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"Applied Blockchain" raises £2m to enable companies to do more together while sharing less data

Leading distributed solutions specialist Applied Blockchain has completed a £2 million funding round lead by Hong Kong based venture capital firm QBN Capital. The newly-injected funds will be invested in developing a platform using privacy-enhancing technologies to help companies to collaborate and generate meaningful outcomes together, without having to share any of their data.

Companies face increasing cybersecurity risks and regulatory requirements in regards to their data, and these are further exacerbated as data leaves an organisation and is shared with others. Recent events mean that businesses are going to become even more digital, and this means that companies will have to improve the way they handle private and sensitive data.

Applied Blockchain has already started working with its growing enterprise client base to test the platform in their respective markets, including energy, shipping, aviation, automotive, telecoms and financial services, demonstrating that it substantially improves their data security and data privacy.

Based at Level39 in London, Applied Blockchain has developed over 70 distributed solutions for both start-ups and corporates and was selected by Shell to build and deploy the first distributed platform for energy derivative trading, which has been live in production since 2018. Shell also lead the seed investment round in 2017 alongside venture capital firm Calibrate.

Adi Ben-Ari, founder and CEO Applied Blockchain, said: “We are very excited to be building a platform to meet the demands of our enterprise clients to do more with their data, while keeping it safe, secure and private. We have now received funding from a strategic venture capital firm, QBN Capital, and we look forward to further developing our privacy-preserving technology and working with them to extend our reach into the Asian markets.”

Philea Chim at QBN Capital said: “Governments, corporates, and individuals are increasingly concerned about data privacy and data security. We believe zero knowledge proofs offer a new and better way to share and handle data. We are very excited to be supporting Applied Blockchain, a pioneer in this space, and we can't wait to see an abundance of applications for ZKP coming out in the near future.”


Worst Month since 1929, Best week since 2008

An article by Anup Singh:

If we view the past 3 weeks from the lens of the pandemic it is almost impossible to find another event that is comparable, because we cannot compare one loss of human life to another.


On a lighter note, watching the screen: The subject line is not fact checked - Worst Month since 1929, Best week since 2008, and is from a twitter feed last week. Even if it is not accurate, it sure feels that way. During our pre-market prep, we found the following charts very intriguing – and knowing each of you on this email – we are curious as to what these charts make you think


A word of caution: The following charts DO NOT reflect implied Correlations; and reflect trader (Risk ON/OFF) sentiment and contagion. Studying Correlations and/or Cointegration necessitates a high degree of mathematical rigor and precision, and the following charts do not reflect that.


Look at Soybean Meal and Orange Juice:


Be careful this week – its not often that one gets to be a part of a drill (2008) and live contact sport (2020) in the Volatility arena.

New Regime | Risk First, Then Opportunity in Volatility

An article by Anup Singh:

This note is NOT about COVID, because I know NOTHING about it. Neither is this about predicting the market; rather it’s about sharing some experiences that may be of assistance to you as you operate in today’s uncertainty and extreme volatility. Most of us participate in markets to manage risk and do not have the choice of being discretionary traders – we are required to operate and continue to find beneficial opportunities for our businesses. As a buyer we can either Buy or Not buy and occasionally Sell an excess purchase when sales forecasts change. The mirror image is the sales side which mostly Selling or Not selling with the occasional Buy Back


A touch early to call – a tsunami of stimulus coordinated (not certain Re coordination) across multiple administrations was thrown at the market over the past 3 weeks and the S&P sold down 1100+ points, spreading contagion to other markets including Asia this weekend. The Fed hastened to cut rates and make US Dollars available to a dollar starved global trade, and most currencies fell perching the greenback higher.


THIS one is our First: “Liquidity can take price to places unimaginable. Price is the balancing mechanism for liquidity and not an accurate discounting mechanism” (John Burbank)

  1. We have worked through several price crashes in commodity markets and two in equity markets, but this is not a price crash but has the potential of evolving into a high magnitude LIQUIDITY crash. Around the Enron bankruptcy, I worked at EPGN, El Paso Energy’s broadband trading desk (only one person on this distribution will recognize that name) and I could not find a bid to liquidate a $300,000/unit position until $3,000. Nat Gas found a bid at $1.8 on 28th Sep after free falling from $6.6 = No Bid, because the buyer did not know what the demand was likely to be.

  2. The global economy has performed as a diversified risk basket, with growth in several microsystems offset slowdown in another.  This is the first time that we can contemplate that all/most economies and economic activities have come to a standstill at ONCE

  3. Confluence of forces/shocks –

    1. Demand Shock

    2. Supply Shock

    3. Wealth Shock: With the number of households connected to financial markets, a collapse of financial asset values will hurt hard, especially if pensions cannot pay and go belly up.

    4. Credit Shock: Unsold inventory consumes working capital, which in turn consumes credit the bank has available to distribute across its risk portfolio and ultimately shrinks available credit. This is made worse when a big portion of the bank’s loan portfolio becomes non-performing. There are some additional knock on effects that I can discuss if needed.

    5. Sovereign/Corp Debt Shock – to what you are already aware, I’ll add that if GDP growth rate is lower than the interest rate and everyone goes into deleveraging at the same time, expansion is hurt

  4. Controversial point: COVID did not cause this liquidity event, it was the tipping point that exposed the fragility of the prevailing environment.

    1. Something to Ponder - Did the trade wars cause the slowdown or did the slowdown lead to the trade wars?


Consider strengthening your repertoire by adding following actions: If you are already evaluating these, you are several steps ahead of others

  1. Relationships with Suppliers and Customers: Volatility and varying degrees of preparedness will put suppliers and customers at elevated levels of performance risk. If one doesn’t engage in business with certain customers they don’t engage in business with us, leading to additional liquidity vacuum in addition to the systemic liquidity vacuum. This is perhaps a better opportunity to extend our skills to our suppliers as well as our customers and build partnerships in risk. Better quality of practices with our counterparties makes for lower performance and business risk

  2. Market Risk and impact to Balance Sheet

    1. Stress the projected Cash Flow for prolonged periods of low prices and volatile prices, unchanged fixed costs and lower % of volume throughput and identify break points on the term structure and evaluate what can be done while there is still some time to act

      • Combine price and credit events. Certain price circumstances may lead counterparties to downgrade the entity and certain price scenarios may lead the entity to downgrade the counterparty. A combination of both provides a multifaceted view of impact to balance sheet

    2. Evaluate impact to income statement and balance sheet and equity impairment levels under various lengths of exposure to price conditions. The results may not be pleasant however will help with preparedness

    3. Evaluate the debt covenants in light of current circumstances and the impact of prolonged stresses to the balance sheet and evaluate actions that might need preparation while there is time to prepare

    4. Tactics that may have been terms risky or unacceptable, may be applicable for current times. Approval to act and being prepared to act are different issues, being prepared doesn’t hurt

  3. Liquidity: Access to credit lines and working capital lines. If the market thus far is of any evidence, there seems to be a severe cash squeeze on with large institutions who had levered up reaching out for all assets to extract cash and stay solvent. This will likely lead to a tightening of cash (see USD strength despite rate cuts and the Eurodollar futures for evidence of US Dollar tightness since early 2019). Previously available cash/credit lines may not be available later when needed. Interest may be a very small price to pay in return for access to precious cash

  4. Multi Point Test: During times of moderate volatility, it may be remotely acceptable to to test one or two indicators.

    1. In the current environment of extreme volatility, one needs to test fundamental indicators against price and trend and then test against volatility regime and make/size decisions accordingly. An argument made by someone we respect tremendously is that – in times of 2 or 3 standard deviation moves in volatility, the underlying asset becomes un-investible.

    2. Bid/Ask/Size: For those involved in physical businesses, keep a laser focus and the most alert senses on inbound enquiries – price indication and bid/offer size, across all term horizons – 1 week, 2nd Week, Balance of month, 1st Half next month

    3. If not already tracking – lifting pace  booking pace 1-10 of month, 1-20 and 1-30 of month is very indicative of cash liquidity

  5. Strategies: All measures, physical contracts, physical contracts with pricing and credit terms, use of derivatives or derivative like terms within physical agreements and use of derivatives should all be brought together as risk management tools to shore up the financial viability of the business

  6. Risk Policy: Higher volatility may need additional risk tolerance, not as much to take risk, but to mitigate risk.

    1. The firm’s natural position may already be significantly exposed and inability to act may add to the elevate the risk level. Risk needs to be evaluated on the entire business combining the natural exposure with risk mitigation measures in addition to existing metrics

    2. Depending on the simulation models, VaR models for the foreseeable term will value positions against a heightened volatility surface – the forward prediction is informed either by the most recent simulation or a volatility weighted one or an exponential one and in either case will, rightfully so, produce high risk valuations. Position sizing is a potent risk response.

  7. Wisdom:

    1. If it remains a bargain for long, it ain’t one

    2. Market moves in direction that hurts most people

    3. One must be selling when there is yelling and buying when there is bleeding – check #1 first

    4. When you need a deal real bad, what you get is a really bad deal

    5. Match the trade horizon with the Idea horizon

Silver Lining: There is life and an economy on the other side

  1. Reward of work is more work: Most of us trade to manage risk and do not have the luxury of being discretionary traders – meaning we have to go to the market and operate.  As a buyer we can either Buy or Not Buy and seldom sell what we don’t need. As a marketer either we can sell or not sell and seldom buy back what we regret selling. If we have a process, an execution discipline that accompanies the process, then little changed for us. Same process, same discipline, another day, albeit an extremely difficult day. Plan the work, work the plan

    1. Risk tactics for low volatility regimes

    2. Risk tactics for high volatility regime

    3. And risk tactics for extreme chop-city Volatility

  2. People still need to eat, drink, turn lights on, buy monitors/laptops, consume coffee and booze, occasionally drive, fill the fridge (and they all don’t know how to cook). Children need to learn/school, we need banking, plants need to run to supply staples.

    1. If they don’t know how to cook, they will eat readymade meals.

    2. Services and product configurations will change, waste will get minimized and yes a price will need to be paid for all this.

    3. “Every time one thinks the world is going to come to an end, the world surprises by living on” (Sir Templeton)

  3. Market turmoil/meltdown is also a shake out – think Moneyball

    1. 2001: Two things happened – Internet and Terrorism.  Both changed business models globally. GFC did not materially change business models, the internet and connectedness did.

    2. 2020: Despite the lock down, we are still working, creating economic value, making sure the GDP growth rate does not drag into depression

    3. Each one of us has the accountability and the fun job to be a Billy Bean and make Oakland A’s of our teams and our businesses

    4. Consider this for ingenuity: The Berlin Philharmonic orchestra is offering Digital Halls so audiences can enjoy concerts from the comfort of their homes:

PS: Note regarding evaluating and comparing analogues

  • GFC – It was an impairment of credit availability more and less a demand/supply shock (commodities, commerce, goods flow), we did not stop flying and did not stop leaving the home

    • GFC was not broadcast on Twitter or Wall 2 Wall coverage: Impacts were felt 6-8 months following the market crash in Oct’08. Test it with people around you and see how many people knew that the market was crashing during GFC and if they did, did they think it would immediately impact them?

    • While some on this email distribution may have seen the GFC coming, I did not. I did see the crash unfold and like a trained BOT bought the dips, only to lose the money. BUT, the average person on the street did not see the crash or even know that one occurred until it made the media. Economic impact was felt months later after the layoffs occurred.

    • It’s an extremely connected economy – viz how quickly the Crude market rebounded after the Saudi attack and the Iranian assassination, including the market open after the Saudi -$10 discount Cash basis

  • Reported/surveyed physical prices reflect the after effect of a liquidity event reported following a negotiation between a buyer and seller, whereas futures can help gauge prevailing sentiment. When comparing older analogues, it’s very relevant to understand the prevailing environment (sentiment, information availability, inter connectedness). There were either no futures for certain products or different contexts during past events

    • Participant mix is markedly different today compared to 10 years ago or 20 years ago

  • Imagination and creativity – we will need to find several different analogues and stitch them together

    • 9-11 NY Style lock down but across all cities

    • Logistics and life disruption in Fukushima and Chernobyl (not the nuclear fallout) and apply the disruption (loss of demand and trade) to all countries across months

    • Changes in import/export volumes during political unrest or economic activity: Rwanda genocide (500K-1M people killed, loss of food demand), South African imports and AIDS (workforce depletion to AIDS was very high during the 90s), Bosnia et al.

    • Stagnated prices for 5 years (Great depression 1929 to 1937, 1964-1979)

Some interesting charts:

Market crashes in the recent 30 years: Contract the abrupt drop in equity markets in the last 40 days compared to ‘gentle slope’ of 2008 and the smoother drift during 2000-2002


The End of the World Kitchen Sink Program: Various Stimulus announced in the past 2 weeks, and there is more on the way


Market Reaction: The days the market seemingly steadied are days when there was no stimulus. Almost feels like there is deliberate selling in anticipation of a sovereign indirect Bid. The 4 charts are S&P, FTSE, DAX and DJI – they all look identical




A Chart that might help test if China is recovering from the initial break out – Veg Oil imports demand on Palm Oil:


For further confirmation:


A chart that might have some clues to the impact of the virus outbreak in G-10 countries and recovery: Lets meet over a coffee??


All else being equal, influence of Short Term Interest Rates on US Exports – importers have to finance the US Dollar to pay exporters:


Identifying Price regimes:


From October discussion at NZX Singapore


Data auto reading and insertion from purchase settlement sheets

Every day, hundreds of financial documents are created within a commodity trading company that contain valuable information for decision-making purposes. One of the main challenges for commodity trading companies nowadays is how to preserve a huge volume of documents from being lost or damaged, accessing these documents and extracting information whenever necessary. Currently, many companies manually process their documents and extract the data through a manual data entry process that is slow, expensive, and less accurate. Therefore, there is an urgent need to develop computer-aided document processing with the use of Artificial Intelligence (AI).

Phlo Systems Ltd in partnership with one of the leading AgriCoop commodity traders in the US has recently developed an automated document-processing tool for commodity documents. The focus is on the purchase settlement sheet, which is used to settle receivables or payables created in a settlement request list for a customer. The developed tool combines sophisticated Machine Learning (ML) algorithms with Optical Character Recognition (OCR) to extract the text and organise key-value pairs in settlement sheets.

Through an OCR process, the scanned copies of settlement sheets are converted into a digital format and their text is extracted. Once the Process of OCR is complete, it is important to identify the corresponding field for the extracted text. For instance, if a block of text belongs to a specific table or it shows a value for total amount, subtotal, date of invoice, vendor name etc. For this purpose, the integrated ML algorithm takes the extracted text and matches the details such as contract information, type of commodity, vendor details, settlements details, assembly information, and ticket information. At the end, the extracted information is stored in a structured database on our Enterprise Resource Planning (ERP) system called Minerva in a retrievable format that is simply accessible and usable by the user. The beauty of this tool is of course the ability of the embedded ML to learn over time and provide an even higher accuracy for reading specific types of documents.


The major benefits of this tool are:

  • Quicker and smoother processing than manual human data entry

  • Full automation of document processing

  • Centralised storage location of information to prevent mistakes

  • Better document organisation and management

  • More detailed information extraction

  • Achievable accuracy up to 99%

  • Reduction of workforce up to at least 50%

  • Ease of accessibility and retrievability in the cases of dispute and decision-making

  • Customisability to other type of documents (i.e. Bill of Lading)

  • Learning ability of the ML algorithm over time to be even more accurate

Importance of Risk Management in the Commodity Trading Industry

With commodity supply chain management firms constantly being exposed to various risks that may lead to financial distress, Phlo Systems wants to emphasise how crucial risk management is for business success.


Risk Management is the process by which the value of the company is enhanced by improving the quality of earnings through prudent risk-taking and control of risk. It involves a constant trade-off between controlling risk and taking a risk in an attempt to enhance return.


A midsize commodities processing and trading firms face various types of risk in the course of its business activities in the upstream, supply chain and midstream segments. These risks can be broadly categorised as financial, operational and other risks. The company also faces the possibility that different risks may occur simultaneously (referred to as a ‘Dangling Participle Risk’), and the probability that the company is completely free from risk is very small given the wide range of business activities and geographies in which the company operates.


Full document here.

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