alva

Alva

What is Alva

Alva is an agentic finance platform. It provides unified access to 250+ financial data sources spanning crypto, equities, ETFs, macroeconomic indicators, on-chain analytics, and social sentiment -- including spot and futures OHLCV, funding rates, company fundamentals, price targets, insider and senator trades, earnings estimates, CPI, GDP, Treasury rates, exchange flows, DeFi metrics, news feeds, social media and more!

What Alva Skills Enables

The Alva skill connects any AI agent or IDE to the full Alva platform. With it you can:

• Access financial data -- query any of Alva's 250+ data SDKs programmatically, or bring your own data via HTTP API or direct upload.
• Run cloud-side analytics -- write JavaScript that executes on Alva Cloud in a secure runtime. No local compute, no dependencies, no infrastructure to manage.
• Build agentic playbooks -- create data pipelines, trading strategies, and scheduled automations that run continuously on Alva Cloud.
• Deploy trading strategies -- backtest with the Altra trading engine and run continuous live paper trading.
• Release and share -- turn your work into a hosted playbook web app at https://yourusername.playbook.alva.ai/playbook-name/version/index.html, and share it with the world.

In short: turn your ideas into a forever-running finance agent that gets things done for you.

Capabilities & Common Workflows

1. ALFS (Alva FileSystem)

The foundation of the platform. ALFS is a globally shared filesystem with built-in authorization. Every user has a home directory; permissions control who can read and write each path. Scripts, data feeds, playbook assets, and shared libraries all live on ALFS.

Key operations: read, write, mkdir, stat, readdir, remove, rename, copy, symlink, chmod, grant, revoke.

2. JS Runtime

Run JavaScript on Alva Cloud in a secure V8 isolate. The runtime has access to ALFS, all 250+ SDKs, HTTP networking, LLM access, and the Feed SDK. Everything executes server-side -- nothing runs on your local machine.

3. SDKHub

250+ built-in financial data SDKs. To find the right SDK for a task, use the two-step retrieval flow:

1. Pick a partition from the index below.
2. Call GET /api/v1/sdk/partitions/:partition/modules to see module summaries, then load the full doc for the chosen module.

SDK Partition Index

Partition	Description
spot_market_price_and_volume	Spot OHLCV for crypto and equities. Price bars, volume, historical candles.
crypto_futures_data	Perpetual futures: OHLCV, funding rates, open interest, long/short ratio.
crypto_technical_metrics	Crypto technical & on-chain indicators: MA, EMA, RSI, MACD, Bollinger, MVRV, SOPR, NUPL, whale ratio, market cap, FDV, etc. (20 modules)
crypto_exchange_flow	Exchange inflow/outflow data for crypto assets.
crypto_fundamentals	Crypto market fundamentals: circulating supply, max supply, market dominance.
crypto_screener	Screen crypto assets by technical metrics over custom time ranges.
company_crypto_holdings	Public companies' crypto token holdings (e.g. MicroStrategy BTC).
equity_fundamentals	Stock fundamentals: income statements, balance sheets, cash flow, margins, PE, PB, ROE, ROA, EPS, market cap, dividend yield, enterprise value, etc. (31 modules)
equity_estimates_and_targets	Analyst price targets, consensus estimates, earnings guidance.
equity_events_calendar	Dividend calendar, stock split calendar.
equity_ownership_and_flow	Institutional holdings, insider trades, senator trading activity.
stock_screener	Screen stocks by sector, industry, country, exchange, IPO date, earnings date, financial & technical metrics. (9 modules)
stock_technical_metrics	Stock technical indicators: beta, volatility, Bollinger, EMA, MA, MACD, RSI-14, VWAP, avg daily dollar volume.
etf_fundamentals	ETF holdings breakdown.
macro_and_economics_data	CPI, GDP, unemployment, federal funds rate, Treasury rates, PPI, consumer sentiment, VIX, TIPS, nonfarm payroll, retail sales, recession probability, etc. (20 modules)
technical_indicator_calculation_helpers	50+ pure calculation helpers: RSI, MACD, Bollinger Bands, ATR, VWAP, Ichimoku, Parabolic SAR, KDJ, OBV, etc. Input your own price arrays.
feed_widgets	Social & news data feeds: news, Twitter/X, YouTube, Reddit, podcasts, web search (Brave, Grok).
ask	General news and market articles.

You can also bring your own data by uploading files to ALFS or fetching from external HTTP APIs within the runtime.

4. Altra (Alva Trading Engine)

A feed-based event-driven backtesting engine for quantitative trading strategies. A trading strategy IS a feed: all output data (targets, portfolio, orders, equity, metrics) lives under a single feed's ALFS path. Altra supports historical backtesting and continuous live paper trading, with custom indicators, portfolio simulation, and performance analytics.

5. Deploy on Alva Cloud

Once your data analytics scripts and feeds are ready, deploy them as scheduled cronjobs on Alva Cloud. They run continuously on your chosen schedule (e.g. every hour, every day). Grant public access so anyone -- or any playbook page -- can read the data.

6. Build the Playbook Web App

After your data pipelines are deployed and producing data, build the playbook's web interface. Create HTML5 pages that read from Alva's data gateway and visualize the results. Follow the Alva Design System for styling, layout, and component guidelines.

7. Release

Three phases:

1. Write HTML to ALFS: POST /api/v1/fs/write the playbook HTML to ~/playbooks/{name}/index.html.
2. Call release API: POST /api/v1/release/playbook — creates DB records and uploads HTML to CDN. Returns playbook_id (numeric).
3. Write ALFS files: Using the returned numeric playbook_id, write release files, draft files, and playbook.json to ALFS. See api-reference.md for details.

The playbook.json must include a type field ("dashboard" or "strategy") and a draft object. Omitting type causes wrong frontend routing; omitting draft causes the dashboard iframe to never load.

Once released, the playbook is accessible at https://yourusername.playbook.alva.ai/playbook-name/version/index.html. -- ready to share with the world.

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Detailed sub-documents (read these for in-depth reference):