Connect with us

Uncategorized

Algorithmic Trading Global Market Report 2022: A $24.79 Billion Market by 2026 – Long-term Forecasts to 2031

Algorithmic Trading Global Market Report 2022: A $24.79 Billion Market by 2026 – Long-term Forecasts to 2031
PR Newswire
DUBLIN, Jan. 25, 2023

 
DUBLIN, Jan. 25, 2023 /PRNewswire/ — The “Algorithmic Trading Global Market Report 2022: Ukraine-Russi…

Published

1 year ago

on

Algorithmic Trading Global Market Report 2022: A $24.79 Billion Market by 2026 - Long-term Forecasts to 2031

PR Newswire

DUBLIN, Jan. 25, 2023

 

DUBLIN, Jan. 25, 2023 /PRNewswire/ -- The "Algorithmic Trading Global Market Report 2022: Ukraine-Russia War Impact" report has been added to ResearchAndMarkets.com's offering.

 

The global algorithmic trading market is expected to grow from $14.13 billion in 2021 to $15.93 billion in 2022 at a compound annual growth rate (CAGR) of 12.7%. The algorithmic trading market is expected to reach $24.79 billion in 2026 at a CAGR of 11.7%.

The algorithmic trading includes revenues earned by entities by providing automated trading services, financial services, trade executions, system architecture management. The market value includes the value of related goods sold by the service provider or included within the service offering.

Algorithmic trading is a technique that uses scripted computer codes and algorithms to open and close transactions under predefined rules that are programmed into a computer system. It reduces transaction costs and avoids significant price changes.

North America was the largest region in the algorithmic trading market in 2021. Asia Pacific is expected to be the fastest-growing region in the forecast period. The regions covered in the algorithmic trading market report are Asia-Pacific, Western Europe, Eastern Europe, North America, South America, Middle East and Africa.

The market value is defined as the revenues that enterprises gain from goods and/or services sold within the specified market and geography through sales, grants, or donations in terms of currency (in USD ($) unless otherwise specified).

The revenues for a specified geography are consumption values - that is, they are revenues generated by organisations in the specified geography within the specified market, irrespective of where they are produced. It does not include revenues from resales either further along the supply chain or as part of other products.

The main types of algorithmic trading are stock market, foreign exchange (forex), exchange-traded fund (ETF), bonds, cryptocurrencies, and others. A stock market refers to a location where buyers and sellers exchange public corporation equity shares. The components involved are solutions and services that operate on programming, debugging, data extraction, back-testing and optimization, risk management functions. These are used by institutional investors, long-term traders, short-term traders, retail investors for equities, forex, commodities, funds, other applications.

The rising need for quick digital transformation is expected to propel the algorithmic trading market going forward. Digital transformation refers to the process of employing digital technology to build new business processes, cultures, and customer experiences or to adapt current ones to fit shifting company and market needs. The quick digital transformation leads to an increasing number of trades that can boost algorithmic trading.

For instance, according to articles published by Forbes, a US-based business magazine, in 2019 globally, 70% of businesses either already have a digital transformation strategy in place or are developing one. Additionally, the year 2019 has seen a 40% increase in investment in technology related to digital transformation with businesses investing over $2 trillion in digital transformation. Therefore, the rising need for quick digital transformation is driving the algorithmic trading market.

Product innovations are a key trend gaining popularity in the algorithmic trading market. Major players are concentrating their efforts on creating innovative products to sustain their position in the algorithmic trading market. For instance, in July 2021, Rain Technologies, Inc., a Canada-based technology company, launched RAIN TRADER. Rain Trader is a web-based platform that provides automated trading and algorithmic trading models. This platform gives individuals the opportunity to engage in hassle-free, fully automated algorithmic trading.

In March 2022, Trading Technologies International Inc., a US-based technology company specializing in professional trading software, infrastructure, and data solutions, acquired RCM-X for an undisclosed amount. Through this acquisition Trading Technologies increases its product portfolio in algorithmic execution strategies, trade analytics, and TCA (transaction cost analysis) services to improve customer experience. RCM-X is a US-based financial technology company that develops algorithmic execution strategies and quantitative trading products.

The countries covered in the algorithmic trading market report are Australia, Brazil, China, France, Germany, India, Indonesia, Japan, Russia, South Korea, UK, USA.

A selection of companies mentioned in this report includes

  • 63 Moons Technologies Limited
  • MetaQuotes Software
  • AlgoTrader
  • Virtu Financial Inc.
  • Tethys Technology Inc.
  • Trading Technologies International Inc.
  • Argo SE
  • Software AG
  • Vela Trading Systems LLC
  • uTrade Solutions
  • InfoReach Inc.
  • Tata Consultancy Services
  • Symphony Fintech Solutions Pvt. Ltd.
  • Refinitiv
  • Thomson Reuters Corporation
  • iRageCapital Advisory Private Limited
  • Lightspeed Financial Services Group LLC
  • FlexTrade Systems Inc.
  • Citadel LLC.

Key Topics Covered:

1. Executive Summary

2. Algorithmic Trading Market Characteristics

3. Algorithmic Trading Market Trends And Strategies

4. Algorithmic Trading Market - Macro Economic Scenario
4.1. COVID-19 Impact On Algorithmic Trading Market
4.2. Ukraine-Russia War Impact On Algorithmic Trading Market
4.3. Impact Of High Inflation On Algorithmic Trading Market

5. Algorithmic Trading Market Size And Growth
5.1. Global Algorithmic Trading Historic Market, 2016-2021, $ Billion
5.1.1. Drivers Of The Market
5.1.2. Restraints On The Market
5.2. Global Algorithmic Trading Forecast Market, 2021-2026F, 2031F, $ Billion
5.2.1. Drivers Of The Market
5.2.2. Restraints On the Market

6. Algorithmic Trading Market Segmentation
6.1. Global Algorithmic Trading Market, Segmentation By Type, Historic and Forecast, 2016-2021, 2021-2026F, 2031F, $ Billion

  • Stock Market
  • Foreign Exchange (FOREX)
  • Exchange-Traded Fund (ETF)
  • Bonds
  • Cryptocurrencies
  • Other Types

6.2. Global Algorithmic Trading Market, Segmentation By Component, Historic and Forecast, 2016-2021, 2021-2026F, 2031F, $ Billion

  • Solution
  • Services

6.3. Global Algorithmic Trading Market, Segmentation By Function, Historic and Forecast, 2016-2021, 2021-2026F, 2031F, $ Billion

  • Programming
  • Debugging
  • Data Extraction
  • Back-Testing and Optimization
  • Risk Management

6.4. Global Algorithmic Trading Market, Segmentation By Type Of Traders, Historic and Forecast, 2016-2021, 2021-2026F, 2031F, $ Billion

  • Institutional Investors
  • Long-Term Traders
  • Short-Term Traders
  • Retail Investors

6.5. Global Algorithmic Trading Market, Segmentation By Application, Historic and Forecast, 2016-2021, 2021-2026F, 2031F, $ Billion

  • Equities
  • Forex
  • Commodities
  • Funds
  • Other Applications

7. Algorithmic Trading Market Regional And Country Analysis
7.1. Global Algorithmic Trading Market, Split By Region, Historic and Forecast, 2016-2021, 2021-2026F, 2031F, $ Billion
7.2. Global Algorithmic Trading Market, Split By Country, Historic and Forecast, 2016-2021, 2021-2026F, 2031F, $ Billion

For more information about this report visit https://www.researchandmarkets.com/r/hre7mb

About ResearchAndMarkets.com
ResearchAndMarkets.com is the world's leading source for international market research reports and market data. We provide you with the latest data on international and regional markets, key industries, the top companies, new products and the latest trends.

Media Contact:

Research and Markets
Laura Wood, Senior Manager
press@researchandmarkets.com
 
For E.S.T Office Hours Call +1-917-300-0470
For U.S./CAN Toll Free Call +1-800-526-8630
For GMT Office Hours Call +353-1-416-8900
 
U.S. Fax: 646-607-1907
Fax (outside U.S.): +353-1-481-1716

Logo: https://mma.prnewswire.com/media/539438/Research_and_Markets_Logo.jpg

View original content:https://www.prnewswire.com/news-releases/algorithmic-trading-global-market-report-2022-a-24-79-billion-market-by-2026---long-term-forecasts-to-2031--301730912.html

SOURCE Research and Markets

Read More

Related Topics:
Continue Reading

Uncategorized

Aging at AACR Annual Meeting 2024

BUFFALO, NY- March 11, 2024 – Impact Journals publishes scholarly journals in the biomedical sciences with a focus on all areas of cancer and aging…

Published

6 hours ago

on

March 11, 2024

By

BUFFALO, NY- March 11, 2024 – Impact Journals publishes scholarly journals in the biomedical sciences with a focus on all areas of cancer and aging research. Aging is one of the most prominent journals published by Impact Journals. 

Credit: Impact Journals

BUFFALO, NY- March 11, 2024 – Impact Journals publishes scholarly journals in the biomedical sciences with a focus on all areas of cancer and aging research. Aging is one of the most prominent journals published by Impact Journals. 

Impact Journals will be participating as an exhibitor at the American Association for Cancer Research (AACR) Annual Meeting 2024 from April 5-10 at the San Diego Convention Center in San Diego, California. This year, the AACR meeting theme is “Inspiring Science • Fueling Progress • Revolutionizing Care.”

Visit booth #4159 at the AACR Annual Meeting 2024 to connect with members of the Aging team.

About Aging-US:

Aging publishes research papers in all fields of aging research including but not limited, aging from yeast to mammals, cellular senescence, age-related diseases such as cancer and Alzheimer’s diseases and their prevention and treatment, anti-aging strategies and drug development and especially the role of signal transduction pathways such as mTOR in aging and potential approaches to modulate these signaling pathways to extend lifespan. The journal aims to promote treatment of age-related diseases by slowing down aging, validation of anti-aging drugs by treating age-related diseases, prevention of cancer by inhibiting aging. Cancer and COVID-19 are age-related diseases.

Aging is indexed and archived by PubMed/Medline (abbreviated as “Aging (Albany NY)”), PubMed Central, Web of Science: Science Citation Index Expanded (abbreviated as “Aging‐US” and listed in the Cell Biology and Geriatrics & Gerontology categories), Scopus (abbreviated as “Aging” and listed in the Cell Biology and Aging categories), Biological Abstracts, BIOSIS Previews, EMBASE, META (Chan Zuckerberg Initiative) (2018-2022), and Dimensions (Digital Science).

Please visit our website at www.Aging-US.com​​ and connect with us:

  • Aging X
  • Aging Facebook
  • Aging Instagram
  • Aging YouTube
  • Aging LinkedIn
  • Aging SoundCloud
  • Aging Pinterest
  • Aging Reddit

Click here to subscribe to Aging publication updates.

For media inquiries, please contact media@impactjournals.com.

Read More

Continue Reading

Uncategorized

NY Fed Finds Medium, Long-Term Inflation Expectations Jump Amid Surge In Stock Market Optimism

NY Fed Finds Medium, Long-Term Inflation Expectations Jump Amid Surge In Stock Market Optimism

One month after the inflation outlook tracked…

Published

11 hours ago

on

March 11, 2024

By

NY Fed Finds Medium, Long-Term Inflation Expectations Jump Amid Surge In Stock Market Optimism

One month after the inflation outlook tracked by the NY Fed Consumer Survey extended their late 2023 slide, with 3Y inflation expectations in January sliding to a record low 2.4% (from 2.6% in December), even as 1 and 5Y inflation forecasts remained flat, moments ago the NY Fed reported that in February there was a sharp rebound in longer-term inflation expectations, rising to 2.7% from 2.4% at the three-year ahead horizon, and jumping to 2.9% from 2.5% at the five-year ahead horizon, while the 1Y inflation outlook was flat for the 3rd month in a row, stuck at 3.0%. 

The increases in both the three-year ahead and five-year ahead measures were most pronounced for respondents with at most high school degrees (in other words, the "really smart folks" are expecting deflation soon). The survey’s measure of disagreement across respondents (the difference between the 75th and 25th percentile of inflation expectations) decreased at all horizons, while the median inflation uncertainty—or the uncertainty expressed regarding future inflation outcomes—declined at the one- and three-year ahead horizons and remained unchanged at the five-year ahead horizon.

Going down the survey, we find that the median year-ahead expected price changes increased by 0.1 percentage point to 4.3% for gas; decreased by 1.8 percentage points to 6.8% for the cost of medical care (its lowest reading since September 2020); decreased by 0.1 percentage point to 5.8% for the cost of a college education; and surprisingly decreased by 0.3 percentage point for rent to 6.1% (its lowest reading since December 2020), and remained flat for food at 4.9%.

We find the rent expectations surprising because it is happening just asking rents are rising across the country.

At the same time as consumers erroneously saw sharply lower rents, median home price growth expectations remained unchanged for the fifth consecutive month at 3.0%.

Turning to the labor market, the survey found that the average perceived likelihood of voluntary and involuntary job separations increased, while the perceived likelihood of finding a job (in the event of a job loss) declined. "The mean probability of leaving one’s job voluntarily in the next 12 months also increased, by 1.8 percentage points to 19.5%."

Mean unemployment expectations - or the mean probability that the U.S. unemployment rate will be higher one year from now - decreased by 1.1 percentage points to 36.1%, the lowest reading since February 2022. Additionally, the median one-year-ahead expected earnings growth was unchanged at 2.8%, remaining slightly below its 12-month trailing average of 2.9%.

Turning to household finance, we find the following:

  • The median expected growth in household income remained unchanged at 3.1%. The series has been moving within a narrow range of 2.9% to 3.3% since January 2023, and remains above the February 2020 pre-pandemic level of 2.7%.
  • Median household spending growth expectations increased by 0.2 percentage point to 5.2%. The increase was driven by respondents with a high school degree or less.
  • Median year-ahead expected growth in government debt increased to 9.3% from 8.9%.
  • The mean perceived probability that the average interest rate on saving accounts will be higher in 12 months increased by 0.6 percentage point to 26.1%, remaining below its 12-month trailing average of 30%.
  • Perceptions about households’ current financial situations deteriorated somewhat with fewer respondents reporting being better off than a year ago. Year-ahead expectations also deteriorated marginally with a smaller share of respondents expecting to be better off and a slightly larger share of respondents expecting to be worse off a year from now.
  • The mean perceived probability that U.S. stock prices will be higher 12 months from now increased by 1.4 percentage point to 38.9%.
  • At the same time, perceptions and expectations about credit access turned less optimistic: "Perceptions of credit access compared to a year ago deteriorated with a larger share of respondents reporting tighter conditions and a smaller share reporting looser conditions compared to a year ago."

Also, a smaller percentage of consumers, 11.45% vs 12.14% in prior month, expect to not be able to make minimum debt payment over the next three months

Last, and perhaps most humorous, is the now traditional cognitive dissonance one observes with these polls, because at a time when long-term inflation expectations jumped, which clearly suggests that financial conditions will need to be tightened, the number of respondents expecting higher stock prices one year from today jumped to the highest since November 2021... which incidentally is just when the market topped out during the last cycle before suffering a painful bear market.

Tyler Durden Mon, 03/11/2024 - 12:40

Read More

Continue Reading

Uncategorized

Homes listed for sale in early June sell for $7,700 more

New Zillow research suggests the spring home shopping season may see a second wave this summer if mortgage rates fall
The post Homes listed for sale in…

Published

18 hours ago

on

March 11, 2024

By

  • A Zillow analysis of 2023 home sales finds homes listed in the first two weeks of June sold for 2.3% more. 
  • The best time to list a home for sale is a month later than it was in 2019, likely driven by mortgage rates.
  • The best time to list can be as early as the second half of February in San Francisco, and as late as the first half of July in New York and Philadelphia. 

Spring home sellers looking to maximize their sale price may want to wait it out and list their home for sale in the first half of June. A new Zillow® analysis of 2023 sales found that homes listed in the first two weeks of June sold for 2.3% more, a $7,700 boost on a typical U.S. home.  

The best time to list consistently had been early May in the years leading up to the pandemic. The shift to June suggests mortgage rates are strongly influencing demand on top of the usual seasonality that brings buyers to the market in the spring. This home-shopping season is poised to follow a similar pattern as that in 2023, with the potential for a second wave if the Federal Reserve lowers interest rates midyear or later. 

The 2.3% sale price premium registered last June followed the first spring in more than 15 years with mortgage rates over 6% on a 30-year fixed-rate loan. The high rates put home buyers on the back foot, and as rates continued upward through May, they were still reassessing and less likely to bid boldly. In June, however, rates pulled back a little from 6.79% to 6.67%, which likely presented an opportunity for determined buyers heading into summer. More buyers understood their market position and could afford to transact, boosting competition and sale prices.

The old logic was that sellers could earn a premium by listing in late spring, when search activity hit its peak. Now, with persistently low inventory, mortgage rate fluctuations make their own seasonality. First-time home buyers who are on the edge of qualifying for a home loan may dip in and out of the market, depending on what’s happening with rates. It is almost certain the Federal Reserve will push back any interest-rate cuts to mid-2024 at the earliest. If mortgage rates follow, that could bring another surge of buyers later this year.

Mortgage rates have been impacting affordability and sale prices since they began rising rapidly two years ago. In 2022, sellers nationwide saw the highest sale premium when they listed their home in late March, right before rates barreled past 5% and continued climbing. 

Zillow’s research finds the best time to list can vary widely by metropolitan area. In 2023, it was as early as the second half of February in San Francisco, and as late as the first half of July in New York. Thirty of the top 35 largest metro areas saw for-sale listings command the highest sale prices between May and early July last year. 

Zillow also found a wide range in the sale price premiums associated with homes listed during those peak periods. At the hottest time of the year in San Jose, homes sold for 5.5% more, a $88,000 boost on a typical home. Meanwhile, homes in San Antonio sold for 1.9% more during that same time period.  

 

Metropolitan Area Best Time to List Price Premium Dollar Boost
United States First half of June 2.3% $7,700
New York, NY First half of July 2.4% $15,500
Los Angeles, CA First half of May 4.1% $39,300
Chicago, IL First half of June 2.8% $8,800
Dallas, TX First half of June 2.5% $9,200
Houston, TX Second half of April 2.0% $6,200
Washington, DC Second half of June 2.2% $12,700
Philadelphia, PA First half of July 2.4% $8,200
Miami, FL First half of June 2.3% $12,900
Atlanta, GA Second half of June 2.3% $8,700
Boston, MA Second half of May 3.5% $23,600
Phoenix, AZ First half of June 3.2% $14,700
San Francisco, CA Second half of February 4.2% $50,300
Riverside, CA First half of May 2.7% $15,600
Detroit, MI First half of July 3.3% $7,900
Seattle, WA First half of June 4.3% $31,500
Minneapolis, MN Second half of May 3.7% $13,400
San Diego, CA Second half of April 3.1% $29,600
Tampa, FL Second half of June 2.1% $8,000
Denver, CO Second half of May 2.9% $16,900
Baltimore, MD First half of July 2.2% $8,200
St. Louis, MO First half of June 2.9% $7,000
Orlando, FL First half of June 2.2% $8,700
Charlotte, NC Second half of May 3.0% $11,000
San Antonio, TX First half of June 1.9% $5,400
Portland, OR Second half of April 2.6% $14,300
Sacramento, CA First half of June 3.2% $17,900
Pittsburgh, PA Second half of June 2.3% $4,700
Cincinnati, OH Second half of April 2.7% $7,500
Austin, TX Second half of May 2.8% $12,600
Las Vegas, NV First half of June 3.4% $14,600
Kansas City, MO Second half of May 2.5% $7,300
Columbus, OH Second half of June 3.3% $10,400
Indianapolis, IN First half of July 3.0% $8,100
Cleveland, OH First half of July  3.4% $7,400
San Jose, CA First half of June 5.5% $88,400

 

The post Homes listed for sale in early June sell for $7,700 more appeared first on Zillow Research.

Read More

Continue Reading

Trending