The "Stock Market Dataset for AI-Driven Prediction and Trading Strategy Optimization" is designed to simulate real-world stock market data for training and evaluating machine learning models. This dataset includes a combination of technical indicators, market metrics, sentiment scores, and macroeconomic factors, providing a comprehensive foundation for developing and testing AI models for stock price prediction and trading strategy optimization.

Key Features Market Metrics:

Open, High, Low, Close Prices: Daily stock price movement. Volume: Represents the trading activity during the day. Technical Indicators:

RSI (Relative Strength Index): A momentum oscillator to measure the speed and change of price movements. MACD (Moving Average Convergence Divergence): An indicator to reveal changes in strength, direction, momentum, and duration of a trend. Bollinger Bands: Upper and lower bands around a stock price to measure volatility. Sentiment Analysis:

Sentiment Score: Simulated sentiment derived from financial news and social media, ranging from -1 (negative) to 1 (positive). Macroeconomic Factors:

GDP Growth: Indicates the overall health and growth of the economy. Inflation Rate: Reflects changes in purchasing power and economic stability. Target Variable:

Buy/Sell Signal: Binary classification (1 = Buy, 0 = Sell) based on price movement thresholds, simulating actionable trading decisions. Use Cases AI Model Training: Ideal for building stock prediction models using LSTM, Gradient Boosting, Random Forest, etc. Trading Strategy Optimization: Enables testing of trading algorithms and strategies in a simulated environment. Sentiment Analysis Research: Useful for understanding how sentiment influences stock movements. Feature Engineering and Selection: Provides a diverse set of features for experimentation with advanced techniques like PCA and LDA. Dataset Highlights Synthetic Yet Realistic: Carefully designed to mimic real-world financial data trends and relationships. Comprehensive Coverage: Includes key indicators and metrics used by traders and analysts. Scalable: Suitable for use in both small-scale academic projects and larger AI-driven trading platforms. Accessible for All Levels: The intuitive structure ensures that even beginners can utilize this dataset for financial machine learning applications. File Format The dataset is provided in CSV format, where:

Rows represent individual trading days. Columns represent features (technical indicators, market metrics, etc.) and the target variable. Acknowledgments This dataset is synthetically generated and is intended for research and educational purposes. It is not based on real market data and should not be used for actual trading.

The main stock market index of United States, the US500, rose to 6818 points on December 2, 2025, gaining 0.08% from the previous session. Over the past month, the index has declined 0.50%, though it remains 12.70% higher than a year ago, according to trading on a contract for difference (CFD) that tracks this benchmark index from United States. United States Stock Market Index - values, historical data, forecasts and news - updated on December of 2025.

This dataset contains historical stock price data for Tesla, Inc. (TSLA) starting from its IPO date, June 29, 2010, to January 1, 2025. The dataset includes daily records of Tesla's stock performance on the NASDAQ stock exchange. It is ideal for time-series analysis, stock price prediction, and understanding the long-term performance of Tesla in the stock market.

The dataset consists of the following columns:

1. Date: The trading date.
2. Open: Opening stock price on the given date.
3. High: The highest stock price during the trading day.
4. Low: The lowest stock price during the trading day.
5. Close: The closing stock price for the day.
6. Adj Close: Adjusted closing price (corrected for dividends and stock splits).
7. Volume: The number of shares traded during the day.

Use Cases of Tesla Stock Historical Data

1. Time-Series Analysis

   • Analyze trends in Tesla's stock prices over time.
   • Identify seasonality, volatility, and long-term patterns in Tesla’s performance.

2. Stock Price Prediction

   • Develop predictive models to forecast future stock prices using techniques such as ARIMA, LSTMs, or regression.

3. Investment Strategy Evaluation

   • Backtest trading strategies by simulating trades based on historical price movements.
   • Analyze returns of investment strategies such as moving averages, RSI, or Bollinger Bands.

4. Market Sentiment Analysis

   • Correlate Tesla’s stock performance with news sentiment, earnings reports, and market events.

5. Portfolio Diversification

   • Evaluate Tesla’s performance compared to other stocks or indices to assess its role in a diversified portfolio.

6. Risk Management

   • Calculate volatility, beta, and other risk metrics to assess the risk associated with investing in Tesla stock.

7. Economic and Market Studies

   • Study how macroeconomic indicators (like inflation, interest rates) influence Tesla’s stock price.
   • Analyze Tesla’s performance during major economic events such as the COVID-19 pandemic or policy changes.

8. Stock Splits and Adjustments Analysis

   • Examine the impact of Tesla’s stock splits on price and trading volume.

9. Educational Purposes

   • Serve as a dataset for academic projects, coursework, or tutorials on financial data analysis.

10. Correlation with Sector Trends

    • Compare Tesla’s stock performance with other automotive or renewable energy companies.

11. Data Visualization and Dashboarding

    • Create dashboards using tools like Tableau, Power BI, or Python libraries to visualize Tesla’s stock performance metrics.

12. A/B Testing for Financial Applications

    • Use historical stock data for controlled experiments in finance-related applications to improve decision-making tools.

This stock market dataset is designed for financial analysis and predictive modeling. It includes historical stock prices, technical indicators, macroeconomic factors, and sentiment scores to help in developing and testing machine learning models for stock trend prediction.

Dataset Features: Column Description Stock Random stock ticker (AAPL, GOOG, etc.) Date Random business date Open Open price High High price Low Low price Close Close price Volume Trading volume SMA_10 10-day Simple Moving Average RSI Relative Strength Index (10-90 range) MACD MACD indicator (-5 to 5) Bollinger_Upper Upper Bollinger Band Bollinger_Lower Lower Bollinger Band GDP_Growth Random GDP growth rate (2.5% to 3.5%) Inflation_Rate Inflation rate (1.5% to 3.0%) Interest_Rate Interest rate (0.5% to 5.0%) Sentiment_Score Random sentiment score (-1 to 1) Next_Close Next day's closing price (for regression) Target Binary classification (1: Price Increase, 0: Price Decrease)

Key Features: Stock Prices: Open, High, Low, Close, and Volume data. Technical Indicators: Simple Moving Average (SMA), Relative Strength Index (RSI), MACD, and Bollinger Bands. Macroeconomic Factors: Simulated GDP growth, inflation rate, and interest rates. Sentiment Scores: Randomized sentiment values between -1 and 1 to simulate market sentiment. Target Variables: Next-day close price (for regression) and price movement direction (for classification).

Japan's main stock market index, the JP225, rose to 49553 points on December 2, 2025, gaining 0.51% from the previous session. Over the past month, the index has declined 3.78%, though it remains 26.25% higher than a year ago, according to trading on a contract for difference (CFD) that tracks this benchmark index from Japan. Japan Stock Market Index (JP225) - values, historical data, forecasts and news - updated on December of 2025.

View data of the S&P 500, an index of the stocks of 500 leading companies in the US economy, which provides a gauge of the U.S. equity market.

Gold fell to 4,199.97 USD/t.oz on December 2, 2025, down 0.75% from the previous day. Over the past month, Gold's price has risen 4.93%, and is up 58.92% compared to the same time last year, according to trading on a contract for difference (CFD) that tracks the benchmark market for this commodity. Gold - values, historical data, forecasts and news - updated on December of 2025.

Context

Microsoft is an American company that develops and distributes software and services such as: a search engine (Bing), cloud solutions and the computer operating system Windows.

Market cap

Market capitalization of Microsoft (MSFT)

Market cap: $3.085 Trillion USD

As of February 2025 Microsoft has a market cap of $3.085 Trillion USD. This makes Microsoft the world's 2nd most valuable company by market cap according to our data. The market capitalization, commonly called market cap, is the total market value of a publicly traded company's outstanding shares and is commonly used to measure how much a company is worth.

Revenue

Revenue for Microsoft (MSFT)
Revenue in 2024 (TTM): $254.19 Billion USD

According to Microsoft's latest financial reports the company's current revenue (TTM ) is $254.19 Billion USD. In 2023 the company made a revenue of $227.58 Billion USD an increase over the revenue in the year 2022 that were of $204.09 Billion USD. The revenue is the total amount of income that a company generates by the sale of goods or services. Unlike with the earnings no expenses are subtracted.

Earnings

Earnings for Microsoft (MSFT)
Earnings in 2024 (TTM): $110.77 Billion USD

According to Microsoft's latest financial reports the company's current earnings are $254.19 Billion USD. In 2023 the company made an earning of $101.21 Billion USD, an increase over its 2022 earnings that were of $82.58 Billion USD. The earnings displayed on this page are the earnings before interest and taxes or simply EBIT.

End of Day market cap according to different sources On Feb 2nd, 2025 the market cap of Microsoft was reported to be:

• $3.085 Trillion USD by Nasdaq

• $3.085 Trillion USD by CompaniesMarketCap

• $3.085 Trillion USD by Yahoo Finance

Content

Geography: USA

Time period: March 1986- February 2025

Unit of analysis: Microsoft Stock Data 2025

Variables

Acknowledgements

This dataset belongs to me. I’m sharing it here for free. You may do with it as you wish.

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Turkmenistan TM: External Debt: DOD: Stocks: Variable Rate data was reported at 143.055 USD mn in 2016. This records an increase from the previous number of 136.000 USD mn for 2015. Turkmenistan TM: External Debt: DOD: Stocks: Variable Rate data is updated yearly, averaging 110.903 USD mn from Dec 1970 (Median) to 2016, with 47 observations. The data reached an all-time high of 1.758 USD bn in 1999 and a record low of 0.000 USD mn in 1992. Turkmenistan TM: External Debt: DOD: Stocks: Variable Rate data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s Turkmenistan – Table TM.World Bank: External Debt: Debt Outstanding, Debt Ratio and Debt Service. Variable interest rate is long-term external debt with interest rates that float with movements in a key market rate; for example, the London interbank offered rate (LIBOR) or the U.S. prime rate. This item conveys information about the borrower's exposure to changes in international interest rates. Long-term external debt is defined as debt that has an original or extended maturity of more than one year and that is owed to nonresidents by residents of an economy and repayable in currency, goods, or services. Data are in current U.S. dollars.; ; World Bank, International Debt Statistics.; Sum;

Techsalerator offers an extensive dataset of End-of-Day Pricing Data for all 19 companies listed on the South Pacific Stock Exchange (XSPS) in Fiji. This dataset includes the closing prices of equities (stocks), bonds, and indices at the end of each trading session. End-of-day prices are vital pieces of market data that are widely used by investors, traders, and financial institutions to monitor the performance and value of these assets over time.

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Top 5 used data fields in the End-of-Day Pricing Dataset for Fiji :

1. Equity Closing Price :The closing price of individual company stocks at the end of the trading day.This field provides insights into the final price at which market participants were willing to buy or sell shares of a specific company.

2. Bond Closing Price: The closing price of various fixed-income securities, including government bonds, corporate bonds, and municipal bonds. Bond investors use this field to assess the current market value of their bond holdings.

3. Index Closing Price: The closing value of market indices, such as the Botswana stock market index, at the end of the trading day. These indices track the overall market performance and direction.

4. Equity Ticker Symbol: The unique symbol used to identify individual company stocks. Ticker symbols facilitate efficient trading and data retrieval.

5. Date of Closing Price: The specific trading day for which the closing price is provided. This date is essential for historical analysis and trend monitoring.

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Top 5 financial instruments with End-of-Day Pricing Data in Fiji:

South Pacific Stock Exchange (SPSE): The South Pacific Stock Exchange is the main stock exchange in Fiji. It facilitates the trading of shares of domestic companies and provides a platform for investors to participate in Fiji's capital markets.

Fijian Dollar (FJD): The Fijian Dollar is the official currency of Fiji. It is commonly abbreviated as FJD and is used for transactions within the country. The currency's value is influenced by economic conditions in Fiji and global factors.

Reserve Bank of Fiji (RBF): The central bank of Fiji responsible for formulating and implementing monetary policy, regulating financial institutions, and maintaining financial stability. The RBF's decisions impact interest rates, inflation, and overall economic conditions in Fiji.

Government Bonds: The Fijian government issues bonds to raise funds for various projects and operations. These bonds offer a fixed return to investors over a specified period. Government bonds are considered relatively safe investments and play a role in financing government activities.

Fiji National Provident Fund (FNPF): The FNPF is Fiji's national superannuation fund, providing retirement savings and social security services to Fijian citizens. It invests in various assets, including equities, bonds, and real estate, with the aim of generating returns for its members.

‍

If you're interested in accessing Techsalerator's End-of-Day Pricing Data for Fiji, please contact info@techsalerator.com with your specific requirements. Techsalerator will provide you with a customized quote based on the number of data fields and records you need. The dataset can be delivered within 24 hours, and ongoing access options can be discussed if needed.

‍

Data fields included:

Equity Ticker Symbol Equity Closing Price Bond Ticker Symbol Bond Closing Price Index Ticker Symbol Index Closing Price Date of Closing Price Equity Name Equity Volume Equity High Price Equity Low Price Equity Open Price Bond Name Bond Coupon Rate Bond Maturity Index Name Index Change Index Percent Change Exchange Currency Total Market Capitalization Dividend Yield Price-to-Earnings Ratio (P/E) ‍

Q&A:

1. How much does the End-of-Day Pricing Data cost in Fiji ?

The cost of this dataset may vary depending on factors such as the number of data fields, the frequency of updates, and the total records count. For precise pricing details, it is recommended to directly consult with a Techsalerator Data specialist.

1. How complete is the End-of-Day Pricing Data coverage in Fiji?

Techsalerator provides comprehensive coverage of End-of-Day Pricing Data for various financial instruments, including equities, bonds, and indices. Thedataset encompasses major companies and securities traded on Fiji exchanges.

1. How does Techsalerator collect this data?

Techsalerator collects End-of-Day Pricing Data from reliable sources, including stock exchanges, financial news outlets, and other market data providers. Data is carefully curated to ensure accuracy and reliability.

1. Can I select specific financial instruments or multiple countries with Techsalerator's End-of-Day Pricing Data?

Techsalerator offers the flexibility to select specific financial instruments, such as equities, bonds, or indices, depending on your needs. W...

Hong Kong's main stock market index, the HK50, rose to 26095 points on December 2, 2025, gaining 0.24% from the previous session. Over the past month, the index has declined 0.24%, though it remains 32.15% higher than a year ago, according to trading on a contract for difference (CFD) that tracks this benchmark index from Hong Kong. Hong Kong Stock Market Index (HK50) - values, historical data, forecasts and news - updated on December of 2025.

In March 2024 Bitcoin BTC reached a new all-time high with prices exceeding 73000 USD marking a milestone for the cryptocurrency market This surge was due to the approval of Bitcoin exchange-traded funds ETFs in the United States allowing investors to access Bitcoin without directly holding it This development increased Bitcoin’s credibility and brought fresh demand from institutional investors echoing previous price surges in 2021 when Tesla announced its 15 billion investment in Bitcoin and Coinbase was listed on the Nasdaq By the end of 2022 Bitcoin prices dropped sharply to 15000 USD following the collapse of cryptocurrency exchange FTX and its bankruptcy which caused a loss of confidence in the market By August 2024 Bitcoin rebounded to approximately 64178 USD but remained volatile due to inflation and interest rate hikes Unlike fiat currency like the US dollar Bitcoin’s supply is finite with 21 million coins as its maximum supply By September 2024 over 92 percent of Bitcoin had been mined Bitcoin’s value is tied to its scarcity and its mining process is regulated through halving events which cut the reward for mining every four years making it harder and more energy-intensive to mine The next halving event in 2024 will reduce the reward to 3125 BTC from its current 625 BTC The final Bitcoin is expected to be mined around 2140 The energy required to mine Bitcoin has led to criticisms about its environmental impact with estimates in 2021 suggesting that one Bitcoin transaction used as much energy as Argentina Bitcoin’s future price is difficult to predict due to the influence of large holders known as whales who own about 92 percent of all Bitcoin These whales can cause dramatic market swings by making large trades and many retail investors still dominate the market While institutional interest has grown it remains a small fraction compared to retail Bitcoin is vulnerable to external factors like regulatory changes and economic crises leading some to believe it is in a speculative bubble However others argue that Bitcoin is still in its early stages of adoption and will grow further as more institutions and governments recognize its potential as a hedge against inflation and a store of value 2024 has also seen the rise of Bitcoin Layer 2 technologies like the Lightning Network which improve scalability by enabling faster and cheaper transactions These innovations are crucial for Bitcoin’s wider adoption especially for day-to-day use and cross-border remittances At the same time central bank digital currencies CBDCs are gaining traction as several governments including China and the European Union have accelerated the development of their own state-controlled digital currencies while Bitcoin remains decentralized offering financial sovereignty for those who prefer independence from government control The rise of CBDCs is expected to increase interest in Bitcoin as a hedge against these centralized currencies Bitcoin’s journey in 2024 highlights its growing institutional acceptance alongside its inherent market volatility While the approval of Bitcoin ETFs has significantly boosted interest the market remains sensitive to events like exchange collapses and regulatory decisions With the limited supply of Bitcoin and improvements in its transaction efficiency it is expected to remain a key player in the financial world for years to come Whether Bitcoin is currently in a speculative bubble or on a sustainable path to greater adoption will ultimately be revealed over time.

Context

Tesla, Inc. is an American company that manufactures and sells electric cars, as well as power storage and photovoltaic systems. The company's goal is to “accelerate the transition to sustainable energy”. The company name is based on the physicist and inventor Nikola Tesla.

Market cap

Market capitalization of Tesla (TSLA)

Market cap: $1.082 Trillion USD

As of February 2025 Tesla has a market cap of $1.082 Trillion USD. This makes Tesla the world's 9th most valuable company by market cap according to our data. The market capitalization, commonly called market cap, is the total market value of a publicly traded company's outstanding shares and is commonly used to measure how much a company is worth.

Revenue

Revenue for Tesla (TSLA)

Revenue in 2024 (TTM): $97.69 Billion USD

According to Tesla's latest financial reports the company's current revenue (TTM ) is $97.69 Billion USD. an increase over the revenue in the year 2023 that were of $96.77 Billion USD. The revenue is the total amount of income that a company generates by the sale of goods or services. Unlike with the earnings no expenses are subtracted.

Earnings

Earnings for Tesla (TSLA)

Earnings in 2024 (TTM): $9.34 Billion USD

According to Tesla's latest financial reports the company's current earnings are $97.69 Billion USD. a decrease over its 2023 earnings that were of $10.12 Billion USD. The earnings displayed on this page are the earnings before interest and taxes or simply EBIT.

End of Day market cap according to different sources

On Feb 12th, 2025 the market cap of Tesla was reported to be:

• $1.082 Trillion USD by Yahoo Finance

• $1.082 Trillion USD by CompaniesMarketCap

• $1.082 Trillion USD by Nasdaq

Content

Geography: USA

Time period: June 2010- February 2025

Unit of analysis: Tesla Stock Data 2025

Variables

Acknowledgements

This dataset belongs to me. I’m sharing it here for free. You may do with it as you wish.

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United Kingdom's main stock market index, the GB100, fell to 9690 points on December 2, 2025, losing 0.13% from the previous session. Over the past month, the index has declined 0.12%, though it remains 15.91% higher than a year ago, according to trading on a contract for difference (CFD) that tracks this benchmark index from United Kingdom. United Kingdom Stock Market Index (GB100) - values, historical data, forecasts and news - updated on December of 2025.

China Bond Repurchase: Fixing Rate: Shanghai SE: (204007) 7 Day data was reported at 1.568 % pa in 16 May 2025. This records an increase from the previous number of 1.556 % pa for 15 May 2025. China Bond Repurchase: Fixing Rate: Shanghai SE: (204007) 7 Day data is updated daily, averaging 2.476 % pa from Jul 2016 (Median) to 16 May 2025, with 2137 observations. The data reached an all-time high of 9.264 % pa in 29 Dec 2017 and a record low of 1.414 % pa in 15 May 2020. China Bond Repurchase: Fixing Rate: Shanghai SE: (204007) 7 Day data remains active status in CEIC and is reported by Shanghai Stock Exchange. The data is categorized under China Premium Database’s Money Market, Interest Rate, Yield and Exchange Rate – Table CN.MR: Stock Exchange Bond Repurchase: Fixing Rate.

Israel's main stock market index, the TA-125, rose to 3538 points on December 2, 2025, gaining 1.75% from the previous session. Over the past month, the index has climbed 4.40% and is up 50.06% compared to the same time last year, according to trading on a contract for difference (CFD) that tracks this benchmark index from Israel. Israel Stock Market (TA-125) - values, historical data, forecasts and news - updated on December of 2025.

Italy's main stock market index, the IT40, rose to 43652 points on December 2, 2025, gaining 0.91% from the previous session. Over the past month, the index has climbed 0.99% and is up 29.04% compared to the same time last year, according to trading on a contract for difference (CFD) that tracks this benchmark index from Italy. Italy Stock Market Index (IT40) - values, historical data, forecasts and news - updated on December of 2025.

Lithuania LT: Foreign Direct Investment Position: Inward: USD: Total: OECD34 Fixed Composition data was reported at 15.926 USD bn in 2019. This records an increase from the previous number of 14.929 USD bn for 2018. Lithuania LT: Foreign Direct Investment Position: Inward: USD: Total: OECD34 Fixed Composition data is updated yearly, averaging 14.929 USD bn from Dec 2015 (Median) to 2019, with 5 observations. The data reached an all-time high of 15.926 USD bn in 2019 and a record low of 12.060 USD bn in 2015. Lithuania LT: Foreign Direct Investment Position: Inward: USD: Total: OECD34 Fixed Composition data remains active status in CEIC and is reported by Organisation for Economic Co-operation and Development. The data is categorized under Global Database’s Lithuania – Table LT.OECD.FDI: Foreign Direct Investment Position: USD: by Region and Country: OECD Member: Annual. Reverse investment: Netting of reverse investment in equity (when a direct investment enterprise acquires less than 10% equity ownership in its parent) and reverse investment in debt (when a direct investment enterprise extends a loan to its parent) is applied in the recording of total inward and outward FDI transactions and positions. Treatment of debt FDI transactions and positions between fellow enterprises: directional basis according to the residency of the ultimate controlling parent (extended directional principle).; Under the directional presentation , the direct investment flows and positions are organised according to the direction of the investment for the reporting economy-either outward or inward . So, for a particular country, all flows and positions of direct investors resident in that economy are shown under outward investment and all flows and positions for direct investment enterprises resident in that economy are shown under inward investment. The directional presentation reflects the direction of influence. For more details, see a complete note on ' Asset/liability versus directional presentation '; FDI financial flows are cross-border transactions between affiliated parties (direct investors, direct investment enterprises and/or fellow enterprises) recorded during the reference period (typically year or quarter). FDI positions represent the value of the stock of direct investments held at the end of the reference period (typically year or quarter). The change in direct investment positions from one period to the next is equal to the value of financial transactions recorded during the period plus other changes in prices, exchange rates, and volume. FDI income data are closely linked to the stocks of investments and are used for analysis of the productivity of the investment and calculation of the rate of return on the total funds invested. The main financial instrument components of FDI are equity and debt instruments. Equity includes common and preferred shares (exclusive of non-participating preference shares which should be included under debt), reserves, capital contributions and reinvestment of earnings. Dividends, distributed branch earnings, reinvested earnings and undistributed branch earnings are components of FDI income on equity . Reinvested earnings and reinvestment of earnings are separately identified components of equity in FDI income data and in FDI financial flows. Debt instruments include marketable securities such as bonds, debentures, commercial paper, promissory notes, non-participating preference shares and other tradable non-equity securities as well as loans, deposits, trade credit and other accounts payable/ receivable.The interest returns on the above instruments are included in FDI income on debt .; FDI transactions and positions by partner country and/or by industry are available excluding and including resident Special Purpose Entities (SPEs). The dataset 'FDI statistics by parner country and by industry - Summary' contains series including resident SPEs only. Valuation method used for listed inward and outward equity positions: Market value. Valuation method used for unlisted inward and outward equity positions: Own funds at book value. Valuation method used for inward and outward debt positions: Market and Nominal values. .

The benchmark interest rate in the United Kingdom was last recorded at 4 percent. This dataset provides - United Kingdom Interest Rate - actual values, historical data, forecast, chart, statistics, economic calendar and news.

Lithuania LT: Foreign Direct Investment Position: Inward: Total: World Not Allocated data was reported at 100.390 EUR mn in 2021. This records an increase from the previous number of 82.790 EUR mn for 2020. Lithuania LT: Foreign Direct Investment Position: Inward: Total: World Not Allocated data is updated yearly, averaging 84.870 EUR mn from Dec 2015 (Median) to 2021, with 7 observations. The data reached an all-time high of 102.390 EUR mn in 2017 and a record low of 70.180 EUR mn in 2015. Lithuania LT: Foreign Direct Investment Position: Inward: Total: World Not Allocated data remains active status in CEIC and is reported by Organisation for Economic Co-operation and Development. The data is categorized under Global Database’s Lithuania – Table LT.OECD.FDI: Foreign Direct Investment Position: by Region and Country: OECD Member: Annual. Reverse investment: Netting of reverse investment in equity (when a direct investment enterprise acquires less than 10% equity ownership in its parent) and reverse investment in debt (when a direct investment enterprise extends a loan to its parent) is applied in the recording of total inward and outward FDI transactions and positions. Treatment of debt FDI transactions and positions between fellow enterprises: directional basis according to the residency of the ultimate controlling parent (extended directional principle).; Under the directional presentation , the direct investment flows and positions are organised according to the direction of the investment for the reporting economy-either outward or inward . So, for a particular country, all flows and positions of direct investors resident in that economy are shown under outward investment and all flows and positions for direct investment enterprises resident in that economy are shown under inward investment. The directional presentation reflects the direction of influence. For more details, see a complete note on ' Asset/liability versus directional presentation '; FDI financial flows are cross-border transactions between affiliated parties (direct investors, direct investment enterprises and/or fellow enterprises) recorded during the reference period (typically year or quarter). FDI positions represent the value of the stock of direct investments held at the end of the reference period (typically year or quarter). The change in direct investment positions from one period to the next is equal to the value of financial transactions recorded during the period plus other changes in prices, exchange rates, and volume. FDI income data are closely linked to the stocks of investments and are used for analysis of the productivity of the investment and calculation of the rate of return on the total funds invested. The main financial instrument components of FDI are equity and debt instruments. Equity includes common and preferred shares (exclusive of non-participating preference shares which should be included under debt), reserves, capital contributions and reinvestment of earnings. Dividends, distributed branch earnings, reinvested earnings and undistributed branch earnings are components of FDI income on equity . Reinvested earnings and reinvestment of earnings are separately identified components of equity in FDI income data and in FDI financial flows. Debt instruments include marketable securities such as bonds, debentures, commercial paper, promissory notes, non-participating preference shares and other tradable non-equity securities as well as loans, deposits, trade credit and other accounts payable/ receivable.The interest returns on the above instruments are included in FDI income on debt .; FDI transactions and positions by partner country and/or by industry are available excluding and including resident Special Purpose Entities (SPEs). The dataset 'FDI statistics by parner country and by industry - Summary' contains series including resident SPEs only. Valuation method used for listed inward and outward equity positions: Market value. Valuation method used for unlisted inward and outward equity positions: Own funds at book value. Valuation method used for inward and outward debt positions: Market and Nominal values. .