"Web 3.0" is a trendy buzzword with a vague definition. Everyone agrees it has to do with a blockchain-based internet evolution, but what is it?

Yet, the meaning and prospects for Web3 have become hot topics in crypto communities. Big corporations use the term to gain a foothold in the space while avoiding the negative connotations of “crypto.”

But it can't be evaluated without a definition.

Among those criticizing Web3's vagueness is Cobie:

“Even the crypto community is split on whether Bitcoin is Web3,” he adds.

The phrase was coined by an early crypto thinker, and the community has had years to figure out what it means. Many ideologies and commercial realities have driven reverse engineering.

Web3 is becoming clearer as a concept. It contains ideas. It was probably coined by Ethereum co-founder Gavin Wood in 2014. His definition of Web3 included “trustless transactions” as part of its tech stack. Wood founded the Web3 Foundation and the Polkadot network, a Web3 alternative future.

The 2013 Ethereum white paper had previously allowed devotees to imagine a DAO, for example.

Web3 now has concepts like decentralized autonomous organizations, sovereign digital identity, censorship-free data storage, and data divided by multiple servers. They intertwine discussions about the “Web3” movement and its viability.

These ideas are linked by Cobie's initial Web3 definition. A key component of Web3 should be “ownership of value” for one's own content and data.

Noting that “late-stage capitalism greedcorps that make you buy a fractionalized micropayment NFT on Cardano to operate your electric toothbrush” may build the new web, he notes that “crypto founders are too rich to care anymore.”

Very Important

Many critics of Web3 claim it isn't practical or achievable. Web3 critics like Moxie Marlinspike (creator of sslstrip and Signal/TextSecure) can never see people running their own servers. Early in January, he argued that protocols are more difficult to create than platforms.

While this is true, some projects, like the file storage protocol IPFS, allow users to choose which jurisdictions their data is shared between.

But full decentralization is a difficult problem. Suhaza, replying to Moxie, said:

So, here are the questions: Web3: Is it a go? Is it truly decentralized?

Web3 history is shaped by Web2 failure.

This is the story of how the Internet was turned upside down...

Then came the vision. Everyone can create content for free. Decentralized open-source believers like Tim Berners-Lee popularized it.

Real-world data trade-offs for content creation and pricing.

A giant Wikipedia page married to a giant Craig's List. No ads, no logins, and a private web carve-up. For free usage, you give up your privacy and data to the algorithmic targeted advertising of Web 2.

Our data is centralized and savaged by giant corporations. Data localization rules and geopolitical walls like China's Great Firewall further fragment the internet.

The decentralized Web3 reflects Berners-original Lee's vision: "No permission is required from a central authority to post anything... there is no central controlling node and thus no single point of failure." Now he runs Solid, a Web3 data storage startup.

So Web3 starts with decentralized servers and data privacy.

Web3 begins with decentralized storage.

Data decentralization is a key feature of the Web3 tech stack. Web2 has closed databases. Large corporations like Facebook, Google, and others go to great lengths to collect, control, and monetize data. We want to change it.

Amazon, Google, Microsoft, Alibaba, and Huawei, according to Gartner, currently control 80% of the global cloud infrastructure market. Web3 wants to change that.

Decentralization enlarges power structures by giving participants a stake in the network. Users own data on open encrypted networks in Web3. This area has many projects.

Apps like Filecoin and IPFS have led the way. Data is replicated across multiple nodes in Web3 storage providers like Filecoin.

But the new tech stack and ideology raise many questions.

Giving users control over their data

According to Ryan Kris, COO of Verida, his “Web3 vision” is “empowering people to control their own data.”

Verida targets SDKs that address issues in the Web3 stack: identity, messaging, personal storage, and data interoperability.

A big app suite? “Yes, but it's a frontier technology,” he says. They are currently building a credentialing system for decentralized health in Bermuda.

By empowering individuals, how will Web3 create a fairer internet? Kris, who has worked in telecoms, finance, cyber security, and blockchain consulting for decades, admits it is difficult:

“The viability of Web3 raises some good business questions,” he adds. “How can users regain control over centralized personal data? How are startups motivated to build products and tools that support this transition? How are existing Web2 companies encouraged to pivot to a Web3 business model to compete with market leaders?

Kris adds that new technologies have regulatory and practical issues:

Each project has varying degrees of decentralization. The diehards say DApps that use centralized storage are no longer “Web3” companies. But fully decentralized technology is hard to build.

Web2.5?

Some argue that we're actually building Web2.5 businesses, which are crypto-native but not fully decentralized. This is vital. For example, the NFT may be on a blockchain, but it is linked to centralized data repositories like OpenSea. A server failure could result in data loss.

However, according to Apollo Capital crypto analyst David Angliss, OpenSea is “not exactly community-led”. Also in 2021, much to the chagrin of crypto enthusiasts, OpenSea tried and failed to list on the Nasdaq.

This is where Web2.5 is defined.

“Web3 isn't a crypto segment. “Anything that uses a blockchain for censorship resistance is Web3,” Angliss tells us.

“Web3 gives users control over their data and identity. This is not possible in Web2.”

“Web2 is like feudalism, with walled-off ecosystems ruled by a few. For example, an honest user owned the Instagram account “Meta,” which Facebook rebranded and then had to make up a reason to suspend. Not anymore with Web3. If I buy ‘Ethereum.ens,' Ethereum cannot take it away from me.”

Angliss uses OpenSea as a Web2.5 business example. Too decentralized, i.e. censorship resistant, can be unprofitable for a large company like OpenSea. For example, OpenSea “enables NFT trading”. But it also stopped the sale of stolen Bored Apes.”

Web3 (or Web2.5, depending on the context) has been described as a new way to privatize internet.

“Being in the crypto ecosystem doesn't make it Web3,” Angliss says. The biggest risk is centralized closed ecosystems rather than a growing Web3.

LooksRare and OpenDAO are two community-led platforms that are more decentralized than OpenSea. LooksRare has even been “vampire attacking” OpenSea, indicating a Web3 competitor to the Web2.5 NFT king could find favor.

The addition of a token gives these new NFT platforms more options for building customer loyalty. For example, OpenSea charges a fee that goes nowhere. Stakeholders of LOOKS tokens earn 100% of the trading fees charged by LooksRare on every basic sale.

Maybe Web3's time has come.

So whose data is it?

Continuing criticisms of Web3 platforms' decentralization may indicate we're too early. Users want to own and store their in-game assets and NFTs on decentralized platforms like the Metaverse and play-to-earn games. Start-ups like Arweave, Sia, and Aleph.im  propose an alternative.

To be truly decentralized, Web3 requires new off-chain models that sidestep cloud computing and Web2.5.

“Arweave and Sia emerged as formidable competitors this year,” says the Messari Report. They seek to reduce the risk of an NFT being lost due to a data breach on a centralized server.

Aleph.im, another Web3 cloud competitor, seeks to replace cloud computing with a service network. It is a decentralized computing network that supports multiple blockchains by retrieving and encrypting data.

“The Aleph.im network provides a truly decentralized alternative where it is most needed: storage and computing,” says Johnathan Schemoul, founder of Aleph.im. For reasons of consensus and security, blockchains are not designed for large storage or high-performance computing.

As a result, large data sets are frequently stored off-chain, increasing the risk for centralized databases like OpenSea

Aleph.im enables users to own digital assets using both blockchains and off-chain decentralized cloud technologies.

Aleph.im raised $10 million in mid-January 2022, and Ubisoft uses its network for NFT storage. This is the first time a big-budget gaming studio has given users this much control.

It also suggests Web3 could work as a B2B model, even if consumers aren't concerned about “decentralization.” Starting with gaming is common.

Can Tokenomics help Web3 adoption?

Web3 consumer adoption is another story. The average user may not be interested in all this decentralization talk. Still, how much do people value privacy over convenience? Can tokenomics solve the privacy vs. convenience dilemma?

Holon Global Investments' Jonathan Hooker tells us that human internet behavior will change. “Do you own Bitcoin?” he asks in his Web3 explanation. How does it feel to own and control your own sovereign wealth? Then:

“The business model must find what that person values,” he says. Putting their own health records on centralized systems they don't control?

“How vital are those medical records to that person at a critical time anywhere in the world? Filecoin and IPFS can help.”

Web3 adoption depends on NFT storage competition. A free off-chain storage of NFT metadata and assets was launched by Filecoin in April 2021.

Denationalization and blockchain technology have significant implications for data ownership and compensation for lending, staking, and using data. 

Tokenomics can change human behavior, but many people simply sign into Web2 apps using a Facebook API without hesitation. Our data is already owned by Google, Baidu, Tencent, and Facebook (and its parent company Meta). Is it too late to recover?

Maybe. “Data is like fruit, it starts out fresh but ages,” he says. "Big Tech's data on us will expire."

Web3 founder Kris agrees with Hooker that “value for data is the issue, not privacy.” People accept losing their data privacy, so tokenize it. People readily give up data, so why not pay for it?

"Personalized data offering is valuable in personalization. “I will sell my social media data but not my health data.”

Purists and mass consumer adoption struggle with key management.

Others question data tokenomics' optimism. While acknowledging its potential, Box founder Aaron Levie questioned the viability of Web3 models in a Tweet thread:

“Why? Because data almost always works in an app. A product and APIs that moved quickly to build value and trust over time.”

Levie contends that tokenomics may complicate matters. In addition to community governance and tokenomics, Web3 ideals likely add a new negotiation vector.

“These are hard problems about human coordination, not software or blockchains,”. Using a Facebook API is simple. The business model and user interface are crucial.

For example, the crypto faithful have a common misconception about logging into Web3. It goes like this: Web 1 had usernames and passwords. Web 2 uses Google, Facebook, or Twitter APIs, while Web 3 uses your wallet. Pay with Ethereum on MetaMask, for example.

But Levie is correct. Blockchain key management is stressed in this meme. Even seasoned crypto enthusiasts have heart attacks, let alone newbies.

Web3 requires a better user experience, according to Kris, the company's founder. “How does a user recover keys?”

And at this point, no solution is likely to be completely decentralized. So Web3 key management can be improved. ”The moment someone loses control of their keys, Web3 ceases to exist.”

That leaves a major issue for Web3 purists. Put this one in the too-hard basket.

Is 2022 the Year of Web3?

Web3 must first solve a number of issues before it can be mainstreamed. It must be better and cheaper than Web2.5, or have other significant advantages.

Web3 aims for scalability without sacrificing decentralization protocols. But decentralization is difficult and centralized services are more convenient.

Ethereum co-founder Vitalik Buterin himself stated recently"

This is why (centralized) Binance to Binance transactions trump Ethereum payments in some places because they don't have to be verified 12 times."

“I do think a lot of people care about decentralization, but they're not going to take decentralization if decentralization costs $8 per transaction,” he continued.

“Blockchains need to be affordable for people to use them in mainstream applications... Not for 2014 whales, but for today's users."

For now, scalability, tokenomics, mainstream adoption, and decentralization believers seem to be holding Web3 hostage.

Much like crypto's past.

But stay tuned.

If tasked with the problem of coming up with a zk-SNARK protocol, many people would make their way to this point and then get stuck and give up. How can a verifier possibly check every single piece of the computation, without looking at each piece of the computation individually? But it turns out that there is a clever solution.

Polynomials

Polynomials are a special class of algebraic expressions of the form:

• x+5
• x^4
• x^3+3x^2+3x+1
• 628x^{271}+318x^{270}+530x^{269}+…+69x+381

i.e. they are a sum of any (finite!) number of terms of the form cx^k

There are many things that are fascinating about polynomials. But here we are going to zoom in on a particular one: polynomials are a single mathematical object that can contain an unbounded amount of information (think of them as a list of integers and this is obvious). The fourth example above contained 816 digits of tau, and one can easily imagine a polynomial that contains far more.

Furthermore, a single equation between polynomials can represent an unbounded number of equations between numbers. For example, consider the equation A(x)+ B(x) = C(x). If this equation is true, then it's also true that:

• A(0)+B(0)=C(0)
• A(1)+B(1)=C(1)
• A(2)+B(2)=C(2)
• A(3)+B(3)=C(3)

And so on for every possible coordinate. You can even construct polynomials to deliberately represent sets of numbers so you can check many equations all at once. For example, suppose that you wanted to check:

• 12+1=13
• 10+8=18
• 15+8=23
• 15+13=28

You can use a procedure called Lagrange interpolation to construct polynomials A(x) that give (12,10,15,15) as outputs at some specific set of coordinates (eg. (0,1,2,3)), B(x) the outputs (1,8,8,13) on thos same coordinates, and so forth. In fact, here are the polynomials:

• A(x)=-2x^3+\frac{19}{2}x^2-\frac{19}{2}x+12
• B(x)=2x^3-\frac{19}{2}x^2+\frac{29}{2}x+1
• C(x)=5x+13

Checking the equation A(x)+B(x)=C(x) with these polynomials checks all four above equations at the same time.

Comparing a polynomial to itself

You can even check relationships between a large number of adjacent evaluations of the same polynomial using a simple polynomial equation. This is slightly more advanced. Suppose that you want to check that, for a given polynomial F, F(x+2)=F(x)+F(x+1) with the integer range {0,1…89} (so if you also check F(0)=F(1)=1, then F(100) would be the 100th Fibonacci number)

As polynomials, F(x+2)-F(x+1)-F(x) would not be exactly zero, as it could give arbitrary answers outside the range x={0,1…98}. But we can do something clever. In general, there is a rule that if a polynomial P is zero across some set S=\{x_1,x_2…x_n\} then it can be expressed as P(x)=Z(x)*H(x), where Z(x)=(x-x_1)*(x-x_2)*…*(x-x_n) and H(x) is also a polynomial. In other words, any polynomial that equals zero across some set is a (polynomial) multiple of the simplest (lowest-degree) polynomial that equals zero across that same set.

Why is this the case? It is a nice corollary of polynomial long division: the factor theorem. We know that, when dividing P(x) by Z(x), we will get a quotient Q(x) and a remainder R(x) is strictly less than that of Z(x). Since we know that P is zero on all of S, it means that R has to be zero on all of S as well. So we can simply compute R(x) via polynomial interpolation, since it's a polynomial of degree at most n-1 and we know n values (the zeros at S). Interpolating a polynomial with all zeroes gives the zero polynomial, thus R(x)=0 and H(x)=Q(x).

Going back to our example, if we have a polynomial F that encodes Fibonacci numbers (so F(x+2)=F(x)+F(x+1) across x=\{0,1…98\}), then I can convince you that F actually satisfies this condition by proving that the polynomial P(x)=F(x+2)-F(x+1)-F(x) is zero over that range, by giving you the quotient:
H(x)=\frac{F(x+2)-F(x+1)-F(x)}{Z(x)}
Where Z(x) = (x-0)*(x-1)*…*(x-98).
You can calculate Z(x) yourself (ideally you would have it precomputed), check the equation, and if the check passes then F(x) satisfies the condition!

Now, step back and notice what we did here. We converted a 100-step-long computation into a single equation with polynomials. Of course, proving the N'th Fibonacci number is not an especially useful task, especially since Fibonacci numbers have a closed form. But you can use exactly the same basic technique, just with some extra polynomials and some more complicated equations, to encode arbitrary computations with an arbitrarily large number of steps.

Photo by Juanjo Jaramillo on Unsplash

Calling APIs is the most common thing to do in any modern web application. When it comes to talking with an API then most of the time we need to do a lot of repetitive things like getting data from an API call, handling the success or error case, and so on.

When calling tens of hundreds of API calls we always have to do those tedious tasks. We can handle those things efficiently by putting a higher level of abstraction over those barebone API calls, whereas in some small applications, sometimes we don’t even care.

The problem comes when we start adding new features on top of the existing features without handling the API calls in an efficient and reusable manner. In that case for all of those API calls related repetitions, we end up with a lot of repetitive code across the whole application.

In React, we have different approaches for calling an API. Nowadays mostly we use React hooks. With React hooks, it’s possible to handle API calls in a very clean and consistent way throughout the application in spite of whatever the application size is. So let’s see how we can make a clean and reusable API calling layer using React hooks for a simple web application.

I’m using a code sandbox for this blog which you can get here.

import "./styles.css";
import React, { useEffect, useState } from "react";
import axios from "axios";

export default function App() {
  const [posts, setPosts] = useState(null);
  const [error, setError] = useState("");
  const [loading, setLoading] = useState(false);

  useEffect(() => {
    handlePosts();
  }, []);

  const handlePosts = async () => {
    setLoading(true);
    try {
      const result = await axios.get(
        "https://jsonplaceholder.typicode.com/posts"
      );
      setPosts(result.data);
    } catch (err) {
      setError(err.message || "Unexpected Error!");
    } finally {
      setLoading(false);
    }
  };

  return (
    <div className="App">
      <div>
        <h1>Posts</h1>
        {loading && <p>Posts are loading!</p>}
        {error && <p>{error}</p>}
        <ul>
          {posts?.map((post) => (
            <li key={post.id}>{post.title}</li>
          ))}
        </ul>
      </div>
    </div>
  );
}

I know the example above isn’t the best code but at least it’s working and it’s valid code. I will try to improve that later. For now, we can just focus on the bare minimum things for calling an API.

Here, you can try to get posts data from JsonPlaceholer. Those are the most common steps we follow for calling an API like requesting data, handling loading, success, and error cases.

If we try to call another API from the same component then how that would gonna look? Let’s see.

500: Internal Server Error

Now it’s going insane! For calling two simple APIs we’ve done a lot of duplication. On a top-level view, the component is doing nothing but just making two GET requests and handling the success and error cases. For each request, it’s maintaining three states which will periodically increase later if we’ve more calls.

Let’s refactor to make the code more reusable with fewer repetitions.

Step 1: Create a Hook for the Redundant API Request Codes

Most of the repetitions we have done so far are about requesting data, handing the async things, handling errors, success, and loading states. How about encapsulating those things inside a hook?

The only unique things we are doing inside handleComments and handlePosts are calling different endpoints. The rest of the things are pretty much the same. So we can create a hook that will handle the redundant works for us and from outside we’ll let it know which API to call.

500: Internal Server Error

Here, this request function is identical to what we were doing on the handlePosts and handleComments. The only difference is, it’s calling an async function apiFunc which we will provide as a parameter with this hook. This apiFunc is the only independent thing among any of the API calls we need.

With hooks in action, let’s change our old codes in App component, like this:

500: Internal Server Error

How about the current code? Isn’t it beautiful without any repetitions and duplicate API call handling things?

Let’s continue our journey from the current code. We can make App component more elegant. Now it knows a lot of details about the underlying library for the API call. It shouldn’t know that. So, here’s the next step…

Step 2: One Component Should Take Just One Responsibility

Our App component knows too much about the API calling mechanism. Its responsibility should just request the data. How the data will be requested under the hood, it shouldn’t care about that.

We will extract the API client-related codes from the App component. Also, we will group all the API request-related codes based on the API resource. Now, this is our API client:

import axios from "axios";

const apiClient = axios.create({
  // Later read this URL from an environment variable
  baseURL: "https://jsonplaceholder.typicode.com"
});

export default apiClient;

All API calls for comments resource will be in the following file:

import client from "./client";

const getComments = () => client.get("/comments");

export default {
  getComments
};

All API calls for posts resource are placed in the following file:

import client from "./client";

const getPosts = () => client.get("/posts");

export default {
  getPosts
};

Finally, the App component looks like the following:

import "./styles.css";
import React, { useEffect } from "react";
import commentsApi from "./api/comments";
import postsApi from "./api/posts";
import useApi from "./hooks/useApi";

export default function App() {
  const getPostsApi = useApi(postsApi.getPosts);
  const getCommentsApi = useApi(commentsApi.getComments);

  useEffect(() => {
    getPostsApi.request();
    getCommentsApi.request();
  }, []);

  return (
    <div className="App">
      {/* Post List */}
      <div>
        <h1>Posts</h1>
        {getPostsApi.loading && <p>Posts are loading!</p>}
        {getPostsApi.error && <p>{getPostsApi.error}</p>}
        <ul>
          {getPostsApi.data?.map((post) => (
            <li key={post.id}>{post.title}</li>
          ))}
        </ul>
      </div>
      {/* Comment List */}
      <div>
        <h1>Comments</h1>
        {getCommentsApi.loading && <p>Comments are loading!</p>}
        {getCommentsApi.error && <p>{getCommentsApi.error}</p>}
        <ul>
          {getCommentsApi.data?.map((comment) => (
            <li key={comment.id}>{comment.name}</li>
          ))}
        </ul>
      </div>
    </div>
  );
}

Now it doesn’t know anything about how the APIs get called. Tomorrow if we want to change the API calling library from axios to fetch or anything else, our App component code will not get affected. We can just change the codes form client.js This is the beauty of abstraction.

Apart from the abstraction of API calls, Appcomponent isn’t right the place to show the list of the posts and comments. It’s a high-level component. It shouldn’t handle such low-level data interpolation things.

So we should move this data display-related things to another low-level component. Here I placed those directly in the App component just for the demonstration purpose and not to distract with component composition-related things.

Final Thoughts

The React library gives the flexibility for using any kind of third-party library based on the application’s needs. As it doesn’t have any predefined architecture so different teams/developers adopted different approaches to developing applications with React. There’s nothing good or bad. We choose the development practice based on our needs/choices. One thing that is there beyond any choices is writing clean and maintainable codes.

Historically, only large financial institutions, brokerages, and trading houses could actively trade in the stock market. With instant global news dissemination and low commissions, developments such as discount brokerages and online trading have leveled the playing—or should we say trading—field. It's never been easier for retail investors to trade like pros thanks to trading platforms like Robinhood and zero commissions.

Day trading is a lucrative career (as long as you do it properly). But it can be difficult for newbies, especially if they aren't fully prepared with a strategy. Even the most experienced day traders can lose money.

So, how does day trading work?

Day Trading Basics

Day trading is the practice of buying and selling a security on the same trading day. It occurs in all markets, but is most common in forex and stock markets. Day traders are typically well educated and well funded. For small price movements in highly liquid stocks or currencies, they use leverage and short-term trading strategies.

Day traders are tuned into short-term market events. News trading is a popular strategy. Scheduled announcements like economic data, corporate earnings, or interest rates are influenced by market psychology. Markets react when expectations are not met or exceeded, usually with large moves, which can help day traders.

Intraday trading strategies abound. Among these are:

• Scalping: This strategy seeks to profit from minor price changes throughout the day.
• Range trading: To determine buy and sell levels, range traders use support and resistance levels.
• News-based trading exploits the increased volatility around news events.
• High-frequency trading (HFT): The use of sophisticated algorithms to exploit small or short-term market inefficiencies.

A Disputed Practice

Day trading's profit potential is often debated on Wall Street. Scammers have enticed novices by promising huge returns in a short time. Sadly, the notion that trading is a get-rich-quick scheme persists. Some daytrade without knowledge. But some day traders succeed despite—or perhaps because of—the risks.

Day trading is frowned upon by many professional money managers. They claim that the reward rarely outweighs the risk. Those who day trade, however, claim there are profits to be made. Profitable day trading is possible, but it is risky and requires considerable skill. Moreover, economists and financial professionals agree that active trading strategies tend to underperform passive index strategies over time, especially when fees and taxes are factored in.

Day trading is not for everyone and is risky. It also requires a thorough understanding of how markets work and various short-term profit strategies. Though day traders' success stories often get a lot of media attention, keep in mind that most day traders are not wealthy: Many will fail, while others will barely survive. Also, while skill is important, bad luck can sink even the most experienced day trader.

Characteristics of a Day Trader

Experts in the field are typically well-established professional day traders.
They usually have extensive market knowledge. Here are some prerequisites for successful day trading.

Market knowledge and experience

Those who try to day-trade without understanding market fundamentals frequently lose. Day traders should be able to perform technical analysis and read charts. Charts can be misleading if not fully understood. Do your homework and know the ins and outs of the products you trade.

Enough capital

Day traders only use risk capital they can lose. This not only saves them money but also helps them trade without emotion. To profit from intraday price movements, a lot of capital is often required. Most day traders use high levels of leverage in margin accounts, and volatile market swings can trigger large margin calls on short notice.

Strategy

A trader needs a competitive advantage. Swing trading, arbitrage, and trading news are all common day trading strategies. They tweak these strategies until they consistently profit and limit losses.

Strategy Breakdown:

Type | Risk | Reward

Swing Trading | High | High
Arbitrage | Low | Medium
Trading News | Medium | Medium
Mergers/Acquisitions | Medium | High

Discipline

A profitable strategy is useless without discipline. Many day traders lose money because they don't meet their own criteria. “Plan the trade and trade the plan,” they say. Success requires discipline.

Day traders profit from market volatility. For a day trader, a stock's daily movement is appealing. This could be due to an earnings report, investor sentiment, or even general economic or company news.

Day traders also prefer highly liquid stocks because they can change positions without affecting the stock's price. Traders may buy a stock if the price rises. If the price falls, a trader may decide to sell short to profit.

A day trader wants to trade a stock that moves (a lot).

Day Trading for a Living

Professional day traders can be self-employed or employed by a larger institution.

Most day traders work for large firms like hedge funds and banks' proprietary trading desks. These traders benefit from direct counterparty lines, a trading desk, large capital and leverage, and expensive analytical software (among other advantages). By taking advantage of arbitrage and news events, these traders can profit from less risky day trades before individual traders react.

Individual traders often manage other people’s money or simply trade with their own. They rarely have access to a trading desk, but they frequently have strong ties to a brokerage (due to high commissions) and other resources. However, their limited scope prevents them from directly competing with institutional day traders. Not to mention more risks. Individuals typically day trade highly liquid stocks using technical analysis and swing trades, with some leverage. 

Day trading necessitates access to some of the most complex financial products and services. Day traders usually need:

Access to a trading desk

Traders who work for large institutions or manage large sums of money usually use this. The trading or dealing desk provides these traders with immediate order execution, which is critical during volatile market conditions. For example, when an acquisition is announced, day traders interested in merger arbitrage can place orders before the rest of the market.

News sources

The majority of day trading opportunities come from news, so being the first to know when something significant happens is critical. It has access to multiple leading newswires, constant news coverage, and software that continuously analyzes news sources for important stories.

Analytical tools

Most day traders rely on expensive trading software. Technical traders and swing traders rely on software more than news. This software's features include:

• Automatic pattern recognition: It can identify technical indicators like flags and channels, or more complex indicators like Elliott Wave patterns.

• Genetic and neural applications: These programs use neural networks and genetic algorithms to improve trading systems and make more accurate price predictions.

• Broker integration: Some of these apps even connect directly to the brokerage, allowing for instant and even automatic trade execution. This reduces trading emotion and improves execution times.

• Backtesting: This allows traders to look at past performance of a strategy to predict future performance. Remember that past results do not always predict future results.

Together, these tools give traders a competitive advantage. It's easy to see why inexperienced traders lose money without them. A day trader's earnings potential is also affected by the market in which they trade, their capital, and their time commitment.

Day Trading Risks

Day trading can be intimidating for the average investor due to the numerous risks involved. The SEC highlights the following risks of day trading:

Because day traders typically lose money in their first months of trading and many never make profits, they should only risk money they can afford to lose.
Trading is a full-time job that is stressful and costly: Observing dozens of ticker quotes and price fluctuations to spot market trends requires intense concentration. Day traders also spend a lot on commissions, training, and computers.
Day traders heavily rely on borrowing: Day-trading strategies rely on borrowed funds to make profits, which is why many day traders lose everything and end up in debt.
Avoid easy profit promises: Avoid “hot tips” and “expert advice” from day trading newsletters and websites, and be wary of day trading educational seminars and classes. 

Should You Day Trade?
As stated previously, day trading as a career can be difficult and demanding.

• First, you must be familiar with the trading world and know your risk tolerance, capital, and goals.
• Day trading also takes a lot of time. You'll need to put in a lot of time if you want to perfect your strategies and make money. Part-time or whenever isn't going to cut it. You must be fully committed.
• If you decide trading is for you, remember to start small. Concentrate on a few stocks rather than jumping into the market blindly. Enlarging your trading strategy can result in big losses.
• Finally, keep your cool and avoid trading emotionally. The more you can do that, the better. Keeping a level head allows you to stay focused and on track.
  If you follow these simple rules, you may be on your way to a successful day trading career.

Is Day Trading Illegal?

Day trading is not illegal or unethical, but it is risky. Because most day-trading strategies use margin accounts, day traders risk losing more than they invest and becoming heavily in debt.

How Can Arbitrage Be Used in Day Trading?

Arbitrage is the simultaneous purchase and sale of a security in multiple markets to profit from small price differences. Because arbitrage ensures that any deviation in an asset's price from its fair value is quickly corrected, arbitrage opportunities are rare.

Why Don’t Day Traders Hold Positions Overnight?

Day traders rarely hold overnight positions for several reasons: Overnight trades require more capital because most brokers require higher margin; stocks can gap up or down on overnight news, causing big trading losses; and holding a losing position overnight in the hope of recovering some or all of the losses may be against the trader's core day-trading philosophy.

What Are Day Trader Margin Requirements?

Regulation D requires that a pattern day trader client of a broker-dealer maintain at all times $25,000 in equity in their account.

How Much Buying Power Does Day Trading Have?

Buying power is the total amount of funds an investor has available to trade securities. FINRA rules allow a pattern day trader to trade up to four times their maintenance margin excess as of the previous day's close.

The Verdict

Although controversial, day trading can be a profitable strategy. Day traders, both institutional and retail, keep the markets efficient and liquid. Though day trading is still popular among novice traders, it should be left to those with the necessary skills and resources.