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Ask More Questions, Find More Answers

A fraction of the time

No spreadsheets, no coding. Stop wasting time with manual work.

Data is built into the system and analytics are calculated on-the-fly. Get to answers to your questions in seconds, not hours. Compare us to Excel or Matlab

More intelligent questions

Finance-specific analytics tools at your fingertips.

Custom metrics, regressions, factor sensitivities, backtesting, event studies and more. All built-in and ready to go

Iterate in an instant

Financial analysis is an iterative process. Iterate more effectively.

Analyze your data in multiple ways with just a few clicks. Collaborate on analyses with other users and build upon existing work to gain new insights.

An end-to-end analytics platform

Get Data

Seamlessly analyze millions of datasets.
Data is piped in automatically from Quandl. We currently offer financial and market data but more datasets are coming soon. Examples of datasets that we plan to add:
  • Operating data
  • Social sentiment
  • Consumer spending
  • Point of sales
  • Analyst estimates and more
Alpha Hat is smart enough to work with any dataset. Just ask!

Organize Data

We organize data for you so that you don’t have to.
Our proprietary data model knows how to deal with data. Stop wasting time structuring your data manually, we’ll do it for you.
    Examples of how Alpha Hat organizes data
  • Time series alignment
  • Classifications and aggregations by sectors, deciles and more
  • Weighting by market cap
  • Rebalancing

Analyze Data

Finance-specific analysis, on-the-fly.
Unlike traditional terminals, Alpha Hat can handle calculations on-the-fly. Prebuilt analysis functions mean that you can find relevant answers in seconds. Alpha Hat functions build upon each other like building blocks to make your analyses more powerful than ever.
  • Current analysis functions
  • Custom metrics
  • Regressions & correlations
  • Factor sensitivities
  • Event studies
  • Calculating alphas
  • Screening & backtesting

Present Data

Share. Collaborate. Iterate. Understand.
Our built-in graphics engine allows you to present your findings intuitively and clearly.
Share and collaborate on your analyses with colleagues and clients with ease. Every analysis can be fine-tuned to run for a different sector, time range, perform additional computations, etc.
Financial analysis is inherently iterative but existing workflows make this process cumbersome. Alpha Hat lets you iterate in seconds.

No more manual work, no more time-wasting

Bloomberg

No calculations on-the-fly

  • Focus is on data, not analytics
  • Data gets exported to other tools for in-depth analysis

Excel

Limited results, much frustration

  • Import data from external sources
  • Spend time manually organizing data
  • Basic analytics functions
  • Error-prone
  • Iteration is a pain

R, Matlab, etc.

Ad-hoc coding = wasted opportunities

  • Steep learning curve
  • Difficult to get started
  • Not amenable to sharing computation steps
library(Quandl)

tickers = c("AAPL", "GOOGL", "MSFT", "ORCL", "IBM", "INTC", "CSCO", "QCOM", "EMC", "HPQ")

grossProfitPrefix = "SF1/"
grossProfitSuffix = "_GP_ART"

totalAssetsPrefix = "SF1/"
totalAssetsSuffix = "_ASSETS_ARQ"

grossProfitCodes = paste(paste(grossProfitPrefix, tickers, sep=""), grossProfitSuffix, sep="")
totalAssetsCodes = paste(paste(totalAssetsPrefix, tickers, sep=""), totalAssetsSuffix, sep="")

grossProfit = Quandl(grossProfitCodes)
totalAssets = Quandl(totalAssetsCodes)

forwardFill <- function(data) {
	for (i in 2:dim(data)[2]) {
		for (j in 2:dim(data)[1]) {
			if (is.na(data[j,i])) {
				data[j,i] <- data[j-1, i]
			}
		}
	}

	return(data)
}

grossProfit = forwardFill(grossProfit)
totalAssets = forwardFill(totalAssets)

combinedDates = intersect(grossProfit[,1], totalAssets[,1])
combinedDates = combinedDates[as.Date(combinedDates) > as.Date("2010-12-31")]

grossProfit = grossProfit[match(combinedDates, grossProfit[,1]),]
totalAssets = totalAssets[match(combinedDates, totalAssets[,1]),]

grossProfitDividedByTotalAssets = cbind(combinedDates, grossProfit[match(combinedDates, grossProfit[,1]),2:dim(grossProfit)[2]] / totalAssets[match(combinedDates, totalAssets[,1]),2:dim(totalAssets)[2]] )

matplot(as.Date(grossProfitDividedByTotalAssets[,1]), grossProfitDividedByTotalAssets[,2:11], type="l", xaxt="n", ylab="Gross Profit Divided By Total Assets")
title("Mega Cap Technology Stocks Gross Profit Divided By Total Assets")
axis(1, as.Date(combinedDates), format(as.Date(combinedDates), "%m-%Y"), cex.axis = .7)
legend(locator(1), tickers, lty=1)
      

Simple, intuitive, fast

  • Data built-in
  • Powerful, finance-specific functions
  • Calculations on-the-fly
  • Share your analysis easily

Step 1: Start with something simple

Step 2: Gain greater understanding with a couple of clicks

Step 3: Look at data in new ways, in seconds

Designed for an iterative process

Collaborate on analysis

Every analysis can be fine-tuned to run for a different sector, time range, perform additional computations, etc.

Share living analysis with your colleagues, clients, and partners.

Get in contact with Us

info@alphahat.com
Alpha Hat, Inc.
1460 Broadway, 10th Floor
New York, NY 10036