2001-2002: ALGORITHMS IN COMMODITIES
Set up one of the first algorithmic trading desks for gas at a commercial company
· SciTheWorld ·
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Would you use it only for trading or would you be slightly more ambitious?
YOU WOULD SIMPLY EXTEND IT TO RISK MANAGERS, DATA SCIENTISTS, SALES/BANKERS AND TECH MANAGERS
RISK MANAGERS cannot chase traders nor algorithms with a tier two technology
DATA SCIENTISTS require a realistic Lab based on trading insights. And they should be able to throw their Python code into it at a minimum effort
SALES need timely recommendations based on sound signals from intraday to long run (standard Recommendation Systems are not enough)
TECH MANAGERS need to know how to efficiently deploy the previous modules within a central, steady architecture
We bring maximal flexibility to traders (400+ parameters) to easily accomodate their ideas
We allow risk managers to create their own algorithmic strategies to stress and control those of the traders real time. Boost liquidity risk management through the same architecture
We provide data scientists a realistic environment for them to isolate their, already complex, Machine Learning challenge
We allow them to crucially enhance their recommendation systems with our market insights
Would you settle for a one-off or would you be slightly more ambitious?
Set up one of the first algorithmic trading desks for gas at a commercial company
One of the first pioneers to research on the role of bots in Finance (Kyoto University)
Doubled and quadrupled P&L at different trading desks from different Tier One Banks (commercial and US IB)
Entered the first cohort of the UK PhD Center for Financial Computing.
The Thesis was applied for real at a Tier Two bank - our "sandbox". We took them from manual trading onto the Frontier of Knowledge within 5 years. Against all odds, its algorithmic architecture got the prize to the best trading platform in Europe. Similartly, its novel approach to A.I., Avatar Calibration (the first example of Augmented Machines) was selected by UK EPSRC for its major impact in the Digital Economy
Succeeded on the first cross-asset algorithmic transformation of the sell-side. Now, best-practice of the industry
We spent two years only devoted to developing the overarching technology needed to offer the suite of products that we wanted to start providing
Set out the first autonomous machine on production at a business (statement from a BigTech)
Set out the first augmented machine on production
Set out the first algorithmic risk strategy that can be sent on-the-fly to supervise algorithmic trading strategies real time
During the last quarter of 2019, within the first two weeks of selling, we secured a deal to set up our tech at a tier one bank for the first time - a major milestone that allowed us getting a fast traction towards 2020
MRes in Financial Computing at UK PhD Centre for Financial Computing and Analytics (UCL, LSE, LBS). Authored the first publication towards Synthetic Liquidity Provision through Multi-Objective Particle Swarm Optimization - used to create liquidity on EM ETFs at the industry. Former Head of Commercial Knowledge at BBVA and IT Consultant in the Tech and Banking industries
PhD in Computer Science at UCL. Honorary Senior Research Associate at UCL, Computer Science. Senior Advisor Cyber, Transformation & Finance at Oliver Wyman. Former Global Head of Data Science at BBVA, Global Head of Algo Strats at BBVA Global Markets, Equities Trader at Morgan Stanley UK, FI Trader & Structurer at Santander & Santander UK, and Risk consultant at Deloitte
Sr Lawyer. Father to the "Right to be Forgotten" on internet. European Data Protection Officer
Goya awarded film director. Frequent visual content creator for banks on the A.I. space, and marketing expert
Sr Fellow Harvard. Strategy consultant. Political advisor. Diplomat. Fmr CEO Women's World Bank.Artist. Buddhist
Sr Trader across assets. Former Global Head of Equities at BBVA Global Markets, and CIO of BBVA Asset Management
Computer Scientist. Professor at University College London. Founder of the UK Centre for Financial Computing & Analytics
Sr lawyer. Named "Cornerstone in Spain's Maritime Law" by Chambers Europe. Former General Secretary at Duro Felguera
Filter the elements in your portfolio based on facts just as the most advanced big data providers would - whether from structured or unstructured data. And do not settle for that. Further filter by:
a) Signals: ours/yours or 3rd party’s signals - from traditional to algorithmic, inherited from inSCIghts; b) Simulation: your views on your desired performance of each element and the portfolio overall upon feasible scenarios when combined with FLY
On-the-fly macro simulation. Smart shortcut to allow for many scenario views before committing to trading a portfolio - not as precise as those produced by our VR Sandbox but handy enough for most Low Frequency Trading.
It leverages Big Data along with Online Machine Learning
Set out the weights in your portfolio based on our free samples (from equal weight to percentage of volume) to our proprietary methodologies (e.g. black swan) through any of your own (DIY) or a 3rd party. Whether static/passive or dynamic/active (considering benefits vs market impact and costs). Whether on a basic Backtest or within our VR Sandbox for you to control all the range of risks from low frequency trading to intraday. Start orthogonal strategies by mixing it with Fractal’s capabilities
Highly fine-tunable Algo Trading engine for your traders to materialize their complex ideas. No coding skills required. Focused on non-latency sensitive strategies. Capable to onboard latency-sensitive ones. It reaches execution, market making and prop trading. Seamless integration with most trading buses, brokers and data providers
A.I.-driven, trading and risk, proprietary indicators. Any party's IP - whether your model, ours or even our own competitors' (we see them as partners). Any type of asset: equities, fixed income, commodities, currencies and cryptocurrencies. Any type of data: quotes, geo-localized/imaginary, social... Whether their signals lead to high frequency quotes dynamics or a mere email/report
Trading floors nowadays require a suite of state-of-the-art strategies, in the shape of a Central Risk Book. This piece, scans all flow coming in and out of the books (whether occurring or expected) and eventually takes it to benefit from orthogonal hedges across desks (and assets) or to reduce market footprint in execution (crucial to give a tier one service to large clients)
New breed of controls and actions for each line of defense (LOD): 1, 1.5, 2 and ours, 3. Leverage Advanced Trading Technology across assets. Whether manual actions or systematic
Similar approach for back office liquidity management strategies
Leverage trading tech to audit traders' algorithmic black-boxes. Whether by yourself (2LOD), by ourselves (3LOD) or, better, by both
Inspired by our experience in Red Teams of Cybersecurity
Stronger when combined with VR Sandbox
Make sure your data scientists comply effortless with local regulation when querying data
Backtesting is not realistic. First, the past is just one of the myriad of instances that could have happened, hence not that relevant by itself. Second, it assumes the rest of the agents would not react to your actions. Design, test and calibrate new trading strategies. Improve existing ones. And leverage it to train your teams within the, otherwise complex and expensive, area of Algorithmic Trading
Same for stress testing
Enhance the accuracy of your Sales (Global Markets & Asset Management) and Bankers (Private, SMEs and Corporates) by letting them timely react to a myriad of high-to-mid frequency signals. Do not settle for standard Recommendation Systems inherited from other domains. Based on "OVERARCH", it brings high quality architecture that includes our business acumen
Use our platform as a book of game rules across traders, data scientists and risk manager so that everyone feels comfortable. Gain crucial insights before devoting large budget onto major decisions. More than halve your digital costs going forward by orderly recycling code, and combining different providers within a well-thought architecture (DIY, ourselves or 3rd parties)
"Which spread is optimal to enter in order to hedge the risk we want to mitigate? Which basis? Shall I use baskets instead of isolated instruments? Shall we have an automatic hedge for the hedge in case it moves sharply against us (corner/squeeze)?"
All these questions that help you adapt to the new era in trading - and more - can be advancely analyzed through the same set of our Finance products. These products are the consequence of embedding all different challenges across assets within a same platform. Most of those started in Equities hence, the digitization of Energy & Commodities is nevertheless another case from the, already well-known, Equitization process that, underpinned by data and electronic markets, the whole investment-and-hedging industry is following.
By leveraging our advanced Machine Learning technology from Algorithmic Trading, upon all your private (sensors information (IoT), inventory, sales...) and public (news, market prices...) data sources, we can help you improve the risk-reward ratio of your business - i.e. higher revenues, lower costs and more steady both. This is, we can help you settle the right path towards the digitization of your business.
You will anticipate:
- changes in prices of inputs (yours and those of your providers) and outputs and their consequences in your business
- failures in the inputs you have been supplied with
- failures in your operational processes
- risks in your business dynamics
Towards a real-time system of alerts that allows you to orchestrate every piece involved in aligning all stages of your supply chain:
- better manage your assets' maintenance - e.g. timings and priorities
- prevent safety issues
- decide the optimal level of inventory
- decide your pricing and timing to sell
If Fractal, along with the rest of our products for Finance, allows investment agents to design, calibrate and audit a series of strategies to get ready for a fierce machine vs machine competition, why wouldn't they help IT managers defend their side of the business from external (and internal) attacks?
Our technology has been abstractly created as a Smart Agent and then, successfully projected into Finance. Next, we will be projecting it into Cybersecurity - the very area where SciTheWorld has been deliverying innovation consultancy since its inception in 2015.
We provide any digital strategy (whether for algorithmic trading, advertising, cybersecurity defense, etc) with a technology that prevents you from using it if it has been hacked.
Notably, this technology is one of the few where we strongly believe in the upside of using Blockchain.
A company can be subtly attacked by directly manipulating its equity and credit markets. It can also be gradually taken over behind the scene by active funds. We use our market expertise to track the dynamics of a company and send alerts to its CFO (e.g. "active fund X building up exposure").
Similarly, we track social networks to estimate whether bots are trying to manipulate the public opinion around a company. That way it can counter attack in a timely manner, whether manually or using our own set of Smart Agents.
How to make the most of your professionals in a world of machines? Adopt the earliest stage of Augmented Machines. Help your employees:
1.- take more insightful risks (e.g. traders and portfolio managers)
2.- advice your clients with a sounder judgement (e.g. sales and bankers)
by sharing intel and insights across teams.
Further discover who you should not leave out in your near, machine-driven future.
Beyond the basics of Collective Knowledge, we gather the views from your experts across a number of financial instruments and give you the views from our machine augmented by them. In other words, "Neocortex adds context".
Our Financial Computing suite of products is just the way we show the industry we can cope with the most advanced challenges on ML-driven apps.
But, as you can see through our singular approach to provide Down-to-Earth solutions, we have curiosity for the solutions-discovery process itself.
Hence, we are more than keen on expanding our portfolio of use-cases along different fields. Whether those have been already visited, as in the case of advanced cybersecurity, or yet to visit, as in the case of marketing, video games, online poker... any project in which we believe we can help our clients have an edge.
· REGULATORS ALGORITHMS APPROVALS ·
Both, Regulators and Banks, approach us to better analyse the suitability of a new, more data-driven algorithm, in the decision making process related to retail.
· GREEN ASSETS SYNTHETIC LIQUIDITY ·
By managing risk systematically and intradaily volume of certain illiquid assets can be increased by more than 30%
· CRYPTO INFLUENCERS ·
Detection and analyses of different bots at Twitter that attempt to affect crypto prices
· FX FIXING AND EQUITY CLOSE PREDICTION ·
Intraday forecasts to help derivative traders better manage their risks
· FIXED INCOME ISSUANCE ·
StatArb strategies and portfolio rebalancing around auction dates
· CREDIT BLACK SWAN ·
We adapted our platform to provide the ACPM desk of a tier one bank with a hedge against a major systemic crises
· REGULATORY ANALYSIS OF HFT ·
Distinguishing good from bad High Frequency Trading to avoid market manipulation
· ANTIMANIPULATION OF STRATEGIES ·
Make sure you are trading the strategy you are expeting to trade. All of its components. One of the few cases where we believe Blockchain has an edge.
· ANOMALY DETECTION ·
Outlier detection of standard activity across servers using billions of rows of information (Netflow data). Improvements in false positive detection exceeded x2
· CODE BOOST ·
Analysis of legacy code, redesign and strategic implementation - from data model to advanced use cases. Efficiency exceeded x3
· HOSTILE BID ANALYSIS ·
Analysis of the probability of large activist funds building up sudden exposure on a client's stock
· CEO PERFORMANCE ANALYSIS ·
Defense of a CEO's performance based on market expectations - discounting market impact from large players' expectations
We used to give lectures on Advanced Financial Computing to students and postgrads of Computer Science at University College London
Now it is the industry experts who we train. It is crucial for them to understand the challenges, the pros and the cons behind their digital transformation - in the limit, algorithmization. By leveraging the aforementioned suite of products, beyond mere Power Points, we grant an impactful, hands-on experience.
What is the quality of tech of the company I am considering buying? How many paths do I have to boost its digitization and what can I expect from each?
Most M&A due dilligences are missing this crucial dimension in the digital era.
We can analyze any company's technology (software and hardware architecture) towards its digitization. We can test how difficult it would be for it to onboard a non-invasive middleware software to leverage data and machine learning - we already have it and can adapt it, bespoke. We can further advice on the pros and the cons of the current team and managers skills, as well as on its personas' conflicts of interest (Game Theory).
If the company is acquired we can then provide sMARTApps and trA.I.ning to reach impactful transformation.
Not only SciTheWorld wants to compensate its professionals with top-end salaries, but also with the upside of having them blended with its financial tech
The Arms Race in Finance is by far one of the most complex of our history. Its direct machine-vs-machine competition leads to a need for precision that poses very fine challenges for our brains to be continuously entertained with
Due to FUNd, SciTheworld does not learn-by-doing with its clients' money. It mostly learns by risking its founders and employees' - quite an unbeatable level of guaranty on top of SciTheWorld's bias towards success fees
As a result, we continuously train ourselves to reallistically tackle some of the most demanding challenges in ML-driven tech. And that leads to a second-to-none judgement when providing solutions for our clients
"You have been the only ones to solve it"
[Beauty contest towards an ambitious CIB Transformation project]
"This is the first time someone proposes a solution that actually makes sense"
[We introduced our views on how to adapt Risk Management to the new era and how to crucially grant the right trA.I.ning]
"Your in-depth knowledge across fields can definitely help our CAIO have impact in her ambitious mandate"
[We were asked to fly over and meet her]
"You have been much faster than us reaching the same conclusion with that sample"
[Solving a challenge to prove our skills and turnaround capacity]
"I like a lot the way you have been able to click it all together"
[Presentation of our Suite of Products]
"In reality, what you have is a Digital Brain that can do many other things here"
[Introducing our Overarch technology]
"I hope he [Sergio] won't mind me saying that he is mad as a snake but full of good ideas."
[Sr Manager at a Hedge Fund kindly introducing SW to the Global Head of Digital at a Tier One Bank] -- don't tell Sergio but this is the one preferred by the team. Spot on: doesn't play games and makes you see things you would have never thought of
Transformation reaches a wide set of challenges, many of which require a team approach
We are starting different due dilligences to select the right group of strategic partners - not only value add is considered but also that there is no friction between them
We are happy to integrate any third party data or module to our overarching technology. Whether from industry or from academia.
If you want your services to be provided through SciTheWorld's Himitsu platform, contact us.
We can proudly say, we don't have them yet. We have accounted for a cybersecurity business that was able to fund our riskiest decisions - e.g. giving up to growth to keep focus on developing our Digital Assets. In the future, we will consider external funding - yet, only from partners that grant our freedom to make decisions towards our ambitiuos projects
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The very day we won our most fierce competitors on a major beauty contest, we Augmented for the first time our Autonomous Machine - at last we have the perfect Kernel to start communicating with our A.I. asset and vice-versa
At prime time TV news, we advice on the many ways a hacker can use the different apps that are getting trendy to blackmail you or phish you whether with regards to your personal or your professional life
CEO, woman in tech, who codes platform and algorithms all day long, recycled from Biology... being on TV should happen sooner or latter ;)
Invited by the Interamerican Development Bank and AstUr Foundation to discuss the ways forward on Latin America through Machine Learning
Helped distinguish good from bad High Frequency Trading. The research therein conducted yielded a prize to the leader of the project
More interest rallied on Augmented Machines took our Avatar Calibration - quite a complex concept - to be widespread through a TED Talk
Mainstream magazine asked us to talk about our discoveries on the activity of bots "influencers" within Twitter
Top newspaper noticed we were considered pioneers of the financial industry and wanted to tell Spain...
Shared panel on Advanced A.I. with Google DeepMind, Oxford University and UCL. We introduced Augmented Machines to an audience with Nobel Laureates
We were asked to speak with @Jack, founder and CEO of Twitter, when he came to Europe. Lots to say about their Machine Learning strategy
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Email: info at scitheworld.com