HMT Quantum Capital LLC

Quantum Capital

私達は、金融市場における自動取引システム開発並びに株主と社員の自己資金を運用する Proprietary trading company です。投資の勧誘や金融商品の販売等の活動は一切行っておりません。

We are a proprietary trading company developing automated trading systems for financial markets and managing the proprietary funds of shareholders and employees. The company does not solicit investments or sell financial products.

Quants strategy

クオンツは、数値データをまとめた定量分析です。昨今、ビッグデータを扱うソリューションの数が増えていることは言うまでもありませんが、より広範な市場データへのアクセスが拡大し、自動化を中心に技術革新の増加により、クオンツの成長が促進されました。定量的戦略は、使用するアルゴリズムの機密性が高いため、ブラック ボックスと呼ばれることがよくあります。クオンツのプログラミングとクオンツアルゴリズムには、経済データポイントからトレンドのグローバル指数やリアルタイムの企業ニュースに至るまで、数々の要素があります。その結果、高度なソフトウェアプログラムを通じて開発された独自のアルゴリズムを使用して、勢い、品質、価値、財務力に関する洗練されたモデルを構築することが可能になります。

Quant is a method of quantitative analysis that summarizes numerical data. Many solutions built around big data have become popular recently, but the growth of quantitative methods has accelerated particularly fast, with access to broader market data and increased technological innovation, especially around automation. Quantitative strategies are often referred to as black boxes, because of the sensitive nature of the algorithms. There are numerous elements to quant programming and quant algorithms, from economic data points to trending global indices and timely company news. This leads to building sophisticated models around momentum, quality, value, and financial strength using proprietary algorithms developed through sophisticated software programs.

クオンツは、主に歴史的な出来事に基づいており、過去が常に未来に繰り返されるとは限らないため、失敗する可能性もあります。強力なクオンツ チームは常にモデルに新しい側面を追加して将来の出来事を予測しますが、毎回未来を予測することは不可能です。しかし、我々はクオンツを利用し、インプットとコンピュータープログラムを使用して投資を選択することで、リスクと損失を削減するのに役立つと考えています。

Quants are based on major historical events, assessing the possibility of failure since history does not always repeat itself. A strong quant team can add new aspects to the models to predict future events, although precisely predicting all future events is impossible. Therefore, risk mitigation is important, via the selection of investments using quantitative methods from various inputs and computer programs.

High speed rotary trading


In recent years, the speed of financial markets has increased due to competition. Hedge funds and asset management companies are demanding enhanced liquidity and trading speed as the most important factors, even more important that system cost. Fast turnover does not require actual corporate financial data, but only empirical results to compare price formation patterns, as it is difficult to discuss the aggressively changing financial market systems since many factors influence price formation.


A general automated trading system development procedure adopts a hypothetical valuation from previous periods, which is used as a trading model by the developers to manually adapt the parameters, filter, and tune (adjust) systems to finally create the most suitable method for investment, strategy, and tactical allocations. Once this method is backtested, the trading strategy is then widely used. However, this method does not consider the myriad of possibilities such as inadequate factors of behavioral judgment, other algorithms, position and order status, etc. This leads to limiting the reproducibility and the approach of general automated trading systems.


To improve upon the limitations of automated trading systems, the analysis of the market conditions, market behavior, and the evaluation of the value criteria and methods behind the investors (or traders) choices, we use market behavior data and event data. By learning from this event-specific data set, effective trading strategies can be constructed in response to actual market changes.
The timing of order placement is important for mainstream trading strategies, which revolve around the predicted value of the investors strategies. The automated trading system developed considers the market environment (time segmentation), the state of the market, and the limit strategy that can predict the order change of the bid-ask, the timing and amount of changes, the spread, and noise to achieve the goal of obtaining a profit.

About us


We are a company developing and self-managing proprietary algorithms and machine learning tools, as well as financial market trading systems. The company does not solicit or sell investment services.


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