Insights for Smarter Portfolio Decisions

A single P/E ratio doesn't tell you if a stock is cheap or expensive. Learn the 4-layer framework professional investors use to assess valuation, with real examples from Adobe and NVIDIA that show why the obvious answer is often wrong.

Should you rebalance monthly, quarterly, semi-annually, or annually? We backtested the same diversified portfolio over 14 years with daily data. The results challenge what most investors assume — and point to a clear loser.

Most backtests are misleading — not because the math is wrong, but because of how they're set up. Learn the 6 most common backtesting mistakes (overfitting, short horizons, monthly data, cherry-picked periods) and how to avoid them with real examples.

Daily and monthly backtesting data produce similar returns but dramatically different risk metrics. We show exactly how much max drawdown, volatility, and Sharpe ratio change with real examples — and why it matters for your portfolio decisions.

We ran two backtests on Ray Dalio's All Weather Portfolio — one with annual rebalancing, one without. The rebalanced version returned less. But the full picture tells a different story. Here's what 4,023 daily data points reveal about what rebalancing actually does.

A single P/E ratio tells you almost nothing. Learn how to track a company's P/E over time, compare trailing vs forward P/E, and use profitability context to assess whether a stock is actually undervalued or just looks cheap.

We backtested the Bogleheads 3-Fund Portfolio (VTI, BND, VXUS) against the S&P 500 over 14 years using daily data. See the real performance, risk metrics, correlation shifts during the 2022 crash, and an AI-powered assessment of strengths and weaknesses.

Portfolio backtesting lets you test an investment strategy against real historical data before risking your money. Learn how it works, what metrics to look for, its limitations, and how to run your first backtest with real examples.

Nike is at its lowest price in nearly a decade. Revenue is declining, margins are compressing, but a new CEO is rebuilding from the ground up. We break down the fundamentals, the turnaround strategy, and the key risks ahead of March 31 earnings.

We tested a 6-ETF portfolio over 12 years and it returned 192.89% — beating its benchmark by 68 percentage points. Here's why fewer, smarter picks outperform bloated portfolios.

A data-driven breakdown of VOO vs VTI with 15 years of daily performance data. Holdings, sector overlap, risk metrics, and when one actually makes more sense than the other.

Learn how the core + satellite strategy helps retail investors balance stability and growth. Includes real backtest data comparing a diversified ETF core vs. a high-growth satellite portfolio.

Adobe is down 35% with record profits and its cheapest P/E in a decade. We break down valuation, margins, cash flow, AI risks, and what to watch at the March 12 earnings — all powered by Awalyt's fundamental analysis.

A data-driven, step-by-step guide to building a core ETF portfolio that matches your risk profile. Includes ETF analysis, correlation checks, backtesting, and the discipline most investors skip.

A practical comparison of Portfolio Visualizer, Testfol.io, PortfolioMetrics, and AWALYT. We focus on what actually matters: data accuracy, granularity, and what each tool reveals — or hides — about your portfolio's real risk.

We backtested the three most popular dividend ETFs over 14 years with daily data. SCHD, VYM, and VIG represent three fundamentally different approaches to dividend investing — here's what the numbers reveal about returns, risk, and alpha.

A portfolio of QQQ, VGT, SOXX, VTI, and 15% GLD returned +828% vs SPY's +545% over 14 years. We analyze why gold — the most boring asset — made the riskiest bet work better, with daily data, correlation matrices, and AI-powered analysis.

A data-driven comparison of SCHD, DGRO, VYM, HDV, and SPYD from 2016 to 2026. We analyze returns, risk metrics, dividend yields, and index methodologies to understand the real trade-offs behind dividend investing.

We asked ChatGPT for 3 perfect ETF portfolios and backtested them on Awalyt. Discover which AI strategy actually survived the 2022 market crash.

We backtested 60/40, 70/30, and 80/20 VTI/VXUS allocations over 14 years. See the actual returns, drawdowns, and what the data says about US vs International diversification.

Backtested portfolios with and without gold over 15 years. 20% gold reduced max drawdown by 18% while maintaining returns. See the data.