Sites That Will Pay You to Test Out Websites

As a blogger, it’s important to know that my site is user-friendly. Because if I’m losing visitors due to lousy navigation, lack of clarity, poor design, or content — then I’m losing money. This is why companies will pay good money for objective third-party reviews of their website.

To do this job from home, you will need to be internet savvy and speak fluent English. You will also need some basic equipment like a computer with a microphone, broadband internet connection, and an updated web browser. Most tests take between 5 – 25 minutes to complete and pay an average of $10 per test.

If you’d like to work from home testing websites, here are 11 sites to check out.

User Testing

Earn $10/$15 for 20 minutes of work. To become a tester – submit your email address and apply. Testers must take a sample test before receiving any assignments. This gig is open to the US and International residents alike who can receive payments via PayPal. Each test takes about 15 – 20 minutes.

User Testing is open to global residents who have an active PayPal account.
Enroll

Make money by testing out websites. To enroll in the program submit your email address, password, and pick your preferred method of testing (desktop computer, tablet, or smartphone). Once you’re fully registered, you’ll receive emails when assignments are ready for you. Assignments vary in nature, as does the pay. I did one job that took less than a minute, and it paid .10 cents. Payments are made via PayPal.

Open to global residents who have an active PayPal account.
StartUpLift

Earn money by answering questions about startup websites. Each company provides their website and assigns tasks that they would like you to complete and provide answers for. After you complete the assignment, you’ll share your thoughts in a written response. Each completed test pays $5.00, and payments are made weekly via PayPal.

TestingTime

Earn up to € 50 per study. Each study is conducted via Skype and usually takes 30 – 90 minutes of time. Once the study is completed, you’ll get paid within 5 – 10 days via PayPal. Testing Time is open to global residents who have an internet connection, and Skype installed on a computer.

TestingTime is open to global residents who have an active PayPal account.
TryMyUI

Earn $10 for 15 – 20 minutes of your time. To become part of the TryMyUI team first, sign up for an account. Next, you’ll need to take and pass a qualification test. The qualification test is a sample test that shows you understand the process and requirements. After you qualify, you’ll be sent test opportunities via email. Payments are made biweekly via PayPal.

Userfeel

Get paid $10 for providing your thoughts on various websites. To become a website tester, register for an account, and take a sample test. Once your sample is approved, you’ll start getting assignments by email. Payments are made via PayPal at the end of each week.

Userlytics

Make money for providing feedback on websites, applications, prototypes, concepts and more. To apply, register for an account, and then wait for an invite to complete an assignment. Once you’ve completed your assignment, you’ll be paid $10 per task via PayPal.

UserZoom

UserZoom is a company that conducts website usability tests for desktop and mobile platforms. Tests pay an average $5 to $10 depending on the complexity of the study. Most tests take between 10 to 20 minutes to complete, and payments are made via PayPal 10 to 14 business days after the completion of the study.

Validately

Validately hires testers to complete mobile and website tests for companies. Compensation varies: Complete a 5-minute test and get paid $5 bucks. Live tests where you speak via phone and share a screen with a moderator, pay a minimum of $25 for 30 minutes. Payments are made via PayPal within five business days of the test.

WhatUsersDo

Get paid to give feedback on clients’ websites. To get started, fill out the application and take a sample test. Once you’ve been approved, you’ll receive assignments via email. Each test takes about 20 minutes to complete and pays 8 £ or around $12.50 US dollars. Payments are made via PayPal on the 25th day of each month.

WhatUsersDo is open to global residents who have an active PayPal account.
uTest

uTest hires independent contractors for quality assurance testing for various software and hardware. According to their job posting on Dice, their customers includes brands like Google, Amazon, Netflix, and more. To get started, fill out their online application (takes approximately 10 minutes), take an audition test to showcase your tech skills, then wait for assignments to be sent to you via email. I wasn’t able to find out how much testers are paid, but the job listing on Dice says, “In 2016 alone, we paid out over $20 million to QA testers worldwide.”

uTest is open to global residents
Now if you’re anything like me, you’re multiplying how many tests you can complete in an hour and how much you’re going to make. But hold your horses! These opportunities are extremely popular! Statistically, there are fewer customers than testers, so don’t expect to be completing three tests every hour on the hour.

Here’s how to make the most of this work-at-home opportunity:

1. Sign up with as many website testing companies as possible.

2. Be sure that you’re taking advantage of practice and sample testing opportunities, as many companies will only allow you a couple of times to pass their test.

3. Always make sure to turn in your best possible work, as many companies rate their testers and those with higher scores tend to get more and better-paying gigs.

4. While you’re waiting for these companies to email you with test opportunities, be sure to add short tasks, focus groups, and digital earning tasks to your routine — this will ensure that you have a constant pipeline of work and income coming in.

And if you’re located outside of the U.S. — check out this post, it has a bunch of opportunities for global residents!

Looking for more gigs like this one? Then consider working from home as a Web Search Evaluator — this post will tell you all about it.

This page includes some affiliate links. Please be aware that we only promote advertising from companies that we feel we can legitimately recommend to our readers. Please see our disclosure policy for further information.

PLATFORMS THAT MATTER FOR YOUR BUSINESS.

Social Media Rule #1: Make it a two-way conversation.

With so many Social Media channels, it’s easy for businesses to jump in with arms wide open and then realize Social Media is not what they expected. Perhaps you’ve been dipping your toes in Social Media for your business. You’re starting to see some Facebook comments, or retweets, or LinkedIn comments, or re-Pins. However, you wonder if you’re spending time and resources in the right channels. You also wonder if all these posts you’re creating are increasing your business’s bottom line. We can help answer your questions.
Social Media Astekweb

Social Media Strategy
Partnering with you and your team, we start with an audit on where you are at with your Social Media efforts as baseline. During the audit, we assess the following:

Target audiences
Content engagement
Content topics and themes
Channel approach
Editorial calendar
Social Media Policy
Employee Social Media guidelines
Escalation plan
Integration with other marketing efforts
Feedback process for insights gathered from social conversations
Metrics and KPIs
Based on the assessment, we will create a strategic Social Media framework that will allow your business to better leverage Social Media.

Social Audit
The Social Audit includes a Brand audit as well as Content Asset Audit with your stakeholders. The stakeholder interviews are the most effective way to get internal perspectives on Social Media Strategy approach and objectives within your team or organization. With the Content Asset Audit, it is often where we discover content gems, such as videos, images, white papers etc, that were previously created but never utilized by businesses.

Competitive Analysis
Have you ever wondered how your competitors’ Social Media analytics look like compared to yours? We are well-versed in social analytic tools and can provide you with detailed reports on competitive intelligence and Social Media measurements. See how you and your competitors differ in engagement, social media content optimization, fans & followers insights and more.

Social Listening
Aside from your business’s Social Media channels, do you know what the rest of the internet thinks about your business? Are there any social chatters about your brand that you may not be aware of? This is where Social Listening will be most helpful. We can help you setup and maintain a Social Listening program to see what type of conversations about your business, if any, are happening, and also where they are occurring online.

Social Content Creation
Are you strapped for time & resources and could use a hand in social content creation? We can help you create “snackable” and relevant social content that drive conversations and engagement on your social platforms.

Blogger Outreach
Working with the right bloggers can do wonders to your social marketing efforts. Not only can we help you identify the right bloggers who are relevant to your business, we can also work with bloggers to develop social media marketing / blogging programs that market your business.

Paid Social Media Support
You’ve worked hard (or we’ve helped you) to develop Social Media content regularly. Your carefully-crafted content has been published. Facebook, Twitter, LinkedIn and many more upcoming social platforms provide self-service paid support. We can help you setup and manage your paid social campaigns, with ongoing optimization as needed.

Our solutions help businesses work smarter and more profitably by delivering technology and value-added services.

MAKING TECHNOLOGY WORK

Microsoft Azure

With Azure, you get the freedom to build and deploy wherever you want, using the tools, applications, and frameworks of your choice.

Dynamics 365

With intelligent business applications across CRM and ERP, Microsoft Dynamics 365 gives you choice. Start with just what you need to run your business—and delight your customers. And then add apps as your needs change.

SharePoint Online

SharePoint Online empower individuals, teams and organizations to intelligently discover, share, and collaborate on content from anywhere and on any device. It helps facilitate teamwork, automate business processes, create business applications, and build com

Power BI

Power BI transforms your company’s data into rich visuals for you to collect and organize so you can focus on what matters to you.

SQL Server

Build intelligent, mission-critical applications using a scalable, hybrid database platform that has everything built in—from in-memory performance and advanced security to in-database analytics.

Amazon Web Services (AWS)

Whether you’re looking for compute power, database storage, content delivery or other functionality, AWS has the services to help you build sophisticated applications with increased flexibility, scalability

Project Online

Streamline project, resource, and portfolio management with Microsoft Project & Portfolio Management (PPM). Integrated planning tools help you keep track of projects and stay organized.

Technology is the first order of business for you…
and we make technology work for you.Technology is a great enabler of productivity, creativity, and effectiveness but only if it is fully adopted.

LAMP vs MEAN, Deciding the right stack for your startup

Move over LAMP. MEAN is the new kid on the block.

It’s what all the trendy startups are using. It’s fun. It’s hip. It’s new. MEAN is taking over the web development world. But how does the stack stack up?

What’s LAMP?

Linux, Apache, MySQL and PHP. The holy grail of web development for at least as long as I can remember. This stack represents the foundation of the web.

While its age may be showing, its maturity is strong. The LAMP stack can be altered to replace MySQL with MonogDB, and PHP with Python. The acronym defines a low level configuration for web applications.

What’s MEAN?

MongoDB, ExpressJS, AngularJS and Node.js makes up the MEAN stack. A powerful JavaScript driven stack with diverse capabilities.

Comparatively to LAMP, the database layer is replaced completely with JSON storage using MongoDB. JSON is the native data language of JavaScript. While relatively young, the framework has a growing number of supporters.

This stack is basically a JavaScript lover’s dream.

Which to Choose?

As always, the answer is: it depends.

Both stacks have advantages and disadvantages. Which one to use depends on the type of web application to be built. Providing a blanket statement of superiority would be greatly oversimplifying software development.

Isn’t PHP Dying?

This has long been cried by the anti-PHP crowd. For years we’ve been hearing that PHP is on the way out. Yet PHP maintains a stronghold on the Internet. It powers an insanely high number of websites globally.

PHP has undergone major revamping through its recent major releases. PHP 7 is just around the corner, expected to bring along language and performance improvements.

Possessing a long history and maintaining backwards provides a disadvantage of innovativeness. Especially in comparison to the light development history of Node.JS. Node.JS however doesn’t offer the same level of maturity. Over time, libraries and frameworks will be built to further improve the infrastructure of Node.JS. Regardless, PHP isn’t going to die any time soon.

JavaScript on the Front, JavaScript on the Back

One common touted advantage of using JavaScript for both the server and the client is code reuse.

While it sounds good in theory, it’s rarely seen in practice. Separation of concerns is a very good thing. Keeping server and client codebases separate can have security benefits. It’s just not a common case to have to move a function from server to client.

Using JavaScript for both the front and back end however may make it easier for some teams to easily switch developing between the two. It creates a more homogeneous workflow. This is especially important when you have one or two full stack developers working on the application as a whole.

It can be quite a challenge to switch between using PHP or Python for the server, then having to use JavaScript and HTML for the client. If you only know JavaScript and nothing else (which could be the case for a new programmer), then MEAN is the easier choice.

If a MEAN stack makes your development life easier, then you should probably choose that.

End Users Could Break Your Website

It’s difficult to predict future behavior of consumers.

Ad blocking has become more commonplace as of recent years. Privacy has become an increasing concern. While most users have JavaScript enabled, some users do not. Some users disable JavaScript to better protect their privacy. Others don’t like unknown code to be executing on their machines.

Various browser extensions allow users to selectively choose which scripts they permit to run. And which they don’t. This may effectively break your web application if it’s dependent on JavaScript.

You might not need to cater for users with JavaScript disabled. Many web applications, like Facebook, are practically useless without JavaScript enabled.

Some users may even use client readers such as Pocket to circumvent visiting your website altogether. Considering today’s options for digesting content, it wouldn’t make a whole lot of sense for a blog to be accessible only with JavaScript enabled.

Disabling JavaScript in your browser can make a lot of the web unusable. AdBlock has been known to break a few websites too. Some websites have countered the rise of AdBlock by neglecting or even banning that segment of users.

JavaScript certainly helps add a modern dimension to web apps. It might not even be feasible to cater for users with JavaScript disabled. Still, accessibility and compatibility is a factor to take into account. MEAN depends on JavaScript. If users disable JavaScript, they’ve killed your web app.

What might be uncommon today may become more common tomorrow. Utilizing lots of JavaScript on the client’s side may turn to backfire if they opt not to run it. The user’s browser is outside of your control.

JavaScript Slows Down the Browser

Speed is another concern.

If you’re developing for any non-first world country, then relying on a JavaScript heavy frontend is probably not the best choice. On older phone devices especially, performance can be slowed down to a crawl. Sometimes it can be cubersome to load even jQuery, let alone processing-heavy AngularJS for modulated views.

Wait, Isn’t Node.JS Super Fast?

Node.JS is incredibly quick. When optimized, so too is PHP.

Node.JS has an advantage of being event-driven (illustrated above). This allows many concurrent requests with less slowdown. Traditional Apache setups are multi-threaded and resource heavy. As a result, LAMP can be slow.

PHP’s speed can be dramatically enhanced through the use of Nginx, Lightspeed or optimizing Apache configuration. While Apache is multi-threaded in nature, Nginx is more similar to the event-driven nature of Node.JS.

For the most part, Apache can be replaced with Nginx in many LAMP based applications. However, an optimized setup requires additional complications and expertise. Considering how many existing scripts and virtual machines automate the setup process, this isn’t too much of a problem.

While Node.JS can be easily configured, setting up a well performing LAMP stack (or LNMP, replacing Apache with Nginx) can add a little extra time to configure.

These speed differences are likely not to become problematic until heavy load is experience. Most startups never live long enough for this to even be an issue. Scaling is a good problem to have. If you need to scale, then that means your startup is doing something right.

Both LAMP and MEAN virtual machines can be spun up really quickly for development, testing and even production. Node.JS has some advantages for future scaling. But that’s not to say that LAMP can’t scale.

Don’t Neglect the Client

What’s neglected in a lot of speed comparisons is the client side processing. Most servers can serve up pages relatively quickly – within fractions of a second.

Where users are left waiting is from loading up client-side resources like CSS, JavaScript, images and video. For speed improvements, developers should place most of their attention on the client side rather than the back end. A fraction of a second speed improvement is negligible when most websites take much longer than two seconds to load.

Especially on mobile devices, modern JavaScript intensive web applications can be slow. Web apps are cool, but sometimes you’re probably better off developing a native mobile app. To get high performance from mobile web apps, you generally need to cut back on the JavaScript libraries.

AngularJS, while bundled in the MEAN stack, is an independent JavaScript client side library that can easily integrate into web applications. Including LAMP based stacks. Adding more and more client side processing by including additional JavaScript libraries can significantly slow down an application. This slow down really has very little to do with the stack itself. Both LAMP and MEAN applications can become incredibly slow once lots of client side resources are added.

Further speed optimizations can be obtained through utilization of CDNs, lazy loading, resource minification and minimizing the total number of requests.

The Unfair “A”

There’s no direct replacement for AngularJS in the LAMP stack. MEAN cuts out the HTTP server (the Apache in LAMP) completely since Node.JS runs independently (though in a production environemnt you may very well add a HTTP server). AngularJS is also an independent framework that could be added to any LAMP stack.

In this sense, comparing LAMP to MEAN is unjust. MEAN includes a front end component, whereas LAMP refers to just the back end. LAMP refers more to low level, whereas MEAN is more high level. There’s no operating system reference in MEAN, though you’ll most likely borrow Linux from LAMP.

There’s no reason you couldn’t add a front end component to LAMP. In fact, most implementations do. At the very least jQuery is usually added, or sometimes Backbone.js. There’s nothing preventing you from using AngularJS on top of LAMP. Or replacing AngularJS in a MEAN stack. There are also many competing libraries to choose from (like React and Ember).

MEAN does have the advantage in that it’s more GUI-focused. The GUI is baked into the stack itself, instead of being left outside.

When Would I Use LAMP vs MEAN?

It probably wouldn’t make much sense to migrate an existing LAMP application to MEAN. But if I were starting a brand new UI-focused application, I’d probably opt for a MEAN (or maybe MEN, cutting out AngularJS and possibly replacing it with something else).

Whether or not I’d use MongoDB or MySQL would depend on the type of data being planned to store. I may very well set up both. Or if it were a really data heavy application that required quick searches, I may even add in ElasticSearch or Solr.

If all you need is a simple website, it’d be quite foolish to opt for MEAN. LAMP topped with a powerful CMS like WordPress or Drupal can meet the needs of many business websites. For most eCommerce businesses, there’s plenty of existing software to handle the job. MEAN should only be considered for tech-heavy businesses.

Too many times I’ve seen startups struggling with their software development because they’ve opted for new and cool over mature and stable. Just because you can do just about anything in LAMP/MEAN, doesn’t mean you should. You should use the best tool for the job. If you want to adopt a new technology, be prepared for potential debugging nightmares and a lot of reinventing the wheel.

Another thing to consider would be the team. PHP programmers are generally much more common. Subsequently, PHP programmers can be hired for lower costs than Node.JS programmers. If I were working with a team that knew PHP well, but wasn’t experienced with Node.JS, then it probably wouldn’t be worthwhile to teach the whole team a new development platform. Or vice versa. You need to stick with what you know.

If I were building a backend API, I’d probably almost always choose a LAMP based stack, opting for Python and perhaps MongoDB (and probably ditching Apache in place of Nginx). There are many REST libraries written to make your life easier.

A startup’s success is not determined by its stack
Although a lot of dogma exists in software development, there really isn’t any better or worse. Software developers tend to become emotionally attached to one platform over another as it requires an enormous amount of personal investment (in the form of time and effort) to master a platform. New developers may be fond of MEAN, whereas older developers are probably more likely to cling onto LAMP.

Deciding between LAMP and MEAN is really project specific. Depending on available skills, business constraints and application demands, one could be forgiven choosing either option.

What we need to keep in mind is that a startup’s success is not determined by its stack. What determines success is execution. Time spent between contemplating LAMP vs MEAN can usually be better spent elsewhere. Like, actually obtaining customers and figuring out what you need to build.

AngularJS removes the need to manage the DOM. This allows for pretty applications, but difficult for search engine parsing. If SEO is an important marketing channel for you, then utilizing AngularJS might not be such a great idea. Google will probably become better and add support for such web apps in the future, but right now we’re out of luck.

It Doesn’t Have to Be One Or The Other

Some applications you may have both stacks. You may have LAMP for the API, and MEAN for the GUI.

The technologies in each stack are not exclusive. You may use a relational database like MySQL or PostgreSQL, or a non-relational database like MongoDB or Cassandra.

You may choose to utilize JavaScript and Python. Or PHP. Or Go. Maybe even Erlang. Or one of hundreds of other programming languages that may suit your project better.

Your final stack may not neatly fit into an existing religious acronym. That’s perfectly okay too.

Top Programming Languages Used in Web Development

With the popularity and advancements in web technology, it is imperative for every business to have a website and one which is highly functional and visually attractive. The process through which a good website, mobile apps or other similar platforms are created is known as web development. One of the most integral aspects of web development is web programming that is achieved with the help of programming languages. Web development languages are the platforms through which instructions are communicated to a machine and actions are pursued.

In this article, we shall learn more about 1) web development and programming languages as well as 2) focus on the most popular programming languages in the world.

WEB DEVELOPMENT: AN INTRODUCTION

Web development is a term that is used to refer to the process of creating a website and can range from developing a single simple page to a series of complex pages. Web development encompasses several actions or practices and some of them include web design, content creation, programming, network security tasks as well as client side or server side scripting, etc. In the recent few years, web development has taken the definition of the creation of content management systems or CMS, which is the mid-step between the user and the database. In order to pursue web development as a profession, one of the most important things that you will need to consider is having expertise in programming languages.

WHAT ARE PROGRAMMING LANGUAGES?

A programming language is used to control the actions of a machine. Such a language is a properly drafted or constructed language when it is designed in such a way that through it instructions can be communicated to a computer system. Ever since the invention of computers, thousands of programming languages have been created, and more are being created every year.

A programming language is generally split into two components that are the semantics and the syntax. Where on one hand the syntax is the form or type, the semantics are the meaning of that type or form. Every programming language is different; where on one hand, some may be marked by a specification documents, others may have a dominant implementation or a reference. A programming language thus broadly is a notation that helps to write programs that are identified as an algorithm.

Traits of a programming language
The features or characteristics of a programming language can be referred to as its traits. The following are the three main traits of such languages that you must know about:

Abstractions – Most of the programming languages have certain rules that help us define or mark the data structures as well as manipulate the way in which the commands are executed. These rules are referred to as abstractions. Every language needs to be supported by sufficient abstractions and this need is defined by the abstraction principle. The abstraction principle in some cases is derived as the recommendations given to a web programmer so that he/she makes the correct use of abstractions.
Function and target – When you make use of a programming language, then besides doing the writing work on your own, you also need the help of the computer system that performs the computation work or controls the algorithm. The computer also controls the external devices associated such as the printer, the robots, etc. Thus, the complete definition of a programming language includes a description or a machine or processor that has been idealized for that language. This is one reason why programming languages differ from human languages of interaction.
Expressive power – Languages are mostly classified by the computations that they are able to express. This very expressive power is yet another trait of programming languages and is an important one.
Factors to be considered when choosing a programming language
Since there are so many different types of programming languages, it can be difficult for a web developer to select which one to use and which one to leave. There are certain factors on the basis of a decision can be made, and they are given as follows:

Targeted platform – The first thing you need to decide is where the program will be run. Not all languages are capable of running on all kinds of platforms. For example, a program written in C language requires compilers to run on Windows and Linux based systems.
Language domain match – The language must be chosen on the basis of the problem domain that you have. One of the better ways to do so is by searching that language others in the same domain or industry are using or by trying to look for a code that resolves the issues that you may have.
Efficiency – The compilers that go well with the language you choose must be efficient so as to make the language perform fast.
Elasticity and Performance – The language you choose must be flexible enough to let you add more programs or features in it. Also, its overall performance must be to your suitability and liking.
Availability of libraries – There must be a library that is capable of solving all your problems with the language that you select for web development.
Project size – There are two types of programming’s: large and small. You must select a language that can support your cause and suits the project size well.
Expressiveness & Time to production – Make sure you pick that language that is highly expressive and the time taken to produce the programs or codes is not very bothersome to you.
Tool support – Buy a tool-oriented language that offers you many elements and ways to edit, control and work.
Evolution of Programming Languages

THE MOST POPULAR PROGRAMMING LANGUAGES

The universe of programming languages is wide and knowing all or learning each one of them is neither practical nor possible. If you are a developer who is interested in learning the most useful and popular ones, then you must first know which ones of the thousands of languages to learn. Thankfully, there are certain websites and platforms that create lists of the top languages, according to their popularity. The list of the top 15 programming languages of this year are given below, and it is clear that JavaScript is the most popular followed closely by Java, Python, and others.

Top 15 programming languages in 2015
JavaScript
Java
Python
CSS
PHP
Ruby
C++
C
Shell
C#
Objective C
R
VimL
Go
Perl
Let’s learn about some of these top languages in detail.

1. JavaScript
JavaScript is one of the most popular and dynamic programming languages used for creating and developing websites. This language is capable of achieving several things including controlling the browser, editing content on a document that has been displayed, allowing client-side scripts to communicate with users and also asynchronous communication. It was developed by Netscape and borrows a lot of its syntax from C language. JavaScript is used very widely and effectively in creating desktop applications as well as for developing games.

One of the best things about JavaScript for you as a developer or a website owner is that this is one of the few programming languages that are accepted and supported by all the major browsers without the need of any compilers or plug-ins. It can also be worked with on platforms that are not web-based, for example-desktop widgets and PDF docs. This is a multi-paradigm language which means that it has a combination of features. Also, JavaScript supports functional and object-oriented programming styles.

The features of a language define the way it will work, the way it responds, how easy is its code and what it can achieve. The following are some of the main features of JavaScript programming language for your reference:

Structured – JavaScript is a highly structured language with a proper and planned syntax that has been derived from C. This language too has a function scoping by it lacks block scoping, unlike C. It too differentiates between statements and expressions, just like the fundamental C web programming platform.
Dynamic – The types in JavaScript are not related with variables but with values. This is a dynamic programming language that enables you to test the type of an object in many different ways. Also, this programming language is object-oriented where all the objects are associative arrays.
Functional – All functions in JavaScript are objects and are all first-class. They are associated with their own functions as well as characteristics. For example, a function within a function is called a nested function whereas this language also supports anonymous function.
2. Java
Java is yet another highly popular and widely used language that you can consider for web development. This language is an object-oriented, class-based and concurrent language that was developed by Sun Microsystems in the 1990s. Since then, the language continues to be the most in-demand language that also acts as a standard platform for enterprises and several mobile and games developers across the world. The app has been designed in such a way that it works across several types of platforms. This means that if a program is written on Mac Operating system then it can also run on Windows based operating systems.

Java, when it was designed originally, was developed for interactive television, but the developers realized that this language and technology was way too forward for this industry. It was only later that it was incorporated into the use it serves today.

Every language is created with a certain mission, goal or objective in mind. The following are the 5 major principles or goals that were kept in mind during the creation of this language:

It must be a secure and robust programming language
It must be an object-oriented, simple language which becomes familiar soon.
It must be capable of being implemented and executed with high performance.
It must be threaded, dynamic and interpreted.
It must be portable and architecture-neutral.
3. Python
Python is a highly used and all-purpose programming language which is dynamic in nature. Being dynamic in nature means that you as a developer can write and run the code without the need of a compiler. The design of the language is such that it supports code readability which means that its syntax is such that only a few lines of codes are needed to express a point or a concept. This concept of code readability is also possible in the case of Java and C++, etc. This is a high-level or advanced language that is considered easy for beginners to understand and learn.

Some of the apps that are powered by Python are Rdio, Instagram, and Pinterest. Besides this, some other web platforms that are supported by Python are Django, Google, NASA, and Yahoo, etc. Some of the other features of this language include automatic memory management, large library, dynamic type system and support of many paradigms.

Python works on a core philosophy and follows its main principles in all seriousness. The language was designed with the aim of making it highly extensible. This means that the language can easily be incorporated or embedded in existing applications. The goal of the developers of this language was to make it fun to use one. The developers worked on the language in such a way that it could reduce upon premature optimization. Here’s a look at some of the principles that have been summarized for you:

Readability is important
Complex is better than complicated-
Beautiful is better than ugly
Simple is better than complex
Explicit is better than implicit
4. CSS
CSS or Cascading Style Sheets is rather a markup language. When paired with HTML, CSS allow a developer to decide and define how a web page or a website will eventually look or how it will appear to the visitors of the web platform. Some of the elements which CSS has an impact on include font size, font style, the overall layout, the colors and other design elements. This is a markup language that can be applied to several types of documents including Plain XML documents, SVG documents as well as XUL documents. For most websites across the world, CSS is the platform to opt for if they need help to create visually attractive webpages and finds use not just in the creation of web applications but also mobile apps.

The language’s syntax is pretty similar to that of HTML and XHTML, which work well in synchronization and combination of one another. The Style sheets included in CSS consist of a selector and a declarator. The simple syntax of the language uses several English language words to define the styling properties.

5. PHP
The term ‘PHP’ is used to define PHP Hypertext Processor language that is a free server-side scripting language that has been designed for not just web development but also as a general-purpose programming platform. This is a widely used language that was created in the year 2004 and now powers over 200 million websites worldwide. Some popular examples of websites powered by this platform include Facebook, WordPress, and Digg.com.

PHP is an interpreted script language which means that it is usually processed by an interpreter. For this reason, the language is most suitable for server-side programming that have server tasks being repeatedly performed when the website development process is on.

The following are some more points that shall help you understand the language better:

PHP is an open source language and fast prototyping language.
This language is compatible with UNIX based OS as well as Windows OS.
Some industries where PHP is mostly used include startup businesses, advertising apps, and small software organizations as well as media agencies.
The language can be embedded in HTML directly.
6. Ruby
Developed in the year 1993, Ruby is a dynamic programming language that is used for the creation or programming of mobile apps and websites. The language successfully balances imperative programming with functional programming and is a highly scalable language. This open source platform is not only simple to understand but also easy to write. But if you are a developer who wants to learn Ruby, then you will also have to equip yourself with the knowledge of Ruby on Rails or Rails which is another framework which can help you make it interesting to deal with Ruby. For those who are interested in creating small business software and for those who are into the field of creative designing, Ruby is the perfect programming language.

During its development, the idea was to come up with a language that was more productive in terms of programming and has a concise and simple code. Ruby is mostly used in the web servers where there is a lot of web traffic. Some examples of platforms that make use of this programming language include Hulu, Twitter, and Scribd, etc.

7. C++
C++ is a general purpose, well compiled and case sensitive web programming language that is not only imperative but also offers facilities for low-level memory manipulation. Since the language makes use of both low-level features as well as the feature of high-level languages, it is considered as a middle-level language. This language was developed by Bjarne Stroustrup starting in the year 1979 and was later enhanced and renamed in 1983. Since C++ is an object oriented language, it supports the 4 principles of object oriented development including polymorphism, encapsulation, inheritance, and data hiding.

C++ is similar to C language in a lot of ways and is in fact the superset of C. This means that any program of C language is a program of C++ programming language. The language has many technical details, but the key to learning this language for you is not to get lost in these details but rather concentrate on its concepts.

Like any other language, this language too based on a philosophy and has certain elements that make it what it really is. C++ consists of three important parts, and they are given as follows:

The standard library of C++ is capable of giving a rich combination and gamut of features such as strings and manipulating sets, etc.
The standard template library or STL is capable of giving a rich set of methods manipulating data structures and other elements.
The core C++ language has the capability of giving the building elements like literals, data types, and variables.
8. C Language
C is another general-purpose and imperative programming language which was developed way back in the 70s and is similar to C++ language. This language is known to be the most widely used programming platform that offers building elements for other languages like C++, Python, Java and others. These languages borrow features either directly or indirectly from it, and some of these include control structures, overall syntax, and standard libraries. This is the reason why if you want to learn programming, it is advisable that you learn C and C++ first and then move onto the others after strengthening your foundation. Some of the features that this language supports include static type system, lexical variable scope, recursion and structured programming.

The following are some of the points which shall help you understand the overall design of C language:

C is a procedural or imperative language
The language was designed in such a way that can be easily compiled by making use of a simple compiler.
The language was designed to offer a low-level access to memory.
It was designed in a way that it should need minimum possible run-time support and encourages cross-platform programming.

TaskVest has a history of making it easier for ordinary investors to put money to work

it has a history of making it easier for ordinary investors to put money to work
a new real estate investment trust that allows anyone in the US and all over the world to easily invest in a real estate portfolio in the US.What really sets TaskVest apart is that it backs each and every deal itself. The quality hasn’t gone unnoticed. TaskVest a new way of investing in real time portfolio.

Why Public Stocks Underperform Private Investments

Imagine if you lost 50% of the value of your investments overnight? How would you feel? Undoubtedly upset, concerned, and disillusioned over the stock markets.
While most people assume this scenario is unlikely, the truth is this value slashing happens every day without you even realizing it. In fact, it happens every time you buy a stock or bond for the long-term. You are charged a huge hidden cost and don’t even know it.
Here is what’s happening
Virtually every public company starts as a private company. When the company goes public (IPO), the stock price usually increases significantly. This higher price for the exact same company is called an auction liquidity premium. The public pays a higher price for the same asset because you also gain the ability to sell the shares you just bought. The price now includes a markup for daily liquidity, which an investor pays for whether or not they use it.
In a report for NYU’s Stern School of Business entitled “Private Company Valuations”, finance professor Dr. Aswath Damodaran posits that “the illiquidity discount for a private firm is between 20-30%”, i.e. a normal investor will pay 20-30% more for the same product because he or she is buying in the public market versus the private market.
While one could debate the fairness of such a large premium, if you are a buy-and-hold investor whose intention is to invest for the long-term (as almost all investment advisors recommend), it seems not only unfair but flat-out foolish to pay 20-30% more for a “daily liquidity premium” that you don’t intend to use.
Let’s look at an example
Earlier this year, Invitation Homes (stock ticker “INVH”), a Blackstone-owned portfolio of single family rental homes, filed its initial public offering on the NYSE. The price of a share in the IPO was $20—a 215% increase from the $6.36 per share book value it had disclosed only two months prior to its IPO.
In other words, in a span of only two months, the value of Invitation Homes grew by roughly 215%. What happened to cause such astronomical growth in the value of the company?
Invitation Homes is a company that buys what they believe to be undervalued suburban homes across the U.S. and then spends money renovating those homes and renting them out. According to the company’s public offering prospectus, both revenue and operating expenses were fairly consistent over the months prior to going public. Put simply, there was really no material change in the underlying business between December 2016 and February 2017—and certainly nothing that would warrant a 215% increase in the value of the company.
So, if nothing changed, what did happen? Behold the public market price markup.
The cost investors don’t know they’re paying
The truth is that nothing material about the core Invitation Homes business changed. What did change is that the company went from being owned primarily by Blackstone and their investors in the private market to being owned largely by individual investors in the public markets.
The 215% increase in value translated to $4.3 billion in additional enterprise value being captured by the pre-existing, private owners of the company as a result of “going public”. Put another way, this 215% one-time markup is the premium paid by the public market investor for access to the same investment opportunity that the private market investor had.
Why does the public market investor end up paying such a high premium for the same thing? The conventional argument is that the public market investor is paying for access to daily liquidity. In other words, the public markets afford the ability to sell an investment at any time, which therefore warrants a lower return for the same asset via a “liquidity premium”.
Lower returns for the individual investor
Just how big of an impact does the 20-30% public market markup have on the average investor’s returns? Returning to the example of Invitation Homes, while privately-owned at $6.36 per share book value, investors earned approximately 8.75% annualized current income. At the IPO, the average investor paid $20 per share and, as a result, returns fell to 2.8% annualized current return.
private market investments versus public market investments
Industry-wide, the public versus private market divide results in the average investor paying more for shares that will earn less than those held by the private market investor—regardless of whether they are consciously making the tradeoff of lower returns for other (real or perceived) benefits.
For the first time, Taskvest creates an opportunity for individual investors to have that choice, leveling the playing field when it comes to the private markets. Online distribution combined with software-driven asset management reduces friction, lowers transaction costs, and allows for the disintermediation of unnecessary middlemen. What was previously only attainable by a private investor with the right relationships and deep pockets can now be purchased online by any investor through a financial technology platform.
Private market investing for the public investor has the potential to not only revolutionize the real estate capital markets, but the broader financial markets as well, by democratizing access to a more sophisticated investment portfolio with higher return potential.
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Why Private Markets Outperform Traditional Publicly-Traded Stocks and Bonds

Abstract
This paper will examine the efficiency divide between public and private markets, and explore how inefficiency in the private markets creates opportunities to earn alpha, or above-market returns. We argue that traditional public investments generally trade at higher prices than private market investments as a result of numerous factors, including greater liquidity, fewer opportunities for arbitrage, information transparency, lower transaction costs, and scale of competition.
Various studies on the magnitude of this spread indicate a private market price discount in the range of 20% to 65%. For our purposes, we have decided to focus on the most conservative estimate, which is expounded by NYU professor Aswath Damodaran, and suggests an illiquidity discount for private firms in the range of 20-30%.¹
Concomitantly, a wealth of scholarly literature and empirical evidence suggests that, due to inefficiency-induced price discounts, “excess returns are fair game” in private markets.² This has profound implications for the returns of retail investors with traditional portfolios, and, in fact, is generally reflected in the standard institutional allocation to alternative investments.
Public vs. Private Market Efficiency: An Overview
Eugene Fama, the Nobel Prize-winning creator of the efficient market hypothesis, defines “an ‘efficient’ market as one in which there are large numbers of rational profit-maximizers actively competing, with each trying to predict the future market values of individual securities, and where important current information is almost freely available to all participants.”³ Efficient market theories also assume markets are frictionless – no transaction costs – and that “competition will cause the full effects of new information on intrinsic value to be reflected ‘instantaneously’ in actual prices.”⁴
In economics, the efficient market hypothesis is used to argue that it is impossible to consistently “beat the market” for publicly-traded securities on a risk-adjusted basis, since public stock and bond prices fully reflect all available information. As a result, stocks and bonds always trade at their fair value, making it impossible for investors to either purchase undervalued stocks or sell stocks for inflated prices. As such, it should be impossible to outperform the overall stock market through expert stock selection or market timing. Put simply, when an asset is priced in the highly efficient public markets, it is theoretically priced perfectly.
By contrast, private markets are notoriously inefficient, and hence offer investors opportunities to “beat the market”. To cite an example, the market for commercial real estate (CRE) is generally recognized as being highly inefficient, due to its relative illiquidity, unpredictable pricing, high transaction costs, geographical segmentation, and informational opacity. To quote a study conducted for the Real Estate Research Institute, “in relatively illiquid, segmented, and informationally inefficient CRE markets, negotiated transaction prices may vary from the ‘true’ (but unobservable) market value of the property.”⁵ In other words, while the efficient market hypothesis predicts that public securities will always trade at their fair market value, private market assets such as commercial buildings may trade for well below their true market values, hence providing an opportunity for investors to generate above-market returns.
Empirical Evidence: Public vs. Private Returns
There is a wealth of empirical evidence highlighting the pronounced return differential between public and private securities. Cambridge Associates’ 2016 US Private Equity Index highlights this spread, with the index commanding an annualized 25-year yield more than 500 basis points above that for the S&P 500 – 13.22% vs. 8.19% returns per annum, respectively.⁶
The California Public Employees’ Retirement System (Calpers) further illustrates the return premia commanded by private securities. Calpers’ 20-year private-equity returns were 12.3% over 20 years, versus 8.2% for public equity – an approximate 400 basis point differential.⁷

Dyck and Pomorski find that, among institutions, a standard deviation increase in private equity holdings corresponds with 4% greater annual returns, while a two standard deviation increase corresponds with 7.4% greater annual returns.⁸
Large institutional funds have for years recognized the outperformance of private assets by including private equity and commercial real estate in their standard portfolio allocations. For instance, the Yale endowment, which has added nearly $27 billion in value and generated an approximate 13% annual return over the past 30 years⁹ has allocated nearly 75% of its target portfolio to alternative investments, including roughly 30% to private investments like real estate and venture capital.¹⁰
Case Study: Invitation Homes
Private companies that elect to go public through Initial Public Offerings (IPOs) provide further evidence of the substantial pricing premia commanded by public securities. These premia are sufficiently large, in fact, that entrepreneurs are willing to voluntarily subject their companies to much higher regulatory burdens, and pay an industry standard underwriting fee of 5-7%, per PwC¹¹, to unlock them. As rational, profit-maximizing agents, entrepreneurs seek to take their companies public largely in order to fetch higher valuations than they would command in private markets.
For a specific example of this markup, consider Blackstone’s February 2017 listing of Invitation Homes (NYSE: INVH), a portfolio of single family rental homes acquired from 2012-15:

At initial public offering (IPO) the markets priced the Invitation Homes rental housing portfolio at $14 billion enterprise value – $6.3 billion in equity/market capitalization, which equated to $20 per share – a significant premium above the $6.36 per share value it achieved in the private market. In other words, by taking Invitation Homes public, Blackstone was able to mark up their book value by 215% – or, conversely, the public market investor was paying 215% more for a share of the company than the private market investor.
Invitation Homes Balance Sheet (in millions)
Dec 31, 2016 Feb 1, 2017
Equity $2,000 $6,300
Debt $7,700 $7,700
Total Enterprise Value $9,700 $14,000
Blackstone illustrates the valuation benefits of capitalizing on the price differential between the private and public markets. With approximately $170 million of free cash flow (net income after debt service) as of 2016, the public markets priced Invitation Homes at a substantial premium above their private market basis.
To further illustrate the price gains and post-IPO investor yield compression generated by taking private companies public, consider that several of Invitation Homes’ peers also priced at a significant premium over book at their respective IPOs:
Private Market Balance Sheet vs. Public Market Pricing at IPO
Invitation Homes (INVH) American Homes 4 Rent (AMH) Colony Starwood Homes (SFR)
Total Equity on Balance Sheet (financials pre-IPO) $2,000,000 $2,650,000 $1,080,000
Public Market Capitalization (on opening day) $6,300,000 $3,700,000 $3,100,000
Public Market Pricing Premia 215% 39.6% 187%
Source: SEC / EDGAR; Google Finance.
The IPOs of Invitation Homes and its cohorts exemplify the pronounced pricing differential between public and private markets. By going public, companies are able to significantly boost their valuations over book – a benefit to entrepreneurs, but one that comes with profound implications for post-IPO, public market investors.
Investor Implications
While the valuation benefit to entrepreneurs of taking private companies public may be patent, so too is the downside for post-IPO investors in public companies, as higher valuations translate into lower yields. Moreover, it is virtually impossible for public market investors to avoid paying this premium, irrespective of whether they would be willing to accept reduced liquidity in exchange for higher returns.

The impact of the private vs. public yield spread on individual investors can be elucidated by examining the differential returns between institutions with high allocations to private investments and those with low allocations to private investments. A study by Cambridge Associates found that, for the fiscal year ended June 30, 2015, the median annual return for institutions with more than 15% of AUM in private investments was 370 basis points above that realized by institutions with less than 5% of AUM in private investments.¹²

Moreover, these results are robust over time. Over the trailing 20-year period ending June 30, 2015, institutions with private investment allocations above 15% outperformed their counterparts with allocations below 5% by a cumulative margin of 180 basis points annually.¹³ The report also finds that, from June 30, 2005 to June 30, 2015, the average allocation to private investments in the top-performing quartile of institutions was 24.1%, while the average allocation in the bottom quartile was only 6%.¹⁴

As the report concludes, “The evidence strongly supports the view that an allocation of 15% or more of a portfolio to private [investments] leads to higher returns and should be taken seriously by all investors.”¹⁵ We believe this statement is well founded. Extrapolating the median 20-year difference in annual returns observed by Cambridge Associates on an investment portfolio of $50,000, with $5,000 contributed annually over a 45-year period (assuming quarterly interest compounding) implies a portfolio value spread of approximately $4 million at the end of the period.
Examining the Underlying Drivers of Inefficiency Opportunities in Private Markets
A common misconception is to attribute the well-observed private vs. public return differential exclusively to private-market illiquidity. In fact, this misunderstanding oversimplifies the concept of liquidity and overlooks the manifold drivers that determine whether or not a market acts in accordance with the efficient market hypothesis.
We argue that, in private markets, arbitrage opportunities, opacity, friction, and fragmentation take on distinct properties from illiquidity. As a heuristic, consider H2O at different energy states – its physical properties manifest as fundamentally different materials: vapor, water, or ice. Analogously, the general concept of liquidity is imprecise to describe the numerous factors generating inefficiency in private markets.
We aim to demonstrate in the ensuing sections that public markets behave in accordance with the efficient market hypothesis by virtue of the fact that they offer investors greater liquidity, market-dictated pricing, information transparency, low transaction costs, and access to large pools of potential buyers and sellers. By contrast, we contend that private market inefficiencies – and corresponding return premia – are driven by their relative illiquidity, unpredictable pricing, opacity, high transaction costs, and limited numbers of prospective buyers and sellers.
Public Markets Private Markets
Liquid: Easy to buy and sell investments Illiquid: Difficult to buy and sell investments
No Arbitrage: Pricing is set by the market, with limited opportunities for arbitrage Arbitrage: Unpredictable pricing creates opportunities for arbitrage
Transparent: Information transparency Opaque: Information asymmetry and opacity
Frictionless: Low or non-existent transaction costs Frictional: High transaction costs
Scaled: Many prospective buyers and sellers Fragmented: Few prospective buyers and sellers
Liquidity
At its root, market efficiency assumes that investors have access to organized markets in which they may conduct high-volume and costless trades en masse. Once the frame of reference departs from the trade of public securities and applies to buying or selling whole companies or buildings, however, it becomes apparent that such access may be severely lacking, and, hence, that one of the central assumptions of the efficient market hypothesis has been violated.
That said, it is important to bear in mind the distinction between private assets and privately-traded securities. For instance, private real estate assets that trade in single-building sales are highly illiquid, whereas publicly-traded REIT shares that represent investments in pools of commercial real estate assets may be highly liquid. Krainer and LeRoy explicate this point as follows:
Many assets are traded both on illiquid and liquid markets. For example, real estate assets are illiquid when traded retail, liquid when traded as shares of real estate investment trusts. The assets of Ford Motor Company, consisting of auto factories, are very illiquid, but Ford stock is liquid. The principal asset of Microsoft is Bill Gates’ marketing ability, which cannot be directly traded at all due to the constitutional prohibition of slavery, but again, Microsoft is very liquid […] Thus assets themselves cannot be characterized as to liquidity since they can be traded either directly on illiquid markets or indirectly on liquid markets, as securities, or both.
-John Krainer and Stephen F. LeRoy, Equilibrium Valuation of Illiquid Assets¹⁶
As described by Krainer and LeRoy, “liquidity” usually connotes the bid-ask spread in traded securities.¹⁷ However, in private markets, illiquidity has other components not present in the “market microstructure literature of finance,” namely:
Illiquid assets are heterogeneous. Unlike shares of stock, buildings and companies are not fungible, or perfectly interchangeable.
Illiquid purchases imply a certain degree of irrevocability. Any attempt to reverse or quickly dispose of a recent acquisition results in high transactional entropy, and may risk transmitting market signals of seller distress, reducing the seller’s bargaining power.
Assets are indivisible. Real physical properties and corporations are not easily divisible. This results in the need for buyers to operate at scale to achieve optimal financing, negotiating, and operating leverage.
Pricing is highly reflexive. Private market pricing is exceptionally subjective. One buyer can achieve higher utility and economic rents based on leveraging its particular operational advantages.
In confluence, these features generate an appreciable illiquidity discount for private assets and, inversely, a liquidity premium for public assets. Benveniste, Capozza, and Seguin find that securitizing claims to and offering exchange-traded equity on real estate assets increases their value by 12 – 22%.¹⁸ In analyzing cross-sectional dispersions in liquidity, the study also finds that more liquid securitized assets experience even greater value gains. The authors’ model, which uses annual dollar trading volume as a proxy for liquidity, predicts that a one standard deviation in turnover corresponds with an 18% increase in equity valuation.¹⁹
An analysis by Aswath Damodaran, Professor of Finance at NYU Stern, definitively states that “the illiquidity discount for a private firm is between 20-30% and does not vary across private firms.”²⁰ In effect, the public markets charge investors a 20-30% liquidity premium when they purchase shares. Importantly, this premium is charged irrespective of whether the investor is a long-term holder that does not need daily liquidity. In other words, an investor may be paying a substantial price premium for a benefit they do not require or demand.
The impact of illiquidity-generated private market price discounts corresponds with meaningful return premia, as investors demand higher yields in exchange for incurring illiquidity risks. In Liquidity Pricing of Illiquid Assets, Gianluca Marcato finds that the relative illiquidity of real estate corresponds with an average annual ex ante premium of 3.0% in the UK.²¹ In other words, investors expect higher returns based on illiquidity features of the real estate market such as relatively long TOM (time on market) and the uncertain nature and timing of asset dispositions.²²
Arbitrage
The relatively unpredictable pricing that defines private markets creates opportunities for investors to leverage advantages like economies of scale, expertise, and other asset holdings. While in public markets all pertinent information is theoretically capitalized into the market price and buyers hence act as “price takers”, in private markets, buyers routinely leverage their market power to secure better pricing, acting as “price makers.”
Paraphrasing Krainer and LeRoy, private market participants justifiably expect to affect the price and performance of assets acquired.²³ In contrast to public markets, price equilibria in private markets are not Pareto optimal. Both the buyer and the seller can gain positive net present value in a transaction. In fact, prices of the underlying assets reflect the imperfect pricing balance and directly imply that excess returns are fair game.
The commercial real estate market can offer many examples of private-market investors leveraging unique advantages to earn outsized returns. Ling, Naranjo, and Petrova’s study finds that geographic proximity is an important predictor of CRE returns, with distant buyers paying a significant price premium ranging from 4.4 percent for multifamily properties to 14.7 percent for office properties.²⁴
While investors in the publicly-traded shares of large-cap multinational conglomerates are unlikely to see their returns bolstered or depressed by virtue of their neighborhood of residence, private market investors may feasibly benefit from a more intimate knowledge of their local market, as exemplified by the aforementioned study.
Of course, geographical proximity is just one example of an advantage private market investors may leverage to boost returns. The ability to raise capital quickly and at scale, obtain low cost financing, and aggressively negotiate legal terms provide additional examples of factors that can exert a material effect on returns. The best private actors operate at economies of scale, with deep technical knowledge, and have many opportunities to translate management competence into investment performance.
Like CRE, the world of private equity offers useful insights into the impact of operational, informational, and other idiosyncratic advantages on investment returns. A Cambridge Associates study found that specialized or “sector-focused” private equity managers – defined as those who invested more than 70% of managed capital in one of four defined sectors over a decade – generated significantly greater returns than “generalist” managers from 2001 – 2010.²⁵
The study found that sector-focused funds produced a 2.2x multiple of invested capital (MOIC) and 23.2% gross internal rate of return (IRR), compared with the 1.9x MOIC and 17.5% gross IRR produced by generalist funds.²⁶ Moreover, sector-specific private equity funds were found to be better at averting portfolio losses. According to the report, this sizable return (and loss) spread is attributable to a host of competitive advantages. To quote the study:
The deep domain knowledge, industry contacts, and sheer number of repetitions in a sector leads to higher quality and increased volume of deal flow and better pattern recognition for sector specialists. The focused and dedicated resources that sector specialists can deploy within a sector allow them to be closer to industry participants, trends, and themes that can lead to more attractive and differentiated investment opportunities that generalists firms may overlook.²⁷
Importantly, this ability to leverage industry expertise is replicable across a host of private markets. Returning once again to private real estate markets, the sale of high-vacancy properties – typically purchased by buyers with deep industry expertise who believe they can boost occupancies and cash flow through superior property management, branding, and physical improvements (e.g. renovations) – have generated robust returns this cycle.
Real estate data provider CoStar examined 44 million square feet of “turnaround” office buildings – defined as properties at least 30% vacant when acquired that were subsequently sold after vacancies were significantly reduced – generated average value gains of 33%.²⁸ While opportunities to turn industry expertise or managerial competence into above-market returns are virtually absent in highly-efficient public markets, inefficient private markets demonstrably offer opportunities for arbitrage – and alpha – among advantageously equipped investors.
Transparency
Related to the concept of arbitrage is market transparency, as a lack thereof enables investors to leverage an advantage of particular import: information. Generally speaking, better informed investors should be able to leverage their possession of superior information in order to generate outsized investment returns. However, the transparency of public markets limits the extent to which informational advantages in these markets can be translated into alpha.
To be sure, public markets are not perfectly transparent, and there is evidence supporting the ability of better informed investors to earn abnormal returns in public markets. Choi and Yan compiled data on Shanghai Stock Exchange investments from 1996 to 2007 and found that “after controlling for other known determinants of stock returns, the average return of stocks in the top quintile of predicted information asymmetry is 10.8% per year higher than that of stocks in the lowest quintile of predicted information asymmetry,” as illustrated below:²⁹

Analogously, a Finnish study by Berkman, Koch, and Westerholm, which used trading activity in the accounts of children aged 10 and under as a proxy for the priviness of their parents, found that investors with an ostensible information advantage earned superior returns over a 15-year timespan.³⁰ The study finds that “underaged accountholders exhibit superior stock-picking skills on both the buy side and the sell side over the days immediately following trades […], significantly outperform[ing] older investors by an average of 9 basis points based on all trades made one day earlier.”³¹
Turning to the U.S., a study by Coval and Moscowitz found that mutual fund managers “earn substantial abnormal returns in nearby investments,” suggesting that “investors trade local securities at an informational advantage.”³²
Theoretically, the average investor in public securities is trading at a significant knowledge disadvantage to professional investors and those with more intimate knowledge of particular companies, and should hence demand a return premium. Nonetheless, there is scant evidence that information asymmetry manifests in return premia for less-informed investors in public markets.
In fact, Coval and Moscowitz highlight in their study the fact that abnormal returns earned by well-informed mutual fund managers could not easily be replicated by distant (i.e. informationally disadvantaged) investors.³³ They state, “If uninformed investors were, indeed, able to mimic the positions of locally informed mutual fund managers, this would appear to be a violation of semistrong form market efficiency.”³⁴
Put simply, in public markets, information asymmetry may be rampant but rarely translates into actionable opportunities to earn above-market returns for lay investors. As Lambert, Leuz, and Verrecchia write:
With perfect competition information asymmetry makes no difference. Instead, a firm’s cost of capital is governed solely by the average precision of investors’ information. With imperfect competition, however, information asymmetry affects the cost of capital even after controlling for investors’ average precision. In other words, the capital market’s degree of competition plays a critical role for the relation between information asymmetry and the cost of capital.³⁵
Again, real estate markets can offer a window of insight into the mechanisms by which information asymmetries may be leveraged to produce abnormal returns in inefficient, imperfectly competitive private markets. Information provided by sellers in real estate transactions can be suspect, and material provided by brokers may be grossly exaggerated. Private market buyers must perform their own in-depth due diligence, based upon information that is not made available to other market participants due both to its high production costs and precisely to preserve the buyer’s information asymmetry.
Consequently, players with superior knowledge of the market and access to the resources needed to perform appropriate due diligence are able to generate abnormal returns. Evidence of this is offered by Ling, Naranjo, and Petrova, who find that “use of a broker significantly increases the acquisition prices of buyers and decreases the disposition prices of sellers,”³⁶ suggesting that better-informed market participants who do not need to rely on intermediaries are in a position to generate superior returns.
Friction
When investment acquisitions and dispositions entail costly search and transaction costs, investors are typically compensated for this lack of liquidity in the form of a return premium. According to Joseph Williams in Pricing Real Assets with Costly Search (1995), there is a positive liquidity premium in private markets because a matched owner must compensate for the time spent searching for a match and the transaction costs incurred conditional on a match.³⁷
Meanwhile, in Valuation in Over-the-Counter Markets, Duffie, Garleanu, and Pedersen (2005), show that the direction and magnitude of this premium is contingent on the quantity of prospective buyers and the size of search costs, ceteris paribus.³⁸ In other words, small buyer pools and significant search costs correspond with larger price discounts.
The graph provided by Duffie et al shows how the proportional price reduction relative to the perfect-market price decreases as a function of the search intensity λ.³⁹ The solid line plots this illiquidity discount when investors are risk neutral and may face holding costs, where the holding costs are calibrated to match to utility costs in a model with risk-averse investors and time-varying hedging demands, as illustrated by the dashed line.⁴⁰

To help illustrate this point, for many years on the NYSE, the price was set where the greatest number of trades between buyers and sellers would clear (i.e. a Walrasian price was achieved and the illiquidity discount would vanish). Contrastingly, search intensity is poor and highly frictional in private markets. For instance, an institutional commercial property sales contract is bilateral – between a single buyer and seller. Moreover, such contracts are latent with substantial uncertainty and may take significant time to close.
According to CoStar, as of January 2015, commercial properties sat on the market for an average of 390 days before finding a buyer.⁴¹ The switching cost and bargaining power of market participants bring the search function described above close to zero intensity. Moreover, in practice, participants are neither perfectly risk neutral nor risk averse. Hence, it is fair to assume based on Duffie et al’s model that pricing discounts would range between 25% to 65%, depending on the risk sensitivity of the agent.
In his study of Frictional Finance, Lasse H. Pedersen, NYU finance professor and principal of AQR Capital Management, proposes that “frictions are central to the dynamics of financial markets, stronger than any other influence on the market, including systemic risk.”⁴² He provides a starting point with his liquidity-adjusted capital asset pricing model (CAPM):

He argues that different costs associated with illiquidity drive the market to demand higher returns for investments.⁴³

Pedersen shows that pricing dynamics are clearly determined “not by intrinsic values, but rather liquidity premiums, as a result of market inefficiencies” such as slow moving capital.⁴⁴ Frictional finance also implies large cross-sectional and time-series variation in risk premia:⁴⁵

To sum, numerous studies demonstrate that market frictions such as search costs can meaningfully impact investment prices and concomitant returns in private markets.
Scale
Another core driver of private market inefficiency and return premia is fragmentation. Typically, there are far fewer buyers competing in private market transactions than in public transactions, even when compared with an extremely thinly-traded public market.
Investor Business Daily considers a stock to be thinly traded if fewer than 400,000 shares trade per day, based on a 50-day average.⁴⁶ According to the World Bank, which cites data from the World Federation of Exchanges, the total value of shares traded in 2016 exceeded $42 trillion domestically, and $77.5 trillion globally (in US dollars).⁴⁷ By contrast, domestic commercial real estate transactions in core property sectors totaled roughly $500 billion in 2016, according to data provided by CoStar to the National Real Estate Investor.⁴⁸ This substantial divergence in scale creates a fundamental price differential between markets.
To observe the implications of a market with few buyers and longer times to transact, consider an example provided by Duffie et al in Valuation in Over-the-Counter Markets, which models the pricing discount on corporate bonds traded over-the-counter (OTC). The operative assumptions of the study are: (1) an average 49% annual turnover in corporate bonds, based on an average 2-year hold; (2) an owner agent expects to be in contact with 5 possible purchasing agents per day (or 1,250 per year in the OTC market); and (3) the average time needed to sell is 1.8 days – 250 × (2λμhn) − 1 = 1.8 days. In the study, Duffie et al find that OTC corporate bonds fetch an 8.1% pricing discount.⁴⁹
To show a rough contrast with commercial property transactions, we assume (1) an average annual turnover of 16%, based on a standard hold period of 6.31 years, as reported by Ciochetti and Fischer in Characteristics of Commercial Real Estate Holding Period Returns (2002);⁵⁰ (2) that a property owner could safely assume to be in contact with 5 to 20 agents per year, based on our experience as a real estate operator; and (3) an average time of 390 days needed to sell a commercial property, based on CoStar data.⁵¹
Corporate Bonds OTC Private Market Commercial Real Estate
Hold Period An average 49% annual turnover in corporate bonds, based on an average 2-year hold An average annual turnover of 16%, based on a standard hold period of 6.31 years, as reported by Ciochetti and Fischer in the Characteristics of Commercial Real Estate Holding Period Returns (2002)
Scale of Buyer-Seller Interactions An owner agent expects to be in contact with 5 possible purchasing agents per day (or 1,250 per year in the OTC market) A property owner could safely assume to be in contact with 5 to 10 agents a year, and rarely more than 20
Time to Close (Market Liquidity) Concluding an average time needed to sell is 1.8 days – 250 × (2λμhn) – 1 = 1.8 days An average time needed to sell a commercial property is 390 days according to CoStar (2015)
Based on Duffie et al’s model, applying the above inputs, longer hold periods, a significantly lower volume of interactions between buyers and sellers, and dilated sales periods imply a pricing discount in excess of 30% to 50% for private commercial real estate.⁵²
Conclusion
While investors generally cannot beat the market through traditional publicly-traded stocks and bonds, both empirical evidence and economic theory support that above-market returns are achievable through exposure to private investments. Private markets are inefficient – a product of their relative illiquidity, abundance of arbitrage opportunities, opacity, search costs, and fragmentation. In turn, private markets generate a typical pricing discount of at least 20-30%. We argue that by capitalizing on this spread – as institutional asset allocators have done for some time, and with remarkable success – investors can realize meaningfully superior returns on their portfolios.

Safety Net Funds: Why Traditional Advice Is Wrong

KEY TAKEAWAYS

Don’t keep your safety net fund in cash savings accounts. Odds are you’ll lose money due to inflation, and lose out on potential growth of your savings.A smarter way is to invest 130 percent of your safety net in a moderate-risk portfolio. This ensures you keep your safety net fund available — and growing.
Conventional wisdom says that safety net funds should be held in a savings account or a similarly risk-free asset. But is this really the wisest way to manage your rainy day fund? Our analysis finds that you can do far better by investing your safety net fund in a diversified portfolio.

First, let’s get one myth out of the way: Cash savings accounts are not risk free. Why? Because after accounting for inflation there is about a one in three chance you won’t get back the money you put in, in real terms.

Today, with nominal cash interest rates hovering far beneath 1 percent, it’s almost guaranteed that you’ll make a negative real return over the next few years. This means your safety net fund will need topping up year after year to maintain its real value. It also means that you’ll have a significant amount of wealth that is not growing, potentially for a long period of time.

Intelligent Investing Is Safe, Even for Your Safety Money
The better solution is to have a safety net fund and grow it too. For those with a fully funded safety net fund, we recommend investing in a moderate risk portfolio with allocation set between 30 percent and 50 percent stocks. Betterment’s default advice for a safety net goal suggests a 40 percent allocation.

While this flies in the face of traditional advice, our analysis below shows that it stands up to critical examination.

Let’s work through an example to explain our advice. First, everyone should consider having some kind of safety net fund based on his or her monthly expenditures. (Read our blog post about how to calculate your own safety net target amount.) If you have not fully funded your safety net yet, we recommend saving regularly to get there.

For a worker earning around $110,000 in annual salary, a safety net target might be $18,000 (assuming minimum expenses of $4,500 per month for four months). This saver has two options: put this money into a savings account or invest it. We think investing is the smarter choice. However, to be smart investors we want to also protect ourselves against potential losses. This is why we recommend adding a buffer of 30 percent¹ to your original target amount. For example, to maintain an $18,000 safety net we recommend starting with $23,377.

On the chart below we’ve plotted the actual returns for every five-year period since 1955 for a $23,377 safety net fund with a 40 percent stock allocation. As you can see, the returns — like those of any investment — can vary on both the upside and downside. However, over any five-year period it is rare to find the value of the safety net fund dip below $18,000. On the other hand, for the saver who keeps a safety net in cash, inflation is likely to chip away at that amount in real terms.

Value of Safety Net Fund Since Original Investment
Monthly Safety Net Fund account value over every 5-year period since Jan 1, 1955

safety-net-historical-5-year-runs-01

SOURCES: Betterment analysis of S&P500: Yahoo Finance; Federal Reserve Economic Database; Bureau of Labor Statistics

Reinvesting Gains in Your Safety Net Fund
The benefit of investing a slightly larger amount than you need is the opportunity to earn returns. If the original investment of $23,377 grows at around 5 percent per year (an approximate long-term annual return for a Betterment account with a 40 percent stock allocation), it will be getting bigger than necessary on a regular basis. This is a good problem to have.

To prevent your safety net from getting too big, we advise transferring the excess to another goal in order to bring it back down to the correct level every time it gets to be 20 percent bigger than it needs to be. That excess growth not only makes up for the original buffer you invested, but it can now be transferred to help along other goals like IRAs, retirement, or a vacation around the world.

In fact, the best scenario is that you will never need your safety net fund at all. Even the poorest returns on investing will still handily beat cash over 50 years. In other words, cash is a very poor long-term investing — or safety net fund — strategy.

We do not have a crystal ball and do not know exactly what markets will do in the future. But what we can see in recent history is that the downside of taking some risk is not terrible — but the upside is very powerful.

¹ Increasing your target amount by 30 percent will allow the investment to absorb a 23 percent decline while preserving the target amount. We are using 23 percent because it represents the greatest peak-to-trough percentage drop a Betterment 40 percent stock portfolio would have experienced since 2004 (the drop took place between July 2008 and March 2009). Prior to 2004, insufficient data is available to test the Betterment portfolio’s performance with confidence. However, to demonstrate a longer historical view, the graph above uses performance of a portfolio consisting of 40 percent S&P500/60 percent 5-year Treasury Bills, going back to 1955. There is no guarantee that a future drop would not be steeper, but we feel it is useful to demonstrate the impact of historically exceptional volatility on a buffered safety net fund. Please see our full disclosure of our methodology for model historical returns.