SBI Raises Rs.4,000 Cr via Issue of AT-1 Bonds

SBI AT1 Bonds
01/09/2021

State Bank of India announced that it had raised Rs.4,000 crore through the issue of Additional Tier-1 (AT-1) Bonds. These AT-1 bonds are perpetual bonds that do not have any specified maturity. However, the issuer has the prerogative to call back the bonds after a period of 5 years, which is generally the norm. However, the interest will be paid on a periodic basis on these bonds.

One of the big advantages of AT-1 bonds is that they are treated as quasi-equity and, being perpetual in nature, they are at par with equity. Hence, any AT-1 bond raising directly boosts the Tier-1 capital of the bank. The coupon rate on the AT-1 bonds has been fixed at 7.72%, which is one of the most competitive rates in that segment.

The base issue size was Rs.1,000 crore, but SBI received bids for almost Rs.10,000 crore. Finally, SBI has decided to accept bonds worth Rs.4,000 crore at the coupon of 7.72%. AT-1 bonds had come under some sort of cloud last year after Yes Bank repudiated its AT-1 bonds but that is normally not a concern for investors when it comes to blue-chip banks like SBI.

SBI was able to get a competitive coupon rate considering its AAA rating from all the domestic credit rating agencies. However, the AT-1 Bonds are rated AA+ considering the hybrid nature of these bonds and the higher risk implicit in these instruments since they are technically of perpetual maturity.

SBI has a capital adequacy of 13.66% as of June 2021 and needs to continuously boost its capital base in tune with the expansion of its loan book. Being the dominant PSU bank in India, it is expected to be one of the big beneficiaries of the post-pandemic boost to lending. The AT-1 bonds will help SBI to boost its Tier-1 capital in that direction.

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Also Read:

1.  Different Types of Debentures and Their Use

2.  Difference Between Convertible and Non-Convertible Debentures

3.  What are Pros and Cons of Investing in NBFC NCDs

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Ami Organics IPO Subscription Day-2

Ami Organics IPO Subscription Day-2
IPO
01/09/2021

The Rs.570 crore IPO of Ami Organics, consisting of Rs.200 crore fresh issue and Rs.370 crore OFS, had been fully subscribed on Day-1 itself. As per the combined bid details put out by the BSE, Ami Organics IPO was subscribed 3.90X overall at the end of Day-2, the bulk of the demand coming from the retail segment, but QIB and HNI book also got filled up. The issue closes for subscription on Friday, 03 September.

As of close of 02 September, out of the 65.42 lakh shares on offer, Ami Organics saw bids for 255.07 lakh shares. This implies an overall subscription of 3.90X. The granular break-up of subscriptions was tilted in favour of retail investors.

Ami Organics IPO Subscription Day-2
 

Category Subscription Status
Qualified Institutional (QIB) 1.43 Times
Non-Institutional (NII) 1.51 Times
Retail Individual 6.32 Times
Total 3.90 Times

 

QIB Portion

The QIB portion saw 1.43X subscription with demand for 26.43 lakh shares against 18.54 lakh shares available; net of anchor placement. On 31 August, Ami Organics did anchor placement of Rs.171 crore to QIB investors like SBI MF, Nippon MF, Malabar Fund, Kuber Fund, UTI MF, IIFL Asset Management, Elara India, Birla Sun Life, Kotak Life etc. 

HNI Portion

The HNI portion got subscribed 1.51X (getting applications for 21.18 lakh shares against the quota of 14.06 lakh shares). Funded applications and corporate applications, come in on last day, so a clearer picture will emerge on Friday.

Retail Individuals

The retail portion got subscribed 6.32X at the end of Day-2, showing strong retail appetite. Among retail investors; out of the 32.82 lakh shares on offer, valid bids were received for 207.47 lakh shares, of which bids for 157.96 lakh shares were at the cut-off price. 
The IPO is priced in the band of (Rs.603-Rs.610) and has allocated a quota of 35% for retail and 50% for QIBs.

 

Also Read: 

Upcoming IPOs in 2021

IPOs in September

7 Interesting Things to Know Before Investing in Ami Organics IPO

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Sansera Engineering IPO Allotment - How to Check the Allotment Status?

Sansera Engineering IPO Allotment
IPO
by 5paisa Research Team 01/09/2021

The Rs.1,282.98 crore IPO of Sansera Engineering, consisting entirely of an offer for sale (OFS), was subscribed 11.47X overall at the close of bidding on 16 September. The basis of allotment will be finalized on Tuesday, 21 September. If you have applied for the Sansera Engineering IPO, you can check your allotment status online.
 
You can either check your allotment status on the BSE website or the IPO registrar, Link Intime. Here are the steps.

Checking the allotment status of Sansera Engineering on BSE website

Visit the BSE link for the IPO allotment by clicking on the link below :

https://www.bseindia.com/investors/appli_check.aspx

Once you reach the page, here are the steps to follow.

1.  Under Issue Type – Select Equity Option
2.  Under Issue Name – Select Sansera Engineering from the drop down box
3.  Enter the Application Number exactly as in the acknowledge slip
4.  Enter the PAN (10-digit alphanumeric) number
5.  Once this is done, you need to click on the Captcha to verity that you are not a robot
6.  Finally click on the Search Button

The allotment status will be displayed on the screen in front of you informing about the number of shares of Sansera Engineering allotted to you.

Checking the allotment status of Sansera Engineering on Link Intime (Registrar to IPO)

Visit the Link Intime registrar website for IPO status by clicking on the link below:

https://linkintime.co.in/MIPO/Ipoallotment.html

This dropdown will only show the active IPOs, so once the allotment status is finalized, you can select Sansera Engineering from the drop down box.

There are 3 options:

1.  You can either access the allotment status based on PAN, Application Number or DPID-Client ID combination.

2.  Select the appropriate option you want to use and enter the details (PAN / Application Number / DPID-Client ID)

3.  Finally, click on the Search button.

The IPO status with number of shares of Sansera Engineering allotted will be displayed on the screen.


Frequently Asked Questions - 

Q. How do I check whether Sansera Engineering IPO is allotted to me or not?

A. You can check the IPO Allotment status using two ways - mentioned above. However you will also receive an email and SMS notification if you have got the shares allotted to your account or not.


Q. What if Sansera Engineering IPO is not allotted to me?

A. If Sansera Engineering IPO is not allotted to you, then -

1) In case of no-allotment or partial allotment, the money will be refunded to investors of the application money. Once applied for the IPO, then the bank blocks the amount in the account equal to bid size and the amount gets debited from the bank account after final allotment. 

2) Based on application status, the bank will initiate a full or partial refund which generally takes one or two days to receive the refund in your account. 


Q. When is the Sansera Engineering IPO Allotment expected?

A. Sansera Engineering IPO allotment is expected on 21st September 2021.


Q. When is Sansera Engineering IPO getting listed?

A. Sansera Engineering IPO is getting listed on 24th September 2021.


Q. How many times Sansera Engineering IPO was subscribed?

A. Sansera Engineering IPO was oversubscribed (11.47 times).

     Retailer - 3.15 times

     QIB - 26.47 times

     NII -11.37 times

Q. Where can I check the IPO Allotment status of Sansera Engineering IPO?

A. You can login to Linkintime Website OR on BSE India Website to check Sansera Engineering IPO. Above are the steps mentioned for both the websites.

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Why Should You Do Algo Trading?

Why Should You Do Algo Trading?
by 5paisa Research Team 02/09/2021

In Algo Trading, trades are made according to a set of predetermined rules. Trading instructions are stored in the trading software as algorithms, with variables such as time, volume, and price reference. The computer, on the other hand, executes the deal following the instructions supplied to it. As a result, Algo trading is extremely accurate, well-executed, well-timed, and free of most human mistakes. There are more benefits of Algo trading. Keep reading!

 

What are the benefits of Algo Trading?

1. More accuracy: Another important advantage of Algo Trading is that human interference is minimized. This means that the chances of making a mistake are much reduced. The algorithms are double-checked and triple-checked, and they are unaffected by human mistakes.

 

2. Expanded market volume: Algo Trading allows enormous numbers of shares to be purchased and sold in a matter of seconds. As a result, the market's total volume and liquidity grow, while the trading process becomes more systematic and simplified.

 

3. Diversification of trading: Algorithms and computers are used in algorithm trading. As a result, the process of executing several trades and strategies simultaneously becomes very simple.

 

4. Backtesting: The newly generated algorithms are initially backtested using historical data. This aids in determining whether or not the approach will work. The strategy may be changed and fine-tuned based on the backtest results to meet the trader’s needs.

 

5. Better speed: One of the most important benefits of algo trading is the increased speed it provides. The algorithms can assess a wide range of characteristics and technical indicators in a fraction of a second and execute trades instantly.

 

6. Execution of trade at best prices: Algorithmic trading allows huge volumes of trade to be executed in a short amount of time. Multiple deals are performed at a time, and transaction costs are decreased. With the help of algorithm strategies, trades are held at the best possible prices, which helps the traders make huge profits.

 

7. Consistency and discipline: It is widely acknowledged that the most challenging element of trading is planning the trade and trading the strategy. The unpredictability in the markets makes it difficult for traders to stick to their plans, even when they have developed methods. Algo trading addresses market volatility by assisting traders in being consistent and disciplined despite market ups and downs.

 

It depends on you, which algorithmic trading strategies you want to go for, where you want to use them, and how much you want to tailor it based on your needs. All of this, of course, should be in line with your ultimate trading objectives. For example, traders who want to reduce the risk of mechanical breakdowns may find a solution in server-based systems. However, before using algorithmic trading systems, keep in mind that you should have some trading expertise and understanding.

 

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What is Algo Trading?

What is Algo Trading?
by 5paisa Research Team 02/09/2021

Definition and Meaning of Algo Trading

Also known as ‘Black-box trading,’ Algorithmic trading involves the use of computer programs to place a trade based on predefined rules and principles. The computer program uses a set of instructions that helps make trading decisions and earns profits at a pace that would be difficult for a human trader to achieve. Algorithmic trading, in addition to giving profit opportunities for traders, makes markets more liquid and trading more systematic by eliminating the effect of human emotions on trading.

 

Origin of Algo Trading

17th-19th century

A high-frequency trader (HFT) utilizes cutting-edge technological advances to get information quicker than the competition and then execute his trading order faster than the competition. Surprisingly, the phenomena of rapid information distribution may be traced back to the 17th century. In the nineteenth century, Julius Reuter, the founder of Thomson Reuters, utilized a mix of technology including telegraph lines and a fleet of carrier pigeons to convey news.

 

Late 20th century

After computerized trading systems were introduced in American financial markets in the 1970s, the use of algorithms in trading grew. The Designated Order Turnaround (DOT) system was developed by the New York Stock Market in 1976 to route orders from traders to experts on the exchange floor. Michael Bloomberg founded Innovative Market Systems in 1983.

 

Early 21st century-present

In the early 21st century, electronic trading improved, and by 2009, computers had performed over 60% of all deals in the USA. Until 2010, HFT accounted for 56 percent of all stock trading in the USA. Nano trading technology was first introduced in 2011. Fixnetix created a microchip that can perform transactions in nanoseconds.

 

Advantages and Disadvantages of Algo Trading

Advantages of Algo Trading

Some of the advantages of algorithmic trading include:

 

1. Rule-based decision making: Traders and investors are frequently influenced by feelings and emotions and tend to trading techniques. Algorithms work to address this problem by guaranteeing that all trades follow a set of rules. Execution of the decisions occurs at the desired levels due to the quick and precise outcomes of computer programs.

 

2. Reduce market impact: Transaction costs are lower, and the predetermined rules help make automated checks on several market situations simultaneously. A trading algorithm can also purchase shares and check immediately to see if the transaction has influenced the market price.

 

3. Minimize human fallacy: As algorithmic trading works based on predefined instructions, there is less risk of making mistakes while placing transactions. This lowers the possibility of human traders making mistakes as a result of emotional or psychological factors.

 

Disadvantages of Algo Trading

Some of the disadvantages of algorithmic trading are:

 

1. Trades go unnoticed: A trading algorithm does not show any of the signs that the algorithm has been designed to search for. Thus, trading algorithms may lose out on trading deals. This problem can be resolved by simply increasing the number of indications that the algorithm should search for, but such a list can never be exhaustive.

 

2. Need for monitoring: While it would be ideal to switch on the computer and lay back for the day, automated trading systems do need constant supervision. An automated trading system may encounter irregularities that result in erroneous, missing, or duplicate orders. These incidents may be quickly detected and handled if the system is monitored.

 

Algorithm trading has taken over the work of manual trading in all parts of the world. It requires lesser human intervention and makes fewer mistakes. Even though it is a great tool for efficient trading, it should be used by experts and professionals only, as the mechanism may not be easy to grasp for amateurs.

 

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Who uses Algo Trading?

Who uses Algo Trading?
by 5paisa Research Team 02/09/2021

Institutional investors and large brokerage firms mostly utilize algorithmic trading to reduce trading expenses. Algorithmic trading is especially helpful for high order sizes, accounting for up to 10% of global trading activity. Algorithmic trading has gained popularity among both retail and institutional traders in the 21st century. It is popular among investment banks, pension funds, mutual funds, and hedge funds that need to stretch out the execution of a larger order or execute deals that are too quick for human traders to react to.

 

Other institutions that use algorithmic trading include:

● Investment funds

● Pension funds

● Credit unions

● Investment banks

● Insurance companies

● Trusts

● Prime brokers

 

Some examples of big institutions that use algorithm trading are Chicago Trading Company, Citadel LLC, Virtu Financial, Peet's Coffee and Tea, Optiver, Two Sigma Securities, Knight Capital, IMC Financial, ISP group, DRW, and Jump Trading.

 

What are the algorithm trading strategies used by big institutions?

Algo trading strategies that most of the traders use include:

 

1. Pairs trading: Also known as pair trading, it is a market-neutral technique that allows traders to benefit from short-term differences in the relative value of close substitutes. The law of one price cannot ensure price convergence in pairs trading. This especially applies while using the technique on individual equities.

2. Arbitrage: This approach is used by institutional investors who want to profit from small market price differences when a security's market price trades on two different exchanges. Three criteria must be satisfied for arbitrage to take place:

    ● First, on all markets, similar assets should not trade at the same price.

    ● Second, two assets with the same cash flows should not be purchased or sold simultaneously.

    ● Finally, an asset with a known future charge should not be traded using that pricing.

 

3. Delta-neutral strategies: Delta-neutral refers to a portfolio of linked financial assets in which the portfolio value is unaffected by minor changes in the underlying security's value. The positive and negative delta components of such a portfolio are generally offset, resulting in the portfolio's value being relatively insensitive to changes in the value of the underlying investment.

 

4. Mean Reversion: Mean reversion is a mathematical approach for investing in stocks that may also be applied to other activities. It is the process of determining a stock's trading range and then figuring the average price using analytical approaches pertaining to assets, earnings, and other factors.

 

5. Trend following: It is one of the most widely utilized algorithm-based trading methods. The goal of this strategy is to uncover patterns employed in the purchasing and selling process.

 

6. Scalping: This method is distinct from others. It is determined by the difference in bid and the security price. This approach will need a lot of money to deliver the expected outcomes. As a result of its complexity, it is handled by professionals. If you are new to investing, stay away from this approach until you have mastered the fundamentals of trade strategies.

 

Talking about how automated trading grew, Tom Debus, the Managing Partner for Cryptonomics Capital Ltd. has rightly pointed out that, “We have been expanding our automatic trading techniques in the crypto market over the past ten months to include more complicated signals. We can now adapt our algorithms to various market circumstances following successful backtesting and numerous iterations and modifications of the methods.”