CSV after Friday's close or any time before Monday's pre-market open. The V% formula depends on the completed weekly bar — exporting mid-week produces noisy readings because High, Low, Open, and ATR reflect a partial week. Then drop the CSV into the V% Screener page on this site.
The complete walkthrough with explanations of why each filter and column matters, common mistakes to avoid, and the philosophy behind keeping the TradingView basket wide so the screener's V% formula can do its discriminating work. Includes the full list of required TradingView columns — the exact 20 column names to add via the gear icon, in the order the V% Screener expects them.
The full trade decision document. How each V% screener label maps to a position in the structural cycle, the four-gate decision flow, lifecycle progression diagrams for both bull and bear setups, and the conditions that distinguish credit-spread setups from directional entries. Picks up where the Setup Guide ends — once you've exported clean data, this is how you decide what to do with it.
Audio and video sources worth following for macro context, exponential technology, and monetary philosophy. Five shows that cut through noise and are directly relevant to the frameworks behind the lab.
Macro investor's weekly takes on AI acceleration, robotics, oil and commodities, private credit, and market stress cycles. Links tech disruptions directly to SPX, Bitcoin, and asset allocation.
Exponential tech, AI, robotics, and abundance mindsets with top builders and investors. Shows how tech waves create new market opportunities and productivity surges that reshape asset classes.
Macro, crypto, and technology at the Exponential Age nexus. Bridges traditional finance with AI and crypto tailwinds for asset pricing and risk at a macro level.
Foundational understanding of monetary systems that drive every asset class, inflation dynamics, and long-term wealth preservation strategies. Deep philosophy and history of money.
Timeless wisdom on market behavior, avoiding emotional traps, and thoughtful risk management. Essential for any serious trader's mental model — particularly the cycle awareness that feeds into the confluence matrix.
Deep dives into the plumbing of the financial system — banking, debt, and policy distortions. Excellent for understanding the "hidden" macro mechanics that affect markets, with a focus on real-world implications rather than pure theory.
Primary data sources used to populate the matrix dashboards and screener. Each serves a specific role in the confluence framework — no single source provides everything.
Primary charting platform and screener. All V% screener data is exported directly from TradingView CSV exports. Custom indicators live here.
Federal Reserve Economic Data. Used for macro overlay signals — yield curve, credit spreads, inflation metrics, Fed funds rate positioning.
Fed funds futures implied probability tool. Key input for the macro layer of the SPY confluence matrix — rate expectations move markets before rate decisions do.
Weekly retail investor sentiment data. Bull/bear ratio used as a contrarian sentiment input in the SPY confluence matrix sentiment layer.
Volatility index. Core input for the fear/complacency signal in the macro matrix. Extreme readings in either direction carry the most weight.
Composite sentiment index for crypto markets. Primary sentiment input for the Bitcoin Matrix alongside derivatives positioning data.
On-chain Bitcoin analytics. MVRV ratio, realized price, long-term holder supply, and accumulation metrics feed directly into the Bitcoin Matrix cycle layer.
Market breadth visualization and sector heat maps. Used for the breadth layer of the SPY matrix — advance/decline, new highs/lows, sector rotation context.