Магнит БО-004Р-05

RU000A10A9Z1

Data on this page is shown in Russian.

Price

RUB 999.20

Yield

16.0%

Maturity

13.11.2029

Coupon

Variable

Coupon details

Amount

12.62

Accrued interest

8.41

Payments per year

12

Next coupon

31.08.2026

Bond details

Face value

RUB 1,000.00

Currency

rub

Subordinated

No

Amortization

No

Qualified investors

No

Issuer credit rating

—

Based on AI web search, not confirmed by an agency

AI signals

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AI analysis

Дюрация ~3.2 года, спред к ключевой ставке 14% составляет 2.01%. Переменный купон снижает процентный риск при текущей высокой ставке. Кредитный риск низкий - рейтинг AAA от Эксперт РА reflects наивысшую надёжность. Магнит - системный ритеёр с сильными现金流. Premium к номиналу всего 0.14% - дисконт почти нулевой, цена рисков минимальны. При ожидании снижения ключевой ставкиspread сжимается, что даёт потенциал роста цены. Субординированность отсутствует, статус - для всех инвесторов. Рекомендация BUY обоснована сочетанием низкой доходности, сильного кредитного профиля и умеренного процентного риска.

This analysis is generated by artificial intelligence and is not individual investment advice. Consult a licensed financial advisor before making an investment decision. Past results do not guarantee future returns.

What if?

future payout forecast
₽
RUB 10,000RUB 10,000,000
InvestedRUB 99,920100 pcs
You get backRUB 146,391
Net incomeRUB 46,471
MonthlyRUB 1,262
Annual yield 15.2%To maturity 3.1 yrs

FAQ

What is the yield to maturity of RU000A10A9Z1?

The yield to maturity (YTM) of the Магнит БО-004Р-05 bond is 16.0%.

When is the next coupon on RU000A10A9Z1?

The next coupon payment on the Магнит БО-004Р-05 bond is on 31.08.2026.

When does the RU000A10A9Z1 bond mature?

The maturity date of the Магнит БО-004Р-05 bond is 13.11.2029.

Algorithm

How BondScan works

Three stages: from hundreds of securities to a top 100 of reliable options in minutes.

🧹
1

Quick screening

We instantly remove securities with low liquidity, opaque terms and yield below the key rate.

⚖️
2

Deep analysis

The neural network compares the remaining securities: the issuer's financial health, credit quality and the yield-to-risk ratio.

🏆
3

Ranking

The best candidates are scored on three axes: reliability, yield, recommendation. The result is a ready top 100.

Performance

Proven effectiveness of the BondScan algorithm

Yield comparison: BondScan Top 100 vs the Moscow Exchange bond index (RGBITR)

BondScan Top 100
RGBITR (Moscow Exchange)
0%5%10%15%20%Jul 25OctJan 26AprJul 26+16.83%+10.1%+6.7pp
16.83%
Top 100 yield to maturity
+10.1%
RGBITR over the year (actual data)

The BondScan Top 100 offers a yield to maturity of 16.83%, which is 6.7 pp above the Moscow Exchange index (RGBITR, +10.1% over the year). The algorithm filters out hidden subordination risks and picks securities with the highest risk-adjusted premium to the key rate.

Problem

What does an investor face?

Information noise and Excel sheets

Hundreds of issues are traded on the market. To find worthwhile options you have to spend hours collecting data from different screeners, double-checking credit ratings by hand and merging everything into spreadsheets.

High coupon ≠ safety

Abnormally high yield often masks weak company finances or the status of a subordinated bond. A single default can wipe out a whole year of profit.

No time for deep analysis

Hundreds of securities on the market, each with its own financial health, ratings and payment schedules. Only an analyst can sort it out by hand.

Economics

Calculate the payback of BondScan for your capital

AI analysis of securities raises portfolio yield by 6.7 pp on average.

$11,765
Portfolio size
$1,176$58,824
$788
Additional income per year
thanks to AI analysis
$118
Annual subscription cost
≈ 1.0% of the portfolio
×6.7
Payback: extra income
exceeds the subscription 6.7 times

The subscription costs less than 1.0% of the portfolio. The extra income from BondScan ($788) exceeds the subscription by 6.7 times. BondScan pays for itself in the first month.

Full analysis on BondScan →