View Past PerformanceSynopsys バランスシートの健全性財務の健全性 基準チェック /36Synopsysの総株主資本は$30.5B 、総負債は$10.0Bで、負債比率は32.9%となります。総資産と総負債はそれぞれ$47.2Bと$16.7Bです。 Synopsysの EBIT は$984.4Mで、利息カバレッジ比率2.9です。現金および短期投資は$2.2Bです。主要情報32.88%負債資本比率US$10.04b負債インタレスト・カバレッジ・レシオ2.9x現金US$2.20bエクイティUS$30.55b負債合計US$16.69b総資産US$47.24b財務の健全性に関する最新情報更新なしすべての更新を表示Recent updatesお知らせ • Apr 28Synopsys, Inc. to Report Q2, 2026 Results on May 27, 2026Synopsys, Inc. announced that they will report Q2, 2026 results at 4:00 PM, US Eastern Standard Time on May 27, 2026お知らせ • Apr 09Ultra Accelerator Link Consortium Publishes Four Specifications Defining In-Network Compute, Chiplets, Manageability and 200G PerformanceUltra Accelerator Link Consortium, the industry standards organization developing the open scale-up interconnect for next-generation AI workloads, announced the ratification of the next UALink Specification, which encompasses three major additions – In-Network Compute, Chiplet Definition, and Manageability. The new specifications support the deployment of UALink solutions in multi-workload environments, while simultaneously helping improve UALink technology efficiency, performance for AI workloads and ease of implementation. The UALink Consortium provides a standardized foundation for accelerator connectivity at scale, helping drive innovation, increase deployment flexibility and support the rapidly growing performance demands of next-generation AI workloads. The new specification update is facilitated through UALink Consortium’s open governance model, which fosters innovation while enabling a robust, multi-vendor supply chain, providing system designers and cloud providers with the necessary flexibility to deploy interoperable solutions without vendor lock-in. New UALink Specifications: UALink Common Specification 2.0 introduces In-Network Compute for UALink technology, facilitating computation and communication between accelerators. Reduces latency, saves bandwidth, and improves scaling efficiency for distributed training and inference for AI solutions for complex and multi-workload environments for UALink systems. UALink 200G Data Link and Physical Layers (DL/PL) Specification 2.0 split the DL/PL Specification from the UALink Common Specification to enable UALink to move quickly as new physical layers and speeds are needed by the industry without requiring changes to the other specifications. UALink Manageability Specification 1.0 introduces UALink as a system with centralized control and management planes. Utilizes standardized protocols, modeling and APIs like gNMI, Yang, SAI and Redfish. UALink Chiplet Specification 1.0 defines the necessary information to integrate UALink technology into chiplet-based SoCs, including interfaces, form factors, flow control and chiplet management standardization. Fully compliant with the UCIe 3.0 Specification for simplified integration into existing chiplet ecosystems. All of the UALink specifications are available for public download.お知らせ • Mar 30Synopsys, Inc. announced that it has received funding from Elliott Investment Management L.P.Synopsys, Inc announced a private placement to issue several billion dollars on March 28, 2026. The transaction included participation from new investor Elliott Investment Management L.P and issued common shares.お知らせ • Mar 12+ 1 more updateSynopsys Introduces Software-Defined Hardware-Assisted Verification to Enable Ai ProliferationSynopsys, Inc. announced advancements across its leading hardware-assisted verification (HAV) portfolio, including new hardware platforms and capabilities to support the ever-expanding demand for AI chip verification from the data center to the edge. Synopsys HAV platforms, powered by the company's unique software-defined capabilities, set new performance, scalability, and use case benchmarks for verifying the world's most sophisticated multi-die and AI chips amidst compounding design complexity and time-to-market requirements. AI chip verification complexity is escalating rapidly as large language models continue to double in size roughly every four months, and interface data rates advance at a 2x rate every three years. Simultaneously, edge AI architectures are driving aggressive throughput, latency, and power-efficiency targets that further expand the design and validation workload. To keep pace, the industry requires HAV solutions to support broader application coverage and run quadrillions of verification cycles, enabling first-time-right silicon and a seamless ability to integrate heterogeneous AI systems. The latest advancements across Synopsys' software-defined hardware-assisted verification portfolio, include: Breakthrough performance and capacity for the AI era: The latest software-defined updates and modular HAV are available across the ZeBu and HAPS platforms. Of note, with these updates, the industry's highest capacity-scalable emulation platform, ZeBu Server 5, supports complex designs to meet the demands of mega designs supporting data center AI training and inference, GPU, custom accelerators, and networking IPU/DPU workloads. Modular HAV for HAPS enables the largest prototypes for software development, with further improvements for compute, storage, and bring-up capabilities. New HAPS and ZeBu platforms: The new HAPS-200 12 FPGA and ZeBu-200 12 FPGA systems address the complexity and high-performance requirements for data center-sub-system, mobile, client, server, consumer, and edge AI applications. They deliver 2x higher capacity compared to previous 6 FPGA platforms utilizing the flagship AMD Versal™ Premium VP1902 adaptive SoCs, offering EP-Ready Hardware-enabled configurability between prototyping and emulation. Synopsys also introduces the new HAPS-200 1 FPGA platform as a desktop system ideal for IP verification and software bring-up using Synopsys Interface Prototyping Kits. Software-defined HAV capabilities extend system lifetime value: Continuous software improvements deliver compounding performance gains, increased debug productivity, as well as additional use case capabilities for both new and installed systems. The Synopsys HAV portfolio supports new, industry-first Hardware-Assisted Test Solutions, test automation capabilities that allow teams to stress corner cases for processor, memory, and I/O subsystems as well as full-system coherency validation and observe system behavior under realistic workloads in emulation long before silicon is ready. For mixed-signal and system-level designs, Real-Number Models (RNM) emulation enables fast, scalable abstraction of analog behavior within digital-centric verification flows for faster software bring-up. For safety-critical and high-reliability designs, new fault emulation capabilities enable scalable fault injection and analysis across RTL simulation, emulation, and prototyping.お知らせ • Mar 10Synopsys Launches Electronics Digital Twin Platform For Physical AI System DevelopmentSynopsys, Inc. launched the Synopsys Electronics Digital Twin (eDT) Platform, a first-of-its-kind, open solution to accelerate the creation, management, deployment, and use of electronics digital twins (eDTs) critical for software-defined product development enabling physical AI systems. The platform enables users to configure cloud-based eDT Labs, a collection of pre-integrated assets including Synopsys technologies, open-ecosystem tools, models, software, and scalable compute for high-value automotive use cases. The eDT Platform includes Synopsys and partner capabilities that can be used to establish eDT Labs such as Synopsys' virtualization and AI technologies, advanced debug, test tools, ecosystem integration, and blueprints to rapidly build and validate eDTs. System composition uses the open-source SIL Kit by Vector and Synopsys, enabling teams to rapidly assemble and connect virtual ECUs, models, and software components. A broad set of pre-integrated ecosystem partner technologies including silicon models; simulation, debug and analysis tools; and software IP; among others. eDT Labs can be deployed and managed easily using platform capabilities, including provisioning, role-based user management, secure access and encryption, administrative analytics, global license provisioning, and a workflow editor. User interfaces, applications, and APIs (CLI and TEST APIs) integrate with commercial and customer software factory solutions. Flexible compute options with SaaS or BYOC deployment options leverage flexible compute in the cloud, powered by AWS cloud infrastructure and AWS Graviton4 processors delivering computational performance and flexibility required for modern automotive development. The platform enables OEMs to achieve up to 90% of software validation prior to hardware availability by shifting software development and system integration "left," reducing vehicle development cost and time-to-market. The platform enables seamless collaboration between customer teams, suppliers and tool vendors to accelerate time to market. Integration in continuous integration/testing workflows with rapid provisioning of eDTs reduces validation effort while improving software quality.財務状況分析短期負債: SYNP03の 短期資産 ( $5.4B ) が 短期負債 ( $3.9B ) を超えています。長期負債: SYNP03の短期資産 ( $5.4B ) は 長期負債 ( $12.7B ) をカバーしていません。デット・ツー・エクイティの歴史と分析負債レベル: SYNP03の 純負債対資本比率 ( 25.7% ) は 満足できる 水準であると考えられます。負債の削減: SYNP03の負債対資本比率は、過去 5 年間で2.5%から32.9%に増加しました。債務返済能力: SYNP03の負債は 営業キャッシュフロー によって 十分にカバー されています ( 24.3% )。インタレストカバレッジ: SYNP03の負債に対する 利息支払い は EBIT ( 2.9 x coverage) によって 十分にカバーされていません。貸借対照表健全な企業の発掘7D1Y7D1Y7D1YSoftware 業界の健全な企業。View Dividend企業分析と財務データの現状データ最終更新日（UTC時間）企業分析2026/05/07 02:44終値2026/05/07 00:00収益2026/01/31年間収益2025/10/31データソース企業分析に使用したデータはS&P Global Market Intelligence LLC のものです。本レポートを作成するための分析モデルでは、以下のデータを使用しています。データは正規化されているため、ソースが利用可能になるまでに時間がかかる場合があります。パッケージデータタイムフレーム米国ソース例会社財務10年損益計算書キャッシュ・フロー計算書貸借対照表SECフォーム10-KSECフォーム10-Qアナリストのコンセンサス予想+プラス3年予想財務アナリストの目標株価アナリストリサーチレポートBlue Matrix市場価格30年株価配当、分割、措置ICEマーケットデータSECフォームS-1所有権10年トップ株主インサイダー取引SECフォーム4SECフォーム13Dマネジメント10年リーダーシップ・チーム取締役会SECフォーム10-KSECフォームDEF 14A主な進展10年会社からのお知らせSECフォーム8-K* 米国証券を対象とした例であり、非米国証券については、同等の規制書式および情報源を使用。特に断りのない限り、すべての財務データは1年ごとの期間に基づいていますが、四半期ごとに更新されます。これは、TTM（Trailing Twelve Month）またはLTM（Last Twelve Month）データとして知られています。詳細はこちら。分析モデルとスノーフレーク本レポートを生成するために使用した分析モデルの詳細は当社のGithubページでご覧いただけます。また、レポートの使用方法に関するガイドやYoutubeのチュートリアルも掲載しています。シンプリー・ウォールストリート分析モデルを設計・構築した世界トップクラスのチームについてご紹介します。業界およびセクターの指標私たちの業界とセクションの指標は、Simply Wall Stによって6時間ごとに計算されます。アナリスト筋Synopsys, Inc. 26 これらのアナリストのうち、弊社レポートのインプットとして使用した売上高または利益の予想を提出したのは、 。アナリストの投稿は一日中更新されます。35 アナリスト機関Joseph VruwinkBairdGary MobleyBenchmark CompanyNay Soe NaingBerenberg32 その他のアナリストを表示
お知らせ • Apr 28Synopsys, Inc. to Report Q2, 2026 Results on May 27, 2026Synopsys, Inc. announced that they will report Q2, 2026 results at 4:00 PM, US Eastern Standard Time on May 27, 2026
お知らせ • Apr 09Ultra Accelerator Link Consortium Publishes Four Specifications Defining In-Network Compute, Chiplets, Manageability and 200G PerformanceUltra Accelerator Link Consortium, the industry standards organization developing the open scale-up interconnect for next-generation AI workloads, announced the ratification of the next UALink Specification, which encompasses three major additions – In-Network Compute, Chiplet Definition, and Manageability. The new specifications support the deployment of UALink solutions in multi-workload environments, while simultaneously helping improve UALink technology efficiency, performance for AI workloads and ease of implementation. The UALink Consortium provides a standardized foundation for accelerator connectivity at scale, helping drive innovation, increase deployment flexibility and support the rapidly growing performance demands of next-generation AI workloads. The new specification update is facilitated through UALink Consortium’s open governance model, which fosters innovation while enabling a robust, multi-vendor supply chain, providing system designers and cloud providers with the necessary flexibility to deploy interoperable solutions without vendor lock-in. New UALink Specifications: UALink Common Specification 2.0 introduces In-Network Compute for UALink technology, facilitating computation and communication between accelerators. Reduces latency, saves bandwidth, and improves scaling efficiency for distributed training and inference for AI solutions for complex and multi-workload environments for UALink systems. UALink 200G Data Link and Physical Layers (DL/PL) Specification 2.0 split the DL/PL Specification from the UALink Common Specification to enable UALink to move quickly as new physical layers and speeds are needed by the industry without requiring changes to the other specifications. UALink Manageability Specification 1.0 introduces UALink as a system with centralized control and management planes. Utilizes standardized protocols, modeling and APIs like gNMI, Yang, SAI and Redfish. UALink Chiplet Specification 1.0 defines the necessary information to integrate UALink technology into chiplet-based SoCs, including interfaces, form factors, flow control and chiplet management standardization. Fully compliant with the UCIe 3.0 Specification for simplified integration into existing chiplet ecosystems. All of the UALink specifications are available for public download.
お知らせ • Mar 30Synopsys, Inc. announced that it has received funding from Elliott Investment Management L.P.Synopsys, Inc announced a private placement to issue several billion dollars on March 28, 2026. The transaction included participation from new investor Elliott Investment Management L.P and issued common shares.
お知らせ • Mar 12+ 1 more updateSynopsys Introduces Software-Defined Hardware-Assisted Verification to Enable Ai ProliferationSynopsys, Inc. announced advancements across its leading hardware-assisted verification (HAV) portfolio, including new hardware platforms and capabilities to support the ever-expanding demand for AI chip verification from the data center to the edge. Synopsys HAV platforms, powered by the company's unique software-defined capabilities, set new performance, scalability, and use case benchmarks for verifying the world's most sophisticated multi-die and AI chips amidst compounding design complexity and time-to-market requirements. AI chip verification complexity is escalating rapidly as large language models continue to double in size roughly every four months, and interface data rates advance at a 2x rate every three years. Simultaneously, edge AI architectures are driving aggressive throughput, latency, and power-efficiency targets that further expand the design and validation workload. To keep pace, the industry requires HAV solutions to support broader application coverage and run quadrillions of verification cycles, enabling first-time-right silicon and a seamless ability to integrate heterogeneous AI systems. The latest advancements across Synopsys' software-defined hardware-assisted verification portfolio, include: Breakthrough performance and capacity for the AI era: The latest software-defined updates and modular HAV are available across the ZeBu and HAPS platforms. Of note, with these updates, the industry's highest capacity-scalable emulation platform, ZeBu Server 5, supports complex designs to meet the demands of mega designs supporting data center AI training and inference, GPU, custom accelerators, and networking IPU/DPU workloads. Modular HAV for HAPS enables the largest prototypes for software development, with further improvements for compute, storage, and bring-up capabilities. New HAPS and ZeBu platforms: The new HAPS-200 12 FPGA and ZeBu-200 12 FPGA systems address the complexity and high-performance requirements for data center-sub-system, mobile, client, server, consumer, and edge AI applications. They deliver 2x higher capacity compared to previous 6 FPGA platforms utilizing the flagship AMD Versal™ Premium VP1902 adaptive SoCs, offering EP-Ready Hardware-enabled configurability between prototyping and emulation. Synopsys also introduces the new HAPS-200 1 FPGA platform as a desktop system ideal for IP verification and software bring-up using Synopsys Interface Prototyping Kits. Software-defined HAV capabilities extend system lifetime value: Continuous software improvements deliver compounding performance gains, increased debug productivity, as well as additional use case capabilities for both new and installed systems. The Synopsys HAV portfolio supports new, industry-first Hardware-Assisted Test Solutions, test automation capabilities that allow teams to stress corner cases for processor, memory, and I/O subsystems as well as full-system coherency validation and observe system behavior under realistic workloads in emulation long before silicon is ready. For mixed-signal and system-level designs, Real-Number Models (RNM) emulation enables fast, scalable abstraction of analog behavior within digital-centric verification flows for faster software bring-up. For safety-critical and high-reliability designs, new fault emulation capabilities enable scalable fault injection and analysis across RTL simulation, emulation, and prototyping.
お知らせ • Mar 10Synopsys Launches Electronics Digital Twin Platform For Physical AI System DevelopmentSynopsys, Inc. launched the Synopsys Electronics Digital Twin (eDT) Platform, a first-of-its-kind, open solution to accelerate the creation, management, deployment, and use of electronics digital twins (eDTs) critical for software-defined product development enabling physical AI systems. The platform enables users to configure cloud-based eDT Labs, a collection of pre-integrated assets including Synopsys technologies, open-ecosystem tools, models, software, and scalable compute for high-value automotive use cases. The eDT Platform includes Synopsys and partner capabilities that can be used to establish eDT Labs such as Synopsys' virtualization and AI technologies, advanced debug, test tools, ecosystem integration, and blueprints to rapidly build and validate eDTs. System composition uses the open-source SIL Kit by Vector and Synopsys, enabling teams to rapidly assemble and connect virtual ECUs, models, and software components. A broad set of pre-integrated ecosystem partner technologies including silicon models; simulation, debug and analysis tools; and software IP; among others. eDT Labs can be deployed and managed easily using platform capabilities, including provisioning, role-based user management, secure access and encryption, administrative analytics, global license provisioning, and a workflow editor. User interfaces, applications, and APIs (CLI and TEST APIs) integrate with commercial and customer software factory solutions. Flexible compute options with SaaS or BYOC deployment options leverage flexible compute in the cloud, powered by AWS cloud infrastructure and AWS Graviton4 processors delivering computational performance and flexibility required for modern automotive development. The platform enables OEMs to achieve up to 90% of software validation prior to hardware availability by shifting software development and system integration "left," reducing vehicle development cost and time-to-market. The platform enables seamless collaboration between customer teams, suppliers and tool vendors to accelerate time to market. Integration in continuous integration/testing workflows with rapid provisioning of eDTs reduces validation effort while improving software quality.