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QI Investment uses Machine Learning to generate short-term trading signals that can be delivered via custom API. For more information please contact us directly.
Machine learning is a field of artificial intelligence that uses algorithms to learn from data and improve itself over time without being explicitly programmed. The goal is to create algorithms that are able to identify patterns, trends, and relationships from data, then use those patterns to make predictions.
The basic premise of supervised machine learning is to use a dataset of inputs and corresponding known outputs in order to train an algorithm to accurately predict outputs for new, unseen inputs. This allows computers to autonomously “learn” how to make decisions and solve problems. It is commonly used in applications including classification, regression, and probabilistic modeling.
Unsupervised machine learning is a class of algorithms that allows computers to learn without being explicitly programmed or supervised. Unsupervised learning algorithms are used to find patterns and relationships within a given data set without labels or assistance from humans. The goal of unsupervised learning is to identify the structure and relationships that exist within the data. Examples of unsupervised learning include clustering, association rule learning, and anomaly detection.
Neural networks are sets of algorithms, modeled loosely after the human brain, which are designed to recognize patterns. They usually involve multiple, sequentially arranged layers giving them more depth compared to more traditional Machine Learning, which is why they are classified as Deep Learning algorithms. Neural networks are used to model complex relationships between inputs and outputs and find patterns in data.
Recurrent neural networks (RNNs) are a type of artificial neural networks that are commonly used for time series or sequential data. Unlike more traditional neural networks, RNNs are better adapted in processing and learning from the sequential nature of the data. This allows RNNs to analyze and recognize patterns in data over time, which can be useful for speech and image recognition, natural language processing and financial time series.
QI Investment uses Machine Learning, to generate short- to medium term trading signals and to find hidden structures in related datasets. The signals are used in funds advised by QI Investment and can also be accessed in a more individual form through managed account solutions. As a professional or institutional please feel free to reach out for more information about access to our solutions.
QI Investment uses signals created through Machine Learning techniques. For a direct API access to custom signals please feel free to reach out for more information.
Machine learning is a field of artificial intelligence that uses algorithms to learn from data and improve itself over time without being explicitly programmed. The goal is to create algorithms that are able to identify patterns, trends, and relationships from data, then use those patterns to make predictions.
The basic premise of supervised machine learning is to use a dataset of inputs and corresponding known outputs in order to train an algorithm to accurately predict outputs for new, unseen inputs. This allows computers to autonomously “learn” how to make decisions and solve problems. It is commonly used in applications including classification, regression, and probabilistic modeling.
Unsupervised machine learning is a class of algorithms that allows computers to learn without being explicitly programmed or supervised. Unsupervised learning algorithms are used to find patterns and relationships within a given data set without labels or assistance from humans. The goal of unsupervised learning is to identify the structure and relationships that exist within the data. Examples of unsupervised learning include clustering, association rule learning, and anomaly detection.
Neural networks are sets of algorithms, modeled loosely after the human brain, which are designed to recognize patterns. They usually involve multiple, sequentially arranged layers giving them more depth compared to more traditional Machine Learning, which is why they are classified as Deep Learning algorithms. Neural networks are used to model complex relationships between inputs and outputs and find patterns in data.
Recurrent neural networks (RNNs) are a type of artificial neural networks that are commonly used for time series or sequential data. Unlike more traditional neural networks, RNNs are better adapted in processing and learning from the sequential nature of the data. This allows RNNs to analyze and recognize patterns in data over time, which can be useful for speech and image recognition, natural language processing and financial time series.
QI Investment uses Machine Learning, to generate short- to medium term trading signals and to find hidden structures in related datasets. The signals are used in funds advised by QI Investment and can also be accessed in a more individual form through managed account solutions. As a professional or institutional please feel free to reach out for more information about access to our solutions.
QI Investment uses signals created through Machine Learning techniques. For a direct API access to custom signals please feel free to reach out for more information.
Machine learning in investment management is the use of Machine Learning and predictive analytics to identify and optimize investment decisions. Machine Learning is about inferring rules governing the data, which is the distinctive feature compared to more classic approaches that apply a predefined set of rules to the data set.
Using Machine Learning techniques provides a number of benefits, including increased accuracy in predicting stock price movements, improved risk identification and management, increased data-driven decision-making, and more efficient operations.
Typically, the data used for Machine Learning is data related to assets and investment products, including stock prices and volumes, currency exchange rates, macroeconomic indicators, and company-specific financial information.
Machine Learning algorithms can help investors identify trends in the market, spot opportunities, and make more informed decisions. It also contributes to reducing risk by making it easier to detect fraud and other suspicious activities.
The primary challenge for implementing Machine Learning is managing data quality, as Machine Learning algorithms require high-quality, reliable data to produce accurate results.
Machine Learning systems require organizations to implement processes for collecting, cleaning, and structuring relevant data, as well as develop models for feature selection and anomaly detection.
The primary risk with applying Machine Learning techniques is overconfidence in the models. Over-optimistic Machine Learning models can lead to inaccurate predictions, improper risk-reward trade-offs, and poor investment decisions.
Training and validation are two core principles in Machine Learning to avoid overfitted models that show poor performance on new data. Models are calibrated and tested on different data sets to assure optimal predictive power for unseen data inputs.
There are many things organizations can do to stay updated about Machine Learning trends and innovations: By now several Machine Learning conferences that are specialized in finance have come into existence and there are many experts in the field that talk about the most recent developments. Staying up to date with dedicated industry news is also a good way of tracking latest Machine Learning trends.
Fact: Machine Learning models quickly learn from large datasets and structure valuable information with the help of supervised and unsupervised learning algorithms. This data is used to make predictions or find patterns that identify opportunities and risks in the markets.
Fact: Machine Learning is a valuable tool for investment management and can supplement the decision-making process by monitoring market trends and identifying potential risks and opportunities. However, Machine Learning cannot replace human judgment and intuition, which is an important factor in the investment management process.
Fact: While Machine Learning models can be prone to overfitting if not properly tuned, proper tuning of parameters and features can solve the problem. In addtion, a rigorous process of training and testing data, as well as selection of the right algorithms, can help reduce the risk of overfitting.
Fact: Machine Learning can be used not only in short-term investing but also in long-term investment strategies. Machine Learning models are able to quickly learn from datasets and identify patterns that can be used to identify trends, opportunities and risks in the markets over long periods of time.
Fact: Machine Learning models are not as expensive as one may think. With the right resources and technology, Machine Learning can be implemented relatively cheaply. Additionally, when used correctly, Machine Learning models are more efficient than traditional investment models and can help save costs in the long run.
Fact: Machine Learning may appear complex at first, but with the right resources and guidance, it can be a very valuable tool in investment management. With the help of step-by-step tutorials, even beginners can understand the basics and get started with Machine Learning.
Fact: While it may appear like a black box at first, machine learning models are can be well interpretable with the right tools at hand. With the help of various algorithms and techniques, the underlying components of the models can be explored and manipulated to create optimal and transparent models.
Fact: Machine Learning can be beneficial to hedge funds but can be equally beneficial to other types of investors. Machine Learning can be used to identify opportunities and risks in markets which can help any kind of investor make better and more informed decisions.
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We combine new data sources with machine learning techniques to reveal nonlinear relationships and identify new pathways in investing.
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The controller of the website or the hosting provider collects data on each access to the server on which this service is located (so-called server log files) on the basis of a legitimate interest within the meaning of Art. 6 para. 1 lit. f. GDPR. Access data includes the name of the retrieved website, file, date and time of retrieval, amount of data transferred, message about successful retrieval, type of browser including version, user’s operating system, referrer URL (the previously visited page), IP address and the requesting provider.
For security reasons (e.g. for the investigation of abuse or fraud), log file information is stored for a maximum of seven days. After that, they are deleted. Data whose further retention is necessary for evidence purposes is exempted from deletion until the final clarification of the respective incident.
Type of log files and data collection
Access log files and error log files are stored on the server. These log files contain the user’s IP address and thus personal data. The following data is collected: visited website, time at the time of access, amount of data sent in bytes, source / reference from which the user reached the page, used browser, used operating system and used IP address. A contract processing contract (AVV) is concluded with the hosting provider, which meets the requirements of § 11 BDSG.
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Hosting services taken up by the controller of the website serve to provide the following services: infrastructure and platform services, computing capacity, storage space and database services, security services and technical maintenance services used for the operation of this online offer.
In this context, the controller or the hosting provider processes inventory data, contact data, content data, contract data, usage data, meta and communication data of users of this online offer on the basis of a legitimate interest in an efficient and secure provision of the online offer in accordance with Art. 6 para. 1 lit. f GDPR in conjunction with Art. 28 GDPR (conclusion of a contract processing contract).
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The user has the right at any time to obtain free information about stored personal data, their origin and recipients and the purpose of data processing. In addition, there is a right to correction, blocking or deletion of these data. Deletion can only take place if there are no legal or contractual obligations to collect data. If data has been collected on the basis of a legitimate interest, the user has the possibility of objecting to the processing.
Use of Google Analytics
Scope of processing of personal data: We use Google Analytics, a web analysis service of Google LLC., 1600 Amphiteatre Parkway, Mountain View, CA 94043, United States (“Google”) on our website. Google Analytics uses so-called “cookies”, text files that are stored on your computer and enable an analysis of your use of the website. The information generated by the cookie about your use of this website is transferred to a Google server in the USA and stored there. If IP anonymization is activated on this website, your IP address will be shortened by Google within member states of the European Union or in other contracting states of the Agreement on the European Economic Area. Only in exceptional cases will the full IP address be transferred to a Google server in the USA and shortened there. IP anonymization is active on this website. On behalf of the operator of this website, Google will use this information to evaluate your use of the website, to compile reports on website activity and to provide other services related to website usage and internet usage to the website operator. The IP address transmitted by your browser as part of Google Analytics will not be merged with other data from Google. You can prevent the storage of cookies by a corresponding setting of your browser software; however, please note that if you do this, you may not be able to use all the features of this website to the fullest extent.
Legal basis for the processing of personal data: The legal basis for the processing is Art. 6 (1) lit. f GDPR.
Purpose of data processing: The purpose of processing the personal data is to address a target group that has already shown an initial interest by visiting the site.
Duration of storage: Advertising data in server logs are anonymized by Google deleting parts of the IP address and cookie information after 9 or 18 months.
Opposition and elimination possibility: You can also prevent Google from collecting the data generated by the cookie and relating to your use of the website (including your IP address) and from processing this data by downloading and installing the browser plugin available at the following link:
http://tools.google.com/dlpage/gaoptout?hl=de. For more information, please visit
https://www.google.com/intl/de/policies/privacy/partners (“How Google partners use data”),
http://www.google.com/policies/technologies/ads (“Data usage for advertising purposes”),
http://www.google.de/settings/ads (“Manage the information Google uses to show you ads”), and
http://www.google.com/ads/preferences (“Determine which advertising Google shows you”).
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QI Investment Advisory GmbH
Dachauer Straße 65
80335 Munich
Email: enquiry@qi-investment.com
Telephone: +49 (0) 89 122 93665
Registered office: Munich
Commercial register: Munich HRB 249050
Managing directors: Dr. Axel Stahmer, Dr. Christoph Wagner
Investment advice according to section 2 para. 2 no. 4 German Wertpapierinstitutsgesetz (WpIG) and investment brokerage according to section 2 para. 2 no. 3 WpIG shall be made on behalf of, in the name of, for the account and under the liability of the responsible legal entity BN & Partners Capital AG, Steinstraße 33, 50374 Erftstadt, according to section 3 para. 2 WpIG. BN & Partners Capital AG has a corresponding license from the German Federal Financial Supervisory Authority (BaFin) in accordance with section 15 WpIG for the prenamed financial services.
Due to legal obligation, BN & Partners Capital AG participates in the dispute resolution procedures of the arbitration board responsible for it at the Federal Financial Supervisory Authority in case of disputes arising from or concerning consumer contracts with BN & Partners Capital AG.
Contact details of the arbitration board:
Federal Financial Supervisory Authority – Arbitration Board
Graurheindorfer Str. 108
53117 Bonn
Germany
Telephone: +49 228 4108 0
Fax: +49 228 410 862 299
Internet: www.bafin.de
E-mail: schlichtungsstelle@bafin.de
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In the case of direct or indirect references to third-party websites (so-called “hyperlinks”), which are not within the responsibility of the author, liability shall only be assumed in the event that the author has knowledge of the content and it would have been technically possible and reasonable for him/her to prevent the use in the case of illegal content. The author hereby expressly declares that at the time of setting the hyperlinks, no illegal content was recognizable on the pages to be linked. The author has no influence whatsoever on the current and future design, contents or authorship of the linked/connected pages. The author hereby expressly distances himself/herself from all contents of all linked/connected pages which have been modified after the link was set. This applies to all links and references set within the author’s own Internet offer as well as to foreign entries in discussion forums, guest books, link directories, mailing lists and all other forms of databases in which external write access is possible. The provider of the page to which reference is made is solely liable for illegal, defective or incomplete contents and in particular for damages resulting from the use or non-use of such information and not the one who merely refers to the respective publication via links.
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The information provided on this website has been carefully checked and is updated regularly. The website serves as marketing information for website visitors. In particular, the information on financial instruments and securities services is directed exclusively at professional investors domiciled or habitually resident in Germany. The content does not constitute investment advice, investment brokerage or a recommendation to purchase securities. Investment decisions should only be made after consolidating all available information, in particular the securities prospectus. No guarantee can be given that all details and information are complete, correct and/or up to date at all times. This applies in particular to all links to other websites referred to directly or indirectly. We reserve the right to add, remove and/or change all information without prior notice.
This disclaimer is seen as part of the online offering from which this page was referenced. If certain elements or individual formulations of this text should not correspond or no longer correspond or not fully correspond to the current legal situation, the remaining parts of the document shall remain unaffected in their content and validity. QI Investment Advisory GmbH disclaims any liability for losses or damages of any kind arising from access to its website or its hyperlinks. These provisions are subject to the law of the Federal Republic of Germany.
Data Privacy
Purpose-Bound Data Usage
Under the principle of purpose-bound data usage, we collect, process and store personal data only for the purposes that the user has communicated to us. Without explicit consent, no further transmission of the user’s personal data to third parties will take place – unless this is necessary for the performance of the service or for the performance of the contract. Transmission to authorized state institutions and authorities is limited to those required under the statutory duty to provide information (or a court decision to provide information). Employees and service companies commissioned by us are obliged to maintain confidentiality and comply with data protection regulations.
Newsletter, Information Material Request & Contact Forms
The website visitor can make use of different forms for specific services (newsletter, information material request, and contact forms). In accordance with GDPR, the data collected in these form may be processed for the purpose of fulfilling you this service (like sending newsletter, information material, or contacting the interested party). To facilitate this, the data will be shared with third-party provider Mailchimp. The submitted data will only be used for this specific purpose and will not be shared with another third party without your explicit consent.
Cookies
“Cookies” are small files that are stored on users’ computers. Different information can be stored on a cookie. Firstly, it is used to store information about a user (or the device on which the cookie is stored) during or after his visit to an online service. Temporary cookies (also called “session cookies” or “transient cookies”) are cookies that are deleted when a user leaves an online service and closes his browser. These cookies can, for example, save the contents of a shopping cart. Cookies that are referred to as “permanent” or “persistent” remain even after the browser is closed. For example, the login status can be saved – even if a user visits the website again after several days. “Third-party cookies” are offered by other providers than the responsible party (which operates the online service). Cookies of the responsible party are referred to as “first-party cookies”.
Both temporary and persistent cookies can be used and are explained in this privacy policy.
If a user does not want cookies to be stored on his computer, he should disable the corresponding options in the system settings of his browser. The stored cookies can be deleted in the system settings of the browser. Exclusion of cookies may lead to functional restrictions of this online service.
Collection of access data and log files
The controller of the website or the hosting provider collects data on each access to the server on which this service is located (so-called server log files) on the basis of a legitimate interest within the meaning of Art. 6 para. 1 lit. f. GDPR. Access data includes the name of the retrieved website, file, date and time of retrieval, amount of data transferred, message about successful retrieval, type of browser including version, user’s operating system, referrer URL (the previously visited page), IP address and the requesting provider.
For security reasons (e.g. for the investigation of abuse or fraud), log file information is stored for a maximum of seven days. After that, they are deleted. Data whose further retention is necessary for evidence purposes is exempted from deletion until the final clarification of the respective incident.
Type of log files and data collection
Access log files and error log files are stored on the server. These log files contain the user’s IP address and thus personal data. The following data is collected: visited website, time at the time of access, amount of data sent in bytes, source / reference from which the user reached the page, used browser, used operating system and used IP address. A contract processing contract (AVV) is concluded with the hosting provider, which meets the requirements of § 11 BDSG.
Hosting
Hosting services taken up by the controller of the website serve to provide the following services: infrastructure and platform services, computing capacity, storage space and database services, security services and technical maintenance services used for the operation of this online offer.
In this context, the controller or the hosting provider processes inventory data, contact data, content data, contract data, usage data, meta and communication data of users of this online offer on the basis of a legitimate interest in an efficient and secure provision of the online offer in accordance with Art. 6 para. 1 lit. f GDPR in conjunction with Art. 28 GDPR (conclusion of a contract processing contract).
Right to information and objection
The user has the right at any time to obtain free information about stored personal data, their origin and recipients and the purpose of data processing. In addition, there is a right to correction, blocking or deletion of these data. Deletion can only take place if there are no legal or contractual obligations to collect data. If data has been collected on the basis of a legitimate interest, the user has the possibility of objecting to the processing.
Use of Google Analytics
Scope of processing of personal data: We use Google Analytics, a web analysis service of Google LLC., 1600 Amphiteatre Parkway, Mountain View, CA 94043, United States (“Google”) on our website. Google Analytics uses so-called “cookies”, text files that are stored on your computer and enable an analysis of your use of the website. The information generated by the cookie about your use of this website is transferred to a Google server in the USA and stored there. If IP anonymization is activated on this website, your IP address will be shortened by Google within member states of the European Union or in other contracting states of the Agreement on the European Economic Area. Only in exceptional cases will the full IP address be transferred to a Google server in the USA and shortened there. IP anonymization is active on this website. On behalf of the operator of this website, Google will use this information to evaluate your use of the website, to compile reports on website activity and to provide other services related to website usage and internet usage to the website operator. The IP address transmitted by your browser as part of Google Analytics will not be merged with other data from Google. You can prevent the storage of cookies by a corresponding setting of your browser software; however, please note that if you do this, you may not be able to use all the features of this website to the fullest extent.
Legal basis for the processing of personal data: The legal basis for the processing is Art. 6 (1) lit. f GDPR.
Purpose of data processing: The purpose of processing the personal data is to address a target group that has already shown an initial interest by visiting the site.
Duration of storage: Advertising data in server logs are anonymized by Google deleting parts of the IP address and cookie information after 9 or 18 months.
Opposition and elimination possibility: You can also prevent Google from collecting the data generated by the cookie and relating to your use of the website (including your IP address) and from processing this data by downloading and installing the browser plugin available at the following link:
http://tools.google.com/dlpage/gaoptout?hl=de. For more information, please visit
https://www.google.com/intl/de/policies/privacy/partners (“How Google partners use data”),
http://www.google.com/policies/technologies/ads (“Data usage for advertising purposes”),
http://www.google.de/settings/ads (“Manage the information Google uses to show you ads”), and
http://www.google.com/ads/preferences (“Determine which advertising Google shows you”).
For ESG (on staging servers):
QI Investment Advisory GmbH acts as a tied agent according to section 3 para. 2 German Wertpapierinstitutsgesetz (WpIG) on behalf of, in the name of, for the account and unter the liability of the responsible entity BN & Partners Capital AG, Steinstr. 33, 50374 Erftstadt. The mandatory information of the EU Disclosure Regulation of BN & Partners Capital AG as investment firm / financial advisor can be found here:
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Get in touch with QI for a discussion with the partners of the company.
Get in touch with QI for a discussion with the partners of the company.
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