mostlyfintech

[mostlyfintech]

i like docker -P

I don't know when -P was introduced, but it's much better than -p. Basically it automatically assigns a port for every port that's exposed within the docker container.

docker run -e ASPNETCORE_ENVIRONMENT=Test -d -P mytaggeddocker

[mostlyfintech]

Never user a timestamp site again

Timestamp sites are garbage.

Instead in chrome it ctrl-shift-j to open the console

> Date.parse("2001-01-01") / 1000 978307200

> new Date(978307200 * 1000) Sun Dec 31 2000 19:00:00 GMT-0500 (Eastern Standard Time)

Congratulations, you just discovered what happens when you swap between local and UTC timezone. To reconcile that...

> new Date(978307200 * 1000).toISOString()

"2001-01-01T00:00:00.000Z"

And since you didn't ask... we're multiplying / dividing by 1000 to feed JS the milliseconds that it thinks it needs.

[mostlyfintech]

4 Fun Docker Commands

Get a nicely formatted output of CPU & Ram usage

docker stats --format "table {{.Container}}\t{{.CPUPerc}}\t{{.MemUsage}}"

Get a single metric

docker stats --format "{{.Name}}|{{.MemUsage}}" --no-stream | grep client

Deploy a docker stack

docker stack deploy -c client.docker-compose.yml client-api

Scale a service to 0 replicas/tasks

docker service update --replicas=0 client-api_master

Bonus: Pretty out the service name and port it's running on

docker service ls | awk '/client/ {print $2, $6}'

[mostlyfintech]

Convert an AWS Log dump to CSV in Python

AWS saves it’s logs as json with arrays that contain other arrays. Here’s how you blow it up into a universally accepted csv file. import pandas as pd import json, io

a = json.load(open('data.json')) z = [{y['field']: y['value'] for y in x} for x in a['results']] pd = pd.DataFrame(data=z) pdp = pd.drop(['@ptr'], axis=1) pdp.to_csv('data.csv', index=False)

[mostlyfintech]

Step-by-step how to launch Fargate containers behind a Load Balancer

[mostlyfintech]

This is a great project. Love the use of technology + art to create easily themeable svg graphics.

[mostlyfintech]

Kafka as a Messaging System

How does Kafka's notion of streams compare to a traditional enterprise messaging system?

Messaging traditionally has two models: queuing and publish-subscribe. In a queue, a pool of consumers may read from a server and each record goes to one of them; in publish-subscribe the record is broadcast to all consumers. Each of these two models has a strength and a weakness. The strength of queuing is that it allows you to divide up the processing of data over multiple consumer instances, which lets you scale your processing. Unfortunately, queues aren't multi-subscriber—once one process reads the data it's gone. Publish-subscribe allows you broadcast data to multiple processes, but has no way of scaling processing since every message goes to every subscriber.

The consumer group concept in Kafka generalizes these two concepts. As with a queue the consumer group allows you to divide up processing over a collection of processes (the members of the consumer group). As with publish-subscribe, Kafka allows you to broadcast messages to multiple consumer groups.

The advantage of Kafka's model is that every topic has both these properties—it can scale processing and is also multi-subscriber—there is no need to choose one or the other.

Kafka has stronger ordering guarantees than a traditional messaging system, too.

A traditional queue retains records in-order on the server, and if multiple consumers consume from the queue then the server hands out records in the order they are stored. However, although the server hands out records in order, the records are delivered asynchronously to consumers, so they may arrive out of order on different consumers. This effectively means the ordering of the records is lost in the presence of parallel consumption. Messaging systems often work around this by having a notion of "exclusive consumer" that allows only one process to consume from a queue, but of course this means that there is no parallelism in processing.

Kafka does it better. By having a notion of parallelism—the partition—within the topics, Kafka is able to provide both ordering guarantees and load balancing over a pool of consumer processes. This is achieved by assigning the partitions in the topic to the consumers in the consumer group so that each partition is consumed by exactly one consumer in the group. By doing this we ensure that the consumer is the only reader of that partition and consumes the data in order. Since there are many partitions this still balances the load over many consumer instances. Note however that there cannot be more consumer instances in a consumer group than partitions.

kafka.apache.org/intro

[mostlyfintech]

R: Sorting a Matrix by a Column

This one is easy. Using sort.list  to order the rows by the value of the second column.

> y = a[sort.list(a[,2]),]

You can also use the order function that has the same functionality

> y = a[order(a[,1]),]

[mostlyfintech]

R: Quantmod and PerformanceAnalytics for basic Monthly data

This one is fairly simple, but a question that I get often. How can I format OHLC data to monthly data and use it in the PerformanceAnalytics suite

Pull in the required libraries

library(quantmod) library(PerformanceAnalytics)

Get your Benchmark Data using quantmod’s getSymbols call

getSymbols("^GSPC")

create a monthly return stream using PerformanceAnalytics monthlyReturn and using the 4th column of the benchmark data, which is Close.

ret <- monthlyReturn(GSPC[,4])

Bingo! Now you can use the charts call to do something pretty with it.

charts.PerformanceSummary(ret)

[mostlyfintech]

Parsing JSON in R

A note for how to pull data from JSON and pull it through r

library(httr) library(jsonlite) api_endpoint = "https://jsonplaceholder.typicode.com" path = "/posts" url = paste(api_endpoint,path, sep="") x <- content(GET(url)) a <- matrix(NA, nrow=length(x), ncol=4) for (i in x){ a[i$id,] <- c(i$userId, i$id, i$title, i$body) } View(a)

[mostlyfintech]

Loyal3 rolls out Performance feature with an email #Fail

I’ve blogged about Loyal3′s innovative IPO-for-everyone product several times.

Today they rolled out the ability to see the performance of your investments. Unfortunately their marketing people don’t have the financial chops as their software engineers, as the photoshop mock-up got the math wrong.

In the email we see the Amount Invested is $500 & the current value as $1000 giving a return of 200%.

If a stock had a 200% change would turn $500 into $1500, not $1000.

[mostlyfintech]

LOYAL3 announces Follow-On offerings

This just arrived in my email - enjoy

Our mission is to level the playing field and provide you with equal access to investment opportunities previously only available to institutional investors and a few selected individuals. 

We began with IPOs, and today we are announcing Follow-On Offerings, fee-free and only available to the public on LOYAL3.

What's a Follow-On Offering?

A follow-on offering is when a public company, already listed on an exchange, sells additional shares to investors. The general public has typically not had access to these offerings, but LOYAL3 is changing that. Learn More 

How Does Follow-On Offering Pricing Work?

Follow-on shares are frequently, but not always, offered at a modest discount from the closing market price on the day the stock is issued. By the time follow-on shares are priced and allocated, market activity may have affected the public stock price-meaning you may receive shares at a price lower, higher, or equal to the public stock. Learn More 

What is the difference between an IPO and Follow-On Offering?

An IPO is a company's first offering of shares to the public and a follow-on is when a public company offers new shares after its IPO. Another difference is the length of the follow-on roadshow, which is usually much shorter, typically 1-5 days, whereas an IPO roadshow can last 2 weeks. 

How will Follow-Ons work at LOYAL3?

Similar to IPOs, you will select the maximum amount you would like to invest and wait for pricing and the two-hour decision window. As always, there are no fees, and you can invest as little as $100. You can cancel any time before the end of the two-hour window, which begins once final pricing is announced. Learn More 

Keep an eye out for more about follow-ons.

[mostlyfintech]

Sliced Investing launches Sliced Event Driven Fund

Word just came over the wire that the newest player in the fund of hedge fund field Sliced Investing have just registered a new Event Driven hedge fund.

This brings their portfolio to 2 products:

Sliced Event Driven Fund, LP (reported AUM: $960k)

Sliced Investing Long/Short Fund, LP (reported AUM: $750k)

The Y-Combinator alumnus offers accredited investors the ability to get into "Hedge Funds" for as little as $20k.

Secretive, as hedge funds usually are, there is not much information on the website as to how the system works. From what I have been able to gather, the allocations are made through Sliced Investing slick website, and the money is pooled into the Sliced Investing hedge funds. These hedge funds then invest the money into other Hedge Funds. (which then invest into the third party funds that Sliced Investing has sourced).

While Sliced Investing charges no fees, the investors are still paying the fees that the underlying hedge funds are charging (generally a 2% management fee & a 20% incentive fee). 

[mostlyfintech]

Mint moves into the bill pay space

Let's jump right in with the press release...

Mint Bills, available on Android, iPhone, iPad mobile devices and now the Web, helps people easily see and pay their bills in one place, so they never have to miss a payment. According to a recent McKinsey study, two out of every five Americans is living paycheck to paycheck, often struggling to balance money coming in and going out. Mint Bills takes the guesswork out of personal finances and helps consumers avoid late fees.

Here’s what’s new:

Mint Bills’ web app: Extends bill pay capability, letting people quickly register, search for and set up their billers based on their zip code. Registered users will see what bills are due and when.

Mint Bills’ mobile apps: Features several significant product improvements, including a complete redesign for Android devices. Formerly known as Check, the mobile apps simplify the registration and startup process, and adds new bill categories designed to help people find and add new bills.

“Mint has historically served as a rear-view mirror for personal finances, providing consumers a look back at their money,” said Barry Saik, senior vice president and general manager of Intuit’s Consumer Ecosystem Group. “Today, we’re taking a more forward-looking approach, helping people to anticipate and accomplish must-do financial tasks, such as paying bills, so they can feel confident and in control of their money.”

At first I was excited that we'd get a fully integrated solution with the Mint.com that I've used for the last 7 years. Unfortunately, it looks like this is an entirely different application which was purchased by Intuit and wrapped into the Mint brand. Oh well...

[mostlyfintech]

Google Ventures releases a mostly Fintech-free Year in Review

Let's all take a moment right now to bathe in the beauty of Google Venture's 2014 year-end report.

282 portfolio companies which were broken down like this

36% Life Sciences & Health

27% Mobile

24% Enterprise & Data

8% Consumer

5% Commerce

Most importantly 16 fairly visible exits

Nest

iPierian

Luvocracy

SpaceMonkey

Hubspot

Tomfoolery

Divide

Gyft

Namo Media

Ubersense

Mitro

Smarterer

Datapad

Loom

Appurify

Luminate

Among the other tidbits listed we discover that GV was responsible for 95 robot marathons.

And have a nice list of other things that GV employees did with their companies.

[mostlyfintech]

Robinhood (finally) goes live! But YOU still need to wait.

Robinhood has been promising zero-commission trading for a while now. After $16mm in funding, today they launched their mobile app.

They will start onboarding the 500,000 people who are waiting in line, but if you sign up today, you'll still need to wait at least 2 months.

Techcrunch broke the story in what is largely a puff piece on their site.

When all is said and done, while it looks like a cool app, like Loyal3 it's just a way to grab at a younger investment group.

Even with a zero-commission is just a gimmick at this point. We all know that trading is really, really cheap anyway so it's hard to image that discount brokerage houses will be able to continue charging even the $4.95/trade that currently exist.

Finally, you may ask how Robinhood makes money? They answer:

Robinhood charges interest for margin trading and collects interest on cash balances.

Robinhood is well-funded by notable investors such as Index Ventures, Ribbit Capital, Google Ventures, Andreessen Horowitz, Social Leverage, and many others, which affords us the freedom to focus on building a wonderful brokerage experience rather than short-term profits.

[mostlyfintech]

Benzinga publishes series video interviews with Fintech Awards nominees

Very interesting series of Hangout Style videos are being pushed out by Benzinga as part of their ongoing Fintech Awards series.

Shane Leonard CEO at Stockflare

Matt Porzio VP of Strategy & Product Marketing at Intralinks

Atish Davda CEO at EquityZen

Hussain Zaidi Co-Founder & CEO at Advizr 

Uri Gruenbaum CEO & Co-Founder at TipRanks

Dan Schleifer President & Co-Founder at ChartIQ

Yueyu Fu Co-Founder & CPO at Rippleshot

Gokhan Kisacikoglu at QTRADING by Quants Capital

JD Singh, Director at Vetr

Juan Colón Co-Founder & CEO at Darwinex

Evan Rapoport, CEO at HedgeCoVest

Jose Resendiz, VP at Digital Insight

CEO of Benzinga, Kyle Bazzy is doing a fantastic job running this competition and drawing much needed attention to both the fintech startups and the established companies that are competing for these awards.