Syscoin koers (SYS)

Bitpanda Asset Management GmbH, Bitpanda GmbH

9845005X9B7N610K0093, 5493007WZ7IFULIL8G21

Syscoin

Syscoin utilizes a hybrid consensus mechanism that combines Proof of Work (PoW), Proof of Stake (PoS), and ZK-rollups to ensure security, scalability, and functionality. This unique architecture combines the security of Bitcoin’s PoW with Ethereum-compatible smart contracts, providing a decentralized and high-performance blockchain solution. Key Features of Syscoin's Consensus Mechanism: 1. Proof of Work (PoW) and Merged Mining with Bitcoin: Security with PoW: Syscoin leverages Bitcoin’s PoW consensus for securing the network, ensuring immutability and decentralization by having miners solve cryptographic puzzles to add new blocks. Merged Mining: Syscoin miners can also mine Bitcoin simultaneously, a process known as merged mining. This allows miners to secure both networks concurrently, benefiting from Bitcoin's established security while contributing to Syscoin’s blockchain. Block Production: Miners compete to solve complex cryptographic puzzles, adding blocks to the Syscoin blockchain. These blocks are validated through Syscoin’s PoW mechanism, ensuring the network's overall security and resistance to attacks. 2. Network-Enhanced Virtual Machine (NEVM): Smart Contracts and Ethereum Compatibility: Syscoin’s NEVM enables Ethereum-like smart contract functionality on Syscoin’s blockchain, allowing developers to build decentralized applications (dApps) that are compatible with the Ethereum ecosystem. Cross-Chain Compatibility: Syscoin's NEVM facilitates seamless interaction with Ethereum, giving users the ability to leverage Ethereum’s decentralized applications and services on Syscoin’s secure and scalable blockchain. 3. Layer 2 Scalability with ZK-Rollups: Scalability and Efficiency: Syscoin utilizes ZK-rollups to scale transaction throughput on the network, significantly increasing the number of transactions per second while maintaining security and decentralization. ZK-rollups allow off-chain transaction processing while ensuring data availability and finality on Syscoin’s Layer 1 blockchain. 4. Dual-Chain Layer 1 Architecture: UTXO-Based Blockchain: Syscoin’s native blockchain, using the Unspent Transaction Output (UTXO) model, ensures data availability and finality for transactions, providing the foundation for the network’s security and decentralization. Layer 1 and Layer 2 Integration: Syscoin’s dual-chain architecture separates the core security functions and scalability features, allowing the network to operate efficiently with high throughput while maintaining the security of Bitcoin’s PoW.

Syscoin employs a multifaceted incentive mechanism to ensure network security, scalability, and active participation. Incentive Mechanism: 1. Transaction Fees: Users pay transaction fees in Syscoin's native token, SYS, for activities such as transferring assets, minting tokens, and interacting with smart contracts. These fees compensate miners and sentry node operators for processing and validating transactions. 2. Masternodes: Holders of 100,000 SYS can operate masternodes, which support network infrastructure and provide services. Masternode operators receive rewards and seniority bonuses for their participation. 3. Governance Participation: SYS holders can propose and vote on network governance decisions. Each proposal requires a 250 SYS fee, which is burned upon submission. 4. Token and NFT Creation: Creating tokens or NFTs on the Syscoin platform requires burning SYS tokens, reducing the total supply and potentially increasing scarcity. Applicable Fees: Transaction Fees: Fees are paid in SYS tokens for various network activities, including asset transfers and smart contract interactions. Governance Proposal Fees: Submitting a governance proposal incurs a 250 SYS fee, which is burned to decrease the total supply. Token and NFT Creation Fees: Creating tokens or NFTs on the platform requires burning SYS tokens, with the amount varying based on the type and complexity of the asset.

2024-11-27

2025-11-27

2390802.01884 (kWh/a)

For the calculation of energy consumptions, the so called 'bottom-up' approach is being used. The nodes are considered to be the central factor for the energy consumption of the network. These assumptions are made on the basis of empirical findings through the use of public information sites, open-source crawlers and crawlers developed in-house. The main determinants for estimating the hardware used within the network are the requirements for operating the client software. The energy consumption of the hardware devices was measured in certified test laboratories. When calculating the energy consumption, we used - if available - the Functionally Fungible Group Digital Token Identifier (FFG DTI) to determine all implementations of the asset of question in scope and we update the mappings regulary, based on data of the Digital Token Identifier Foundation. The information regarding the hardware used and the number of participants in the network is based on assumptions that are verified with best effort using empirical data. In general, participants are assumed to be largely economically rational. As a precautionary principle, we make assumptions on the conservative side when in doubt, i.e. making higher estimates for the adverse impacts.

34.478147108 (%)

1.50925 (kWh)

0.00000 (tCO2e/a)

985.00102 (tCO2e/a)

0.62180 (kgCO2e)

To determine the proportion of renewable energy usage, the locations of the nodes are to be determined using public information sites, open-source crawlers and crawlers developed in-house. If no information is available on the geographic distribution of the nodes, reference networks are used which are comparable in terms of their incentivization structure and consensus mechanism. This geo-information is merged with public information from Our World in Data, see citation. The intensity is calculated as the marginal energy cost wrt. one more transaction. Ember (2025); Energy Institute - Statistical Review of World Energy (2024) - with major processing by Our World in Data. “Share of electricity generated by renewables - Ember and Energy Institute” [dataset]. Ember, “Yearly Electricity Data Europe”; Ember, “Yearly Electricity Data”; Energy Institute, “Statistical Review of World Energy” [original data]. Retrieved from https://ourworldindata.org/grapher/share-electricity-renewables.

To determine the GHG Emissions, the locations of the nodes are to be determined using public information sites, open-source crawlers and crawlers developed in-house. If no information is available on the geographic distribution of the nodes, reference networks are used which are comparable in terms of their incentivization structure and consensus mechanism. This geo-information is merged with public information from Our World in Data, see citation. The intensity is calculated as the marginal emission wrt. one more transaction. Ember (2025); Energy Institute - Statistical Review of World Energy (2024) - with major processing by Our World in Data. “Carbon intensity of electricity generation - Ember and Energy Institute” [dataset]. Ember, “Yearly Electricity Data Europe”; Ember, “Yearly Electricity Data”; Energy Institute, “Statistical Review of World Energy” [original data]. Retrieved from https://ourworldindata.org/grapher/carbon-intensity-electricity Licenced under CC BY 4.0.