[Generative AI x Asset Management] Beta version of “Lambda” portfolio management tool for individual investors released
*Novalis LLC*
Press release: September 18, 2024
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[Generative AI x Asset Management] Beta version of “Lambda” portfolio management tool for individual investors released
*Asset management support service that allows you to think for yourself through full-scale analysis*
* Novalis LLC (Chuo-ku, Tokyo, Representative: Shusuke Takamizawa) is a portfolio management tool for individual investors called Lambda. We are pleased to announce that we have released the beta version of “(Katakana notation: Lambda)”. *
Click here for details and to register for the beta version
* ■Background of “Lambda” development*
In recent years, with the launch of the new NISA system and the spread of small investment services, the hurdles for individuals to open a securities account and buy and sell financial products have gradually been lowered. However, investment activities involve not only buying and selling, but also a wide range of processes such as stock analysis, post-purchase monitoring, and periodic rebalancing before and after the purchase. For institutional investors, there are many tools that support this entire process, but for individual investors, there are fewer tools.
Currently, you are forced to choose between leaving the operation to a professional, or conducting research and analysis on your own*.
Based on this background, we developed Lambda as a tool that supports the entire process from stock analysis to rebalancing, so that individual investors can manage their assets in a way that satisfies them. Lambda helps individuals overcome the barriers of specialized knowledge they face when independently managing their assets, such as “financial terminology,” “complex risk/return calculations,” and “portfolio optimization methods,” helping them make better
investments. Provides information and analytics to help you make decisions. (*1)
■What you can do with “Lambda”
Function 1. Stock analysis
Lambda’s stock analysis functionality covers not only financial statements and competitor comparison data, but also time series data on dividends and dividend yields. Also,*
Management’s trading history* and institutional investors’ buying and selling trends* (only available for US-listed stocks) are also visualized, allowing you to analyze stocks from a more diverse perspective.
Stock analysis function using generated AI
Generation AI
We utilize generative AI that has learned based on financial statement data. In addition, we provide a wide range of information such as current stock prices, portfolios of famous investors, and company ratings from analysts.
Not only can you communicate via chat, but you can also see your data visually through interactive charts.
Function 2. Portfolio analysis
In addition to valuation gains/losses and asset allocation, Lambda’s portfolio analysis has been enhanced with visual support to help investors make better decisions.
Dividend analysis function
dividend
We calculate the expected yield and potential dividends based on the past dividend performance and future forecasts of the stocks we own. It is designed to visualize trends in the * yield of the entire portfolio * and to intuitively understand the growth of dividend income. (*2)
Risk analysis function 1. – Optimization model
risk
With charts that allow you to visually understand the effects of long-term investment and diversified investment, investors can proceed with asset management with a sense of satisfaction.
We have introduced the “Black-Litterman model,” which is an evolution of the conventional “efficient frontier” model. As a result, *
You can simulate* the optimal holding ratio according to your individual outlook and investment style. (*3)
Risk analysis function 2. – Principal loss probability simulation You can also simulate the *expected performance* and *probability of loss of principal* when an optimized portfolio is operated over the long term.
Investors can create strategies according to their risk tolerance and proceed with investment while understanding future returns and risks. (*4)
Return analysis function
return
You can analyze the return on your assets by factors such as price appreciation, dividends, and exchange rate fluctuations. (*5) In addition, we utilize the statistically based GARCH model to predict the volatility (range of price movements) of a portfolio* one week later*
I’m doing it. When markets become unstable and large fluctuations are expected, you can be better prepared for future trends. (*6) Click here for details and to register for the beta version
■Future outlook
– * Added a wide range of assets for analysis *
In the future, we aim to respond to the various needs of individual investors by supporting even more asset classes. Currently supported stocks and ETFs
In addition to (exchange traded funds), in the future * investment trusts, bonds, futures, virtual currencies *
We plan to gradually expand support for asset classes such as This allows users to consider a wider range of investment strategies, allowing them to further diversify their risks and optimize their portfolios.
– * Development of plans for corporations and educational institutions * We also plan to develop plans not only for individual investors, but also for companies and educational institutions. More investors and students will have access to advanced asset management tools based on financial engineering, helping them improve their financial literacy and acquire practical investment skills.
Novalis LLC
Representative: Shusuke Takamizawa
Head office location: 1-12-4 N&EBLD. 6F, Ginza, Chuo-ku, Tokyo https://lambdafinance.ai
*Disclaimer*
* *1. Disclaimer regarding investment risks*
Lambda and its analysis tools do not provide investment advice or recommendations, and investors are solely responsible for making final investment decisions. Please understand that the principal is not guaranteed and you may incur losses due to market fluctuations and the risks of the investment product itself.
* *2. About the Black Litterman model*
The Black-Litterman model is one way to optimize portfolios to reflect investors’ outlook, but it does not guarantee optimal results in all market environments. Additionally, the results are only an example and may not be optimal for all investors, as the outlook and parameters entered will affect the results.
* *3. Regarding dividend forecast*
Dividend forecasts are based on past data and market conditions, but do not accurately predict future dividend amounts. Dividend payments may change due to company performance and market fluctuations, and the predicted dividend amount is not guaranteed.
* *4. About long-term operation simulation*
Although long-term operation simulations are based on theoretical predictions, there is no guarantee that predicted results will be obtained due to actual market trends and external environments. There are many factors that are difficult to predict, such as economic uncertainty and global financial risks.
* *5. Exchange rate fluctuation risk*
Although “Lambda” provides return analysis that takes currency fluctuations into account, currency market trends are difficult to predict and may have a significant impact on investor returns. Particularly when investing in assets denominated in foreign currencies, currency risk must be carefully considered.
* *6. About volatility prediction*
Volatility prediction using the GARCH model is a method of estimating future volatility based on past data, but it does not provide accurate predictions in all market conditions. If the market experiences unexpected events or fluctuations, predicted results and actual volatility may differ.
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