Posts by jack@benzinga.com

Benzinga increases client engagement & trade-lift with actionable alerts, rumors and unusual activity. Articles cover micro to macro-cap's across all sectors.


Corporate Logos

What are Corporate Logos?

Corporate Logos are designs or symbols that distinctively identify a specific company. These logos are typically trademarked, to deter others from its use. A logo has many different aspects. This includes color, shape, typeface, and symbol. Logos serve as a branding solution for firms. A great example of this is Nike. Nike’s corporate logo is the ‘’Swoosh.” It is simple with its monochromatic black and white design but also expresses motion with its fluidity.

What’s so Important About a Logo?

Logos are a powerful and influential tool in the business world. Logos are easily recognizable to the public, so individuals can make mentally connect a logo to a company, or vice versa, without difficulty. This is called brand identity and it’s extremely important in today’s financial space. Brand identity is an important aspect of a company as it gives consumers a simple understanding of what your company is and what it’s about.

The Benzinga Corporate Logo Package is now available on the BZ Cloud. Because of our full data catalog, we can provide over 2,000 corporate logos. Corporate logos are altered every day as older companies are always modifying their old designs to give a new and innovative look. In 2017, there were 160 IPOs of nascent companies with logos new to the financial space. Because of the introduction of new logos and their changes, our library of logos constantly updates. We offer a wide range of logos from most companies on major exchanges.  Our corporate logos are easy to integrate. They’re available via API and in many different formats like XML or JSON. The Benzinga Corporate Logo API is designed to be flexible with client sizing requirements. Custom filters can be applied to resize the logo and returns a variety of identifiers like ISIN and CUSIP.

 

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5 “Why?” questions every trader should ask himself / Walter Lesicar

Walter Lesicar is a professional order flow trader. The article below asks essential questions pertaining to liquidity and order flow. Walter uses dxFeed Bookmap to answer these questions.

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5 “ Why? ” questions every trader should ask himself / Walter Lesicar

In trading we all tend to ask nearly every day:

  • Why did price stop?
  • Why can’t we predict price?
  • Why is this the top or bottom?
  • Why does the price break a certain level?
  • Why are others placing fake limit orders?

And of course numerous other “Why” questions.

The “why” question is so powerful and omnipotent that it can sometimes torture us. Then we look for answers and solutions by force to find answer to “WHY”.

To cut a long story short: There are rarely satisfactory answers to the “Why” in trading. We can only begin to understand answers to a certain point.  

 

Why isn’t a Classical Chart helpful?

Candle Chart with Trend Lines

 

What can you say about this chart?

  • It is a clear trend up
  • The trend line is up

Now you may say: “There is a trend” and “This trend will continue”. But in fact, it only means: “There has been a trend until this moment.” It should be clear, there is no evidence this trend will continue or reverse. At this moment we simply don’t know. We assume and we hope.

Why does this trend stop here? Why did it reverse? Why did it continue?

I believe these questions can’t be answered based on classical charts. Why not? Because we don’t see what is happening and don’t have any indication what is “behind the curtain”. We are the “audience” and we see with an extremely limited view using trading software.

Classical charts based on Technical Analysis (TA) are misleading because they use historical data to plot patterns. Classical technical analysis leads you to assume patterns develop in a defined predictable environment. However, these patterns actually unfold in a truly random and unknowable sequence.

 

Informed vs. Uninformed Traders

I refer to the informed traders as the investors who have a temporary informational advantage over other market participants day trading stocks. They obtain this informational advantage because they either have some proprietary information or they are able to correctly process new public information more quickly than other investors in the market with day trading software. [1]

The informed investors typically use their temporary advantage to trade with the uninformed investors and extract profit from these transactions.[2]

The second main assumption is that the informed investors act on their information by submitting buy or sell orders. Thus, the informed investors partially disclose their information through their trades that cause higher permanent price changes, compared to the trades of the uninformed investors. [3]

When a large number of informed traders enter the market, it signals a higher probability of a price change in the near future after information has been released to the market. However, uninformed traders do not know the direction of the price change since they are unaware if the news released will be positive or negative. [4]

“Informed” traders possess more information about a company, stock, or event. “Uninformed” traders are risk averse and traders who represent liquidity providers.

 

Why can’t we predict the price?

As you know, an Order Book consists of a “Limit Part” and a “Market Part”. The limit part (‘passive orders’) represents all Limit Orders which are placed by informed and uninformed traders. The market part (‘aggressive orders’) represents all orders which hit the market by both groups at random times.

Why can’t we predict where the price is going next? Because we can’t foresee when and how aggressive market participants are hitting the order book at the market price level — the arrival of aggressive orders is hardly predictable.

But there is a chance, though!

 

Why analyzing passive orders?  

If the arrival of aggressive orders is hardly predictable, we must make this prediction based on observation of passive orders:

  • Are they weakening from the pressure by aggressive orders?
  • Do they desert, cancel or move orders away?
  • Do they stand the ground and absorb the pressure?
  • Do they bring even more forces?

Observing market depth and answering these questions helps to predict the outcome.

Why is the price bouncing off? Because informed traders are bringing more liquidity (or limit passive orders) to the price level.

Informed traders adding liquidity

 

Why does price falling through specific price levels? Because informed traders are canceling their limit orders.

Canceling Orders

Canceling Orders

 

Why does price hold a level? Because informed traders are standing their ground and absorbing all incoming market orders.

Informed traders are absorbing market order

 

Why Is Liquidity important?

We can always detect liquidity concentration above and below the current market price.

On dxFeed Bookmap liquidity concentration can be seen in advance. If price reaches this level, then price can:

  • Price goes through, because passive limit orders retreat, making the liquidity mark at this level irrelevant
  • Aggressive orders retreat and fail pushing the price through the liquidity – price bounces back
  • Fight between aggressive and passive orders, leading to large traded volume cluster

Liquidity is the “blood” of the market and its observance in daily trading turns an uninformed trader into an informed trader!

See also Liquidity 1 – Liquidity 3 in the Post section of my website.

 

Why are traders placing fake/spoof orders?

First of all, I wouldn’t speak of such a thing as a “fake” bid or offer. It is a “No Intention” to buy bid or to sell offer orders though. Basically, the reason large traders (and some smaller traders in thin securities) do this is to give the impression that there is either an abnormally large buyer or an abnormally large seller in the market.

Consider the following:

If you are day trading stocks and have a large amount e.g. 100.000 shares, or Future contracts e.g. 1000 contracts to sell, then you can’t do it all at once because you would manipulate the price to your disadvantage.

Likewise, if you display the order to sell on level 2 with day trading software, people may see that there is a (legitimate) large seller in the market and sell, driving the price down and preventing you from selling where you want as well as lowering the value of your investment.

Another option could be to sell 1000 Future contracts but hide it on level 2 as not to scare people. Otherwise, you could place 200 contracts to inform smaller traders there is enough liquidity so they can buy 50, 100 or more contracts if they want, but not so much that there is a need to have 1000 and more buyers behind them to make the price go up.

The problem with all of this is that you want to sell a large amount of contracts/shares into a market that doesn’t have many buyers.

You need demand. To create demand you might display/spoof/fake a buy order with NO INTENTION to buy of, let’s say 500 contracts on the bid. Now it seems that there is a large buyer in this market. This will create demand and entice retail/uninformed traders to buy. They will begin buying from you as your hidden sell order get filled piece by piece.

This is a risky game for the seller, though. As mentioned above there are no such things as “fake orders”. This 500 buy order is real at that moment! If there is a big seller right at that moment when the intentional seller is trying to find buyers for his inventory and if he doesn’t cancel his orders fast enough he will get a fill and will be long 500 contracts more.

That’s the real risk of placing “non-intentional” orders. Besides, it is illegal under the 2010 Dodd-Franck Act.

Everything can be inverted with trading software to spoof on the sell side and create artificial sell pressure if there is a need to buy before the price goes up. Both of these things are, despite being illegal, practiced pretty regularly by manipulative hedge funds and large traders.

HFT’s do this as well but very, very fast so you often won’t catch it on level 2 unless you are working with a level 2 visualization software like Bookmap is. Algos can use it as a method of price discovery also.

dxFeed Bookmap visualizes the market and enables stock traders to answer the WHY’s. It really all about the liquidity. By analyzing the liquidity, they can understand why specific market movements unfold, and this allows them to make more informed trading decisions. If you’d like to learn more, please attend a dxFeed Bookmap webinar.

 

[1]-[4] Informed Trading and Market Efficiency by Olga Lebedeva, 2012

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Financial Data APIs

What Are the Different Types of Financial Data APIs?

In an earlier blog post, we talked about what APIs are, in particular, stock and market data APIs, and some of the popular financial data APIs Benzinga offers.

In this blog post, we are going to discuss all of the different types of financial data APIs, and where you can buy them.

Let’s Refresh – What is a Financial API?

An API, application programming interface, is used as a tool to plug your website into another. There are countless financial and stock APIs in today’s world and they function as an excellent instrument to obtain information.

What Data Sets are Available?

Some of the many financial APIs that are available include:

  • FRED (Federal Reserve Economic Data)
  • Dow Jones Historical Data
  • Real Estate Data
  • Alternative Data
  • Bitcoin Data
  • Futures Data
  • Treasury Yield Curve Data
  • Gold, silver, aluminum, copper, rhodium, iridium, and coal prices/data

Financial APIs are essential for funds, institutions, and regular investors. These datasets are important because they allow you to access large amounts of information; this information can be processed in a way to be tailored to your goals.

Where to Get Financial APIs?

Financial APIs can be found in many places online. There are free APIs available on the internet; however, the best financial APIs usually will cost you some money. Data sets are obtainable through companies like Benzinga and Quandl. Depending on the source, these APIs can be as granular as needed.

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Futures Contracts Data

What are Futures Contracts?

Futures contracts, or futures, are financial agreements between two parties to typically either buy or sell a security or commodity at a date set in the future. The intended purpose of futures contracts was to mitigate risk; now, futures have many different uses. The two most common uses for futures contracts are for hedging and speculation.

Why Use Futures Contracts?

Let’s say you know you need to buy 1,000 of barrels of crude oil (or some coal, steel, copper, gold, silver, or even bitcoin futures) for your company in six month’s time (crude oil futures contracts are traded in lots sizes of 1,000 barrels). You wouldn’t want to buy 1,000 barrels of crude oil now. Instead, you would want to buy it in six months when you need it. Why? To avoid liquidity issues. If the spot price, the current marketplace price, of crude oil is more than that of the futures price, it would be advantageous to buy a six-month futures contract if you believe crude oil price will rise, or even stay the same, in the next six months. When you enter a futures contract, you are locked into a price to buy, or sell, a commodity/security on a set date.

If you’re interested in crude oil and how it moves, check out our blog post on Crude Oil Prices.

What Type of Futures Data is Available?

Market Futures

  • Historical Futures Data

Index Futures

  • DAX Futures Data
  • VIX Futures Data

Commodity Futures

  • Wheat Futures Data
  • Milk Futures Data
  • Fat Cattle Futures Data
  • Cocoa Futures Data
  • Crude Oil Futures Data

Futures data is accessible via financial API from our data catalog at https://cloud.benzinga.com/news-data-catalog.

Hopefully you learned something about futures contracts in this post!

If you have any unanswered questions please send us an email at licensing@benzinga.com and we’d be happy to answer them!

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Alternative Data

What is Alternative Data?

Alternative data, or alt data, is the data found outside the typical structure for an investor. Data that investors use within that structure is called traditional data which includes information like earnings, guidance and dividends. Everything else is alternative data. This information is sometimes classified as big data, complex information that can’t be processed by typical software. Examples include social media posts about bitcoin data and prices, degree of political leanings, web usage for specific sites, and credit statements.

Alternative data is evaluated by:

  • Scarcity
  • Specification
  • History
  • Structure
  • Reporting

Alternative data is becoming an increasingly popular commodity. The primary users of alternative data are investors, specifically quantitative hedge funds, known as quants or quant funds. These quant funds are quickly looking to buy as much of this data as possible. Their hopes are to use this alt data to increase alpha and profitability. If this information can be processed, sorted, and quantified in a practical method, then it would be considered to be an indispensable tool for these quant funds.

Why is Alternative Data Important to Me?

Why does someone need to know why quant funds and other investors are buying up vast amounts alternative data? A typical individual won’t find the information from alternative data sets useful, but it’s important to know where this information is coming from. Alternative data is data from consumers. Consumers willingly, but usually unknowingly, give up access to their privacy. This is done via mobile phone apps and web usage (think Facebook). Companies can gain access to this information and leverage it to increase profits. Consumers should be vigilant of this practice.
Alternative data is available through many different formats. One of the more popular applications to transfer datasets is API. For more information about APIs, please read our other blog posts here https://cloud.benzinga.com/2018/06/what-is-a-stock-api-and-market-data/.  More information regarding alternative datasets can be found at Benzinga’s data catalog at https://cloud.benzinga.com/alternativedata/.

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