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Purchase
Statistics Data
Provided
by Toshiba Data
Purchase statistics data is obtained from the Digital Receipt service developed by Toshiba Group, with its strength in point of sales (POS) systems. This service provides data such as “when, where, what, how much, and how many were purchased” in a manner that does not identify the retailer or purchaser. From changes in purchasing behavior, it can be used to predict the sales and business performance of the manufacturer.
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TSE Detail Breakdown
Trading Data by Issue
Detail Breakdown Trading Data comprises the daily trading value and volume (for regular trading sessions on the TSE market) of each TSE-listed issue, complied and fragmented into the cash transaction, margin transaction, and short selling categories. Investors enter such attribute information when placing orders, and thus, JPX Market Innovation & Research aggregates the flags and provides data on trading values and trading volumes.

Generally, the outstanding margin trading volume of each issue is announced weekly except for the issues subject to daily publication. However, using Detail Breakdown Trading Data allows for estimating the daily outstanding margin trading volumes for all issues.
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TONA Averages
& TONA Index
TONA Averages and TONA Index are the benchmarks published by the Bank of Japan that are calculated by compounding the uncollateralized overnight call rate. TONA is one of the alternative interest rates to the Japanese Yen LIBOR. However, when used as the substitute, it must be compounded using the daily TONA. Through the use of TONA Averages and TONA Index, market participants can share the daily compounded TONA levels and reduce the burden involved in calculation and reconciliation.

TONA Averages
Interest rates derived from the daily compounded TONA for the period starting exactly 30 days, 90 days, and 180 days prior to the reference date of the benchmark (each business day) until the reference date

TONA Index
Asset valuation on the reference date assuming the asset is managed using TONA, with 100 as of June 14, 2017 (the date on which the Bank of Japan established “Uncollateralized Overnight Call Rate Code of Conduct”)
*By specifying the start and end dates, the interest rate compounded by TONA for any given period can be calculated from the historical data of the TONA Index.
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Tokyo Term Risk
Free Rate (TORF)
Tokyo Term Risk Free Rate (TORF) is a Japanese yen short-term interest rate calculated and published by QUICK Benchmarks Inc. (QBS). TORF is one of the alternative benchmarks to replace the London Interbank Offered Rate (LIBOR), and is designated as a “Specified Financial Benchmark” stipulated by the Financial Instruments and Exchange Act.

It is calculated based on the data of derivative transactions whose underlying asset is the “uncollateralized overnight call rate,” which contains almost no credit risk of financial institutions. Like other interest rate benchmarks such as LIBOR, TORF has a feature in that the rate is fixed as of the start of the interest rate calculation period.

Today, it is widely used by financial institutions around the world as the base interest rate for loans with Japanese yen interest rates and derivatives transactions.

For more information, please see below.
https://corporate.quick.co.jp/en/torf

* Use of TORF requires a license agreement with QUICK.
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QUICK
Equity Risk Premium
QUICK Equity Risk Premium is a service that provides the cost of shareholder’s equity calculated by QUICK (QUICK Cost of Shareholders’ Equity), as well as various parameters necessary for calculating factor models.
The QUICK Cost of Shareholders’ Equity is calculated backward from the market stock prices by combining a stock valuation model (discounted residual income model) and the factor models (the Fama-French 3-factor model, and the QUICK 4-factor model with the addition of an insolvency risk factor). This data can be used to confirm the level of shareholder’s equity costs of listed companies, calculate WACC, and evaluate whether stock prices are overvalued or undervalued.
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TV Metadata
1: TV Program Data /
2: TV-CM (Advertising) Data
TV Metadata is a dataset that 24/7 TV broadcasts (programs and TV-CMs) convert into text and databases.
This data indicates when, where, what, how, and how many seconds were broadcast. You can aggregate broadcast volume and content by brands.
By observing the amount of marketing activity of companies, it is possible to use it as an alternative data as a leading indicator of stock prices and an upward signal, and it can be indexed as a TV index by aggregating the broadcast volume of each brand in TV metadata by time series change. With TV information that affects sentiment, it is possible to discover stocks and make investment decisions from various perspectives, and it is also possible to create new indicators in combination with other data.
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Nikkei
Earnings Summary
This service offers English earnings summary in a news format. The Japanese news source for this service is automatically generated based on the timely disclosure information of listed companies.

Readability:
In the process of translating Japanese news, the conversion process is performed based on the sentence structure. This helps to maintain readability despite being a machine translation.

Earnings revision:
As well as earnings announcements, earnings revisions are also updated.

Related infomation:
In addition to the summary of the announcement, the news also provides the average of analysts' earnings forecasts (QUICK Consensus) and company forecasts.
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Honda
Drive Data Service
(Customer Index)
This data set represents visiting information to parking lot associated with the stocks (retail or BtoB company), and that is calculated using the driving data of Honda car users who have given consent. Since the sampling frequency of the original data is high, it is possible to grasp the time spent in seconds. it is possible to grasp the change in the average stay time even though the offering data set is statistically processed. It would be very helpful information not only for predicting the increase/decrease in the number of customers from the number of visiting vehicles, but also for predicting the increase/decrease in the customer unit price.
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I Know First Stock
Forecast Based On a
Predictive Algorithm
I Know First is a fintech company that provides state of the art self-learning, AI based algorithmic forecasting solutions for the capital markets to uncover the best investment opportunities.
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