Smarter investing made simple. Optimize your portfolio like institutions do — without the spreadsheets.
TL;DR: I’m building Alphora, a portfolio intelligence app that gives long-term investors institutional-level analytics: risk-adjusted metrics (Sharpe, Alpha, Beta), diversification diagnostics, an MPT-based optimizer (long-only, fully invested), portfolio-aware news, dividend intelligence, and clean visualizations (including a network view of how your holdings relate). If that sounds useful, join the waitlist →
The problem: trackers show numbers, not decisions
Most portfolio tools do a fine job listing positions and plotting performance. But long-term investors still struggle with the real questions:
- Is my portfolio’s return efficient for the risk I’m taking?
- Where am I unintentionally concentrated; sector, geography, or single-name risk?
- When should I rebalance, and by how much?
- How do dividends actually contribute to my total return and future income?
- Which news actually matters to my portfolio today?
The current market is crowded with trackers, research portals, and all-in-one finance dashboards. Useful, yes — but they’re either content-heavy, execution-first, or analytics-light. Rarely do you get actionable, portfolio-specific analysis that tells you what to do next.
What I’m building with Alphora
Alphora turns portfolio theory into practical guidance. It’s built for long-term, data-savvy investors (and anyone who wants to think like one).
1) Practical Modern Portfolio Theory (MPT)
- Risk-adjusted metrics: Sharpe, Sortino, Alpha, Beta, Information Ratio, drawdowns.
- Contribution to risk per holding: see what actually drives your volatility.
- Efficient-frontier optimizer (long-only, fully invested): pick low/medium/high risk, get target weights and drift-based rebalance suggestions.
2) Diversification & factor clarity
- Exposure by sector, region, currency; correlation & covariance between holdings.
- Factor-style hints (growth/value, large/small) to spot hidden tilts.
3) Dividend intelligence
- Dividend history and growth rate, yield on cost, and portfolio-level income view.
- Simple forward income estimates and payout timelines.
4) Portfolio-aware news
- A newsfeed filtered by your actual holdings, with quick sentiment/context.
- Earnings calendar & concise earnings-report summaries for positions you own or watch.
5) Visual insights that explain themselves
- Clean dashboards plus a network graph (nodes = securities; edges = covariance/news relationships) so you can see concentration and contagion risk.
- “Why it matters” tooltips on every metric to keep things beginner-friendly.
How it works (high level)
Under the hood, Alphora ingests pricing, fundamentals, and news via APIs and computes the statistics on the fly:
- Builds a variance–covariance matrix across your holdings.
- Computes risk/return metrics and efficient-frontier points subject to long-only and fully-invested constraints.
- Monitors allocation drift and highlights minimal-change rebalance paths.
- Maps news to your securities and surfaces what matters for your portfolio today.
- Tracks dividend events to show total return and income trajectory clearly.
No spreadsheets. No PhD required. Just credible math, presented clearly.
Who it’s for
- Long-term investors who want to understand risk and diversify intelligently.
- Dividend & retirement investors who care about income reliability and growth.
- Data-curious users who appreciate transparent metrics with plain-English explanations.
(Traders and live options Greeks are on the roadmap, but the core is long-term, fundamentals-plus-risk.)
What makes Alphora different
- Institutional analytics, democratized: Full MPT toolset with explanations.
- Actionable, not generic: Portfolio-aware news, earnings, and rebalance guidance.
- Clarity by design: Visualizations that teach as they inform (risk contribution, network graph, scenario nudges).
- Dividend-first view of total return: See how income actually drives your results.
Roadmap (building in public)
- AI Screener: Personalized ideas to reduce concentration and improve diversification.
- Portfolio forecasting: Forward views that account for dividends, volatility, and drift.
- Time-series modeling: Research phase on transformer-style models for price/income scenarios (positioned as foresight, not fortune-telling).
- Broker integrations & timelines: Clean transaction history (buys/sells/dividends) and simple import.
If you want early access, feedback privileges, and a say in what ships first, hop on the list.
Join the waitlist
I’m building Alphora to give individual investors the same analytical edge institutions take for granted; minus the complexity. If that resonates:
👉 Join the waitlist at alphora.com
No spam. Unsubscribe anytime. And of course: nothing here is investment advice.
