✉️White paper

1.0 Project Background

1.1 Financial Landscape in the Post-Pandemic Era

In 2022, there were frequent black swan events, severely impacting risk investments such as cryptocurrencies and technology stocks.

On June 6th, the World Bank released its latest Global Economic Prospects report, raising the global economic growth forecast for 2023 from 1.7% in January to 2.1%. This revision was driven by better-than-expected resilience in major economies. However, the forecast for global growth in 2024 was revised down from 2.7% in January to 2.4% due to the drag from tightening monetary policies. The forecast for global growth in 2025 stands at 3.0%.

Regarding growth expectations in the East Asia and Pacific (EAP) region, excluding China, the report projects a slowdown from 5.8% in 2022 to 4.8% in 2023, as the boost from the early reopening of several large economies diminishes. Regional trade growth will remain subdued due to weak global demand and China's domestically driven growth. By 2024, with the fading impact of China's reopening, EAP's growth rate is expected to slow to 4.6%.

The Federal Reserve raised interest rates for the tenth consecutive time. In May, the Fed announced a 25 basis points increase, corresponding to a rise of 0.25%. Since March 2022, the Fed has put an end to the four-year era of near-zero interest rates, initiating a tightening cycle and continuously raising rates for over a year. The latest rate hike brought the federal funds rate to a range of 5.00%-5.25%, the highest level since 2007.

China's economic growth has slowed down, leading major banks to adjust the benchmark deposit rates for the Chinese yuan. In the fund investment market, 23.29% of wealth management products had negative returns in 2022. The public fund sector experienced an even larger loss, with 67.08% of funds delivering negative returns in 2022. However, some funds achieved returns exceeding 20% despite the adverse market conditions in 2022. In terms of return distribution, the majority of wealth management products had returns ranging from 0% to 3% (including 3%), accounting for 47.89% of products. Products with returns between 3% and 5% (including 5%) represented 24.8%, while those with returns exceeding 5% accounted for only 2.98% of the total.

1.2 Risks of Traditional Quantitative Investing

This means that the accuracy of investment models and strategies is premised on the stability of the conditions on which these patterns and trends rely. However, when these conditions change, more complex models are more prone to failure. From the Asian financial crisis in 1997 to the subprime mortgage crisis in 2008, and now the COVID-19 crisis in 2020, the first financial institutions to collapse were often those heavily leveraged and engaged in quantitative hedge funds. The reason behind this is that investment methods reliant on models, historical data, and algorithmic trading are more vulnerable in the face of sudden external shocks.

1.2.1 Risks of Data Traps

Traditional investment methods have subjective characteristics as they are based on investors' judgments of certain phenomena. Therefore, investors are easily influenced by emotional fluctuations, which can prevent investment transactions from achieving objective and accurate outcomes. In contrast, quantitative investing eliminates individual emotions and extracts and separates investment value from data. It constructs models for analysis and makes decisions based on the results, aiming for consistent and stable non-random returns. Constructing quantitative models is based on the premise that historical patterns will repeat. However, data is not entirely secure and may also pose risks. In the era of big data, investors may be surrounded by data and unable to judge the true validity of the data. Modeling and analyzing flawed data may lead to conclusions that do not align with the real market environment. For example, when the sample of a statistical model changes, it may result in incorrect conclusions that are not applicable to trading decisions.

1.2.2 Risks of System Failures

The risks of system failures in quantitative investment strategies mainly involve four aspects:

(1) Network issues or hardware failures that affect the effectiveness of quantitative investments.

(2) Inadequate consideration of capital allocation and position sizing during the design of the model, leading to a mismatch between positions and funds and potentially causing margin calls.

(3) The current trading systems lack unified standard certification and are mostly individually designed by different institutions without thorough pre-investment testing, resulting in system vulnerabilities and security issues.

(4) Delay issues in exchange processing systems, where additional resources are consumed when the trading mechanism validates orders.

1.2.3 Risks of Market Manipulation

Currently, institutional investors, who often adopt quantitative investment strategies, dominate the traditional capital markets. These institutional investors have substantial funds and higher levels of expertise, which can to some extent contribute to market volatility. However, the majority of participants in China's capital market are individual investors, namely retail investors, who generally lack substantial financial resources, professional knowledge, and technical analysis skills. Only a small portion of them apply quantitative investment strategies in their trading activities. From this perspective, there are risks of market manipulation associated with quantitative investment strategies.

2.0 Product Introduction

As a cooperative brokerage of the world's largest cryptocurrency exchange, SCU offers a compliant product known as quantitative trading to help ordinary small and medium-sized users tap into the funds of irrational investors in the currency market. By using SCU's quantitative trading strategy, users can profit without the need to deposit their own capital, but instead pay a monthly membership fee within a certain range.

2.1 Easy Operation

With SCU, users simply need to follow the product user guide, bind their Binance account's API to the platform, and activate SCU's VIP membership to enjoy quantitative services. No further actions are required, and users can experience daily profit growth provided by SCU.

2.2 Financial Security

2.2.1 SCU implements a non-capital deposit model, distinguishing itself from traditional investment platforms.

As an advanced quantitative trading system operating on the Binance smart contract, SCU upholds a strict separation of user funds. We prioritize the security and integrity of our users' assets by ensuring that SCU does not directly handle or access their funds. Instead, users' capital remains securely stored within their own Binance accounts, granting SCU limited permissions for reading, executing trades, managing contracts, and facilitating transfers within the user's account. This stringent design guarantees that SCU cannot initiate withdrawals or unauthorized transfers, providing users with a peace of mind and full control over their funds. Furthermore, users retain the flexibility to revoke SCU's access privileges at their discretion, placing them in complete control of their assets at all times.

2.2.2 At SCU, we maintain a highly sophisticated and proactive risk management framework.

Far surpassing the traditional reactive risk control systems commonly found in the asset management industry, SCU has established an advanced "predictive + reactive" approach to risk management. Leveraging cutting-edge technologies such as artificial intelligence, machine learning, big data analytics, and cloud computing, our system possesses an unparalleled ability to proactively observe, analyze, and forecast market fluctuations and their associated risk implications. This foresight enables us to stay ahead of potential risks, employing timely and appropriate measures to mitigate their impact. By leveraging our expertise and harnessing the power of information technology, SCU empowers users with a robust risk management infrastructure that instills confidence and security in their investment activities.

Through these measures, SCU has positioned itself as a premier and sophisticated platform, ensuring the highest level of fund security for our esteemed users.

2.3 Product advantages

To achieve fast and stable buy and sell transactions, SCU combines and operates multiple strategy trading models.

✔ Grid Strategy: A powerful tool for range-bound markets, it reduces holding costs and seeks excess returns. By employing the trading patterns of grid robots, it mitigates the emotional impact on regular traders.

✔ CTA Strategy: Dynamic and trend-following. It tracks market trends in real-time, navigating through bull and bear markets to consistently generate steady profits.

✔ Arbitrage Strategy: Capitalizing on information gaps, user disparities, and differences in prices, exchange mechanisms, and trading mechanisms among global cryptocurrency exchanges, it creates opportunities for arbitrage strategies. By leveraging price disparities in the market, it engages in risk-free arbitrage, buying low and selling high.Drawing inspiration from classical trading models in traditional exchanges, SCU injects more profit drivers into cryptocurrency quantification:

✔ MACD: Real-time tracking of MACD trend signals, going long on golden crosses and short on death crosses. Suitable for slowly changing market trends.

✔ MACD-RSI: Combining MACD with RSI, it effectively evaluates market trends and accurately captures trading opportunities.

✔ Dual Moving Averages: Real-time tracking of moving average trend signals, going long on golden crosses and short on death crosses. Suitable for slowly changing market trends.

✔ Dual Moving Averages-RSI: Combining dual moving averages with RSI, it effectively evaluates future market trends and accurately captures trading opportunities.

Multiple indicator combinations, freely adjustable parameters: Including over ten common indicators, allowing for the flexible configuration of multiple indicators for entry and exit conditions. Parameters can be individually set.

As a trusted partner of Binance, SCU operates as a brokerage platform. Users authorize SCU through Binance API interfaces, granting access to "asset query" and "order placement" interfaces, enabling traders to execute operations and trades on Binance International.

2.4 Reasonable Fees

SCU adopts a low entry threshold for users, as their own Binance account only requires a small initial capital to access SCU's services. Users can choose different levels of membership services based on their own quantitative capital. The higher the membership level, the higher the price, the larger the amount of funds that can be quantified, and the higher the cost-effectiveness.