Key insights from mooncake festival at house of Jerry and Liza

Technology trends

  • Companies are increasing shifting their service from one-off on premise licensing deployment monetization to cloud based SaaS recurring subscription models
    • revenue hit in the short run
    • increased customer LTV in the long run
    • affected publicly traded companies will experience short term discounts to their shares
  • Artificial intelligence versus Augmented intelligence
    • companies are increasingly shifting away from automatic insight generation to systems that help decision makers simulate and model potential outcomes when specific policies are executed
    • demand is shifting from insight generation to data cleaning services
  • Corporate adoption of artificial intelligence
    • CEOs are increasingly considering how to leverage AI as a tool for their trade
    • primary use case is figuring out how to increase their sales volume
    • experiencing challenge on how to apply AI on in-house data to achieve monetization goals
  • Rise of deep vertical data networks
    • EverString – provides sales lead refresh for all client companies ends up becoming a large database for decision-making executives information, approximately 6 million records
    • – cleans up real estate data to help agents better price houses for sale by utilizing in-house agency ends up becoming a large database of high quality real estate data
  • Crypto-currency
    • Bit coin is still the main poster child
    • general population still skeptical about libra
    • main argument is still to remove central bank controls
    • main adoption hurdles
      • writing throughput volume
      • a stable store of wealth
      • starting to be using as a means to facilitate transaction in China
      • Inability to increase or decrease currency supply in times of need is going to be hard as a means to provide much needed stimulation during economic recessions and inflations

US/China trade war

  • sources of conflict
    • technology theft
    • forced technology transfer
    • unfair trade practices like subsidized state owned Chinese companies operating in the export markets
  •  economy
    • China is experiencing inflationary deleveraging
      • local farmers are not growing critical food sources
      • critical food supplies are imported
      • price of imported goods are denominated in US reserve currency
      • shifting of supply chain out of China to
        • Vietnam
        • India
        • Taiwan
      • capital flight
        • Li Ka Shing moved funds out from Hong Kong in 2013 to Europe
        • raising funds for US Venture capital from China was easy prior to Chinese and US government shut down
    • US is experiencing deflationary deleveraging
      • businesses are concerned about macro environment and are reducing fixed investments
      • manufacturing is slowing due to decreased demand both locally and overseas
      • consumer spending and confidence is still strong
  • Chinese domestic concerns
    • Potential US meddling in Chinese domestic affairs – Hong Kong’s demonstration and demands
      • Revoking of National Education
      • Revoking of extradition bill
      • Resignations of HK Chief executive
      • universal suffrage: freedom to elect their own leaders
    • destabilized situation presents a challenge for Xi JinPing’s party to retain control of power over former Jian Zemin’s faction
  • value system
    • US is a highly rule based system
    • China’s system of control is highly subjective to the individual in power.  Direct government intervention in the distribution of wealth is a major source of concern

US/Mexico and world issues

  • NAFTA agreement was too one side and failed to take into account large  imbalance between the two economies
  • US’s arrangement of allowing Mexican tax payers the right to claim dependents ultimately resulted into tax claims and refunds for entire extended families in Mexico. This has the effect of subsidizing Mexican’s at the expense of Americans living along the rust belts
  • Its observed income inequality is becoming prevalent across the entire world not just within US and China.

Related readings

Key insights from weekend with Jerry, Liza, Ada and Dan

On US/China trade war

  • 25% tariff basically wiped out whatever profit margin importing from China could bring
  • China’s labor cost have been increasing over the past few years that it is no longer a competitive advantage
  • China’s main advantage is the expertise they built up over the years. A company can easily spin up 25 manufacturing lines in China very quickly
  • US companies are all rapidly shifting their manufacturing activities out of China
  • New locations are Taiwan, India and Vietnam
  • Chinese staff that were retained by Google are now flying to new manufacturing facilities spun up in these countries to oversee the spin up process

On alternate data

  • Real estate
    • the rise  of platforms like AirBnB has lead investors to seek out alternate data that can help predict short term rental yield as opposed to long term rental yield in a neighborhood
    • government agencies are seeking such data to detect neighborhoods where they should focus their efforts to crack down illegal subletting on AirBnB
  • Sports
    • being able to predict strategy coaches of football teams will employ in real time will help support strategies
    • being able to predict starting line in close to real time and the corresponding outcomes will be valuable for coaches in making play decisions

On HongKong/China protest

  • Public opinion is the agenda for the ongoing protest is now getting really murky
  • Airport has stopped operations, it’s hard to even get in and out of the country
  • Foreign Chinese nationals are supportive of protest in HongKong
  • Topics pertaining to Taiwan, Tibet and TianAnMen massacre are sensitive topics amongst mainland Chinese
  • Funds of funds from Hong Kong are still very liquid

Reflections of erroneous trading over the past 48 hours

Market has been pretty volatile in the post and pre market hours. Been automatically buying into the maximum possible over priced positions during the non-market hours or immediately at the start of market.

Rectified action

When buy signal is generated during the prior day in 3 month time frame

  • Company operates within my circle of competence
  • RSI was ever less than 30 during this period of dip
  • MACD has crossed over positive
  • $.VIX is below 15

To mitigate intraday noise, enter into position in the last hour of the trading day, between 1130am to 1pm period when market prices have stabilized for the day and the spreads are narrow.

To stop the practice of programming trading action into system the prior night.

Ok to skip buying into position if price has advanced above buying range. It’s much better to have erred on omission than to have erred on mis-execution.

Related references

Book summary: The Asian Financial Crisis by Shalendra Sharma

This book describes how the 1997 Asian Financial Crisis transpired.

Impacted countries

  • South Korean
  • Indonesia
  • Thailand
  • Malaysia
  • Singapore
  • Hong Kong
  • China

Key lessons

  • Only 2 of these three conditions can be allowed to be true without causing inflationary recession
    • Fixing the currency exchange rates against other reserve currencies
    • Control over domestic interest rates
    • Control over capital inflow
  • On foreign capital flows
    • huge volume of foreign capital flows into a country
      • economic growth rate increases
      • inflation rate stays low
    • huge volume of foreign capital flows out of country
      • economic growth rate decreases
      • inflation rate goes up

Common pattern across countries

The build up

  • Long periods of high export lead GDP growth attracts high levels of foreign investments. Huge volume of foreign funds originated from Japan which was having a very loose monetary policy
  • Countries peg their exchange rates to reserve currency to ensure stable prices for both imports of raw materials and exports value added products
  • Countries currencies are not reserve currency, hence foreign loans were denominated in foreign currency
  • Excessive leverage within the country by domestic parties who take on short term loans denominated in foreign currencies at lower interest rates to finance long term projects that generate returns in domestic currencies
    • Stocks are purchased with borrowed money. These stocks are then further used as collaterals to borrow more money
    • Real estate are purchased with borrowed money. These real estates are then further used as collaterals to borrow more money
  • Moral hazard due to corruption of financial system
    • banks are arm twisted to finance projects that are not financially viable by governments and politicians

The economic headwinds

  • countries face increasing export market pressure
    • Competition at the low end of the export markets from China
    • Competition at the high end of the export markets from Japan
  • Japanese government instructs central bank to tighten monetary policy to reduce real estate. This severely restricted liquidity from Japan and reduced availability of short term foreign loans to affected countries

The crash

  • Borrowers within these countries increasingly experienced difficulties rolling over their foreign denominated short term loans to finance their long term illiquid domestic projects
  • Many of them started defaulting on their loans
  • Foreign investors started getting spooked and started withdrawing their funds or refusing to allow their loans to roll over
  • Non-performing loans builds up amongst banks within these countries
  • Capital flight continues causing downward pressure on the exchange rates of these countries
  • Countries continued defending their exchanges rates by buying up their own currency and selling off foreign reserves (assets held in foreign currencies)
  • Countries deplete their foreign reserves and are unable to uphold their exchange rates. Since most debts are denominated in foreign currencies, they are not able to print money to pay off these loans.
  • The economy grinds to a halt and hyper-inflation occurs within their financial system at this point
    • domestic production stops and locally produce foods is no longer available for sale
    • due to shortage of foreign reserves imported products become very expensive in local currency
  • Countries approach IMF for loans to tide through this liquidity crunch.
  • IMF steps in and with a lack of understanding of the economic patterns imposes these requirements:
    • Countries required to impose high domestic interest rate. It has the effect of further reducing the money supply within these countries causing more defaults domestically.
    • Countries will reform the financial systems to remove cronyism lead financing
  • Riots ensures and Anti-establishment governments get elected in some countries

The recovery

  • IMF releases the misstep in policies and relents
    • Countries lower their domestic interest rates to increase liquidity within their financial system
    • Countries allow their exchange rates to float freely
  • Relatively cheap asset prices within these countries starts attracting foreign investments again

Afternoon with Tomasso on the limitations of Artificial intelligence’s application

For us to be able to successfully apply artificial intelligence on any domain, the following needs to be true

  • The behavior the system to be modeled must not be stochastic
  • The state of the system must be decipherable by the data scientist
    • it should be possible to understand the state in which the system is at through interpretation of data gathered
  • The domain can be modeled
    • the parameters for modeling the domain must be well defined

Only when all three premise are true can we determine where the adjustment should be made when a model fails to predict an outcome

The financial markets is stochastic  in the short run.

The underlying parameters are constantly changing and thus hard to model due to the emergent nature of impacts caused by human activities. The data is qualitative and thus hard to convert into clean quantitative datasets.

While the price movements are obvious it is hard, it is hard to attribute impact to the various parameters.

As such, it requires human neural networks that consumed all these qualitative data to perform the prediction/decision making.

Why banks are trading at or below net book value

After the 2008 financial crisis, legislations like the Volcker Rules to inhibit big banks from behaving like hedge funds. They are no longer allowed to engage in any forms of trading or financial innovation which leads to excessive multiplying of money supply leading and excessive leveraging within the banking systems.

Their income is thus restricted to investment banking commissions and net interest incomes.

Related references

Long-Sought Volcker Rule Revisions Land on a Changed Wall Street

Book summary: The Savings and Loan Crisis – Lessons from a regulatory failure

This book documents the series of regulatory missteps from the 1980s to the 1990s that lead 50% of savings and loans in the US to insolvency. During this period the total number of savings and loans decreased from 3,234 to 1,645.

Operating mechanism

The savings and loans are a special group of banks that are encourage to grow by the US government to enable affordable housing after the world depression.

They take in short term savings deposits at lower interest rates and lend out long term mortgages at higher interest rates. They profit through the net interest income generated between the short term interest rates and the long term interest rates.

Events leading to massive failure

  • During the Vietnam war, inflation which drove short term interest rates increase. This cannibalized SnLs’ profit margins.
  • De-regulation of short term interest rates which lead to increased competition by other banks for deposits.  This lead to the inability to attract deposits at feasible rates to finance SnL’s long term illiquid mortgage loans.
  • The US government instead of recapitalizing these insolvent SnLs opted to de-regulate by allowing them to enter into other high yield investment instruments. This is in hopes of they will be able to rebuild the capital and thus minimize the amount of burden to be imposed on tax payers
  • Entrance of new entities
    • mutual funds competed for deposits
    • Freddie Mae and Freddie Mac competed for mortgages
  • SnLs ventured out of their areas of expertise and started buying into high yield corporate junk bonds and unsecured commercial loans.
  • With minimal equity stake in the game due to years of erosion and an implied government guarantee for a bail out in case things go south, SnLs began aggressive leveraged into these positions.
  • The US government reversed it stance and past regulation against SnLs holding high yield investment instruments. The forced liquidation of relatively illiquid positions further exacerbated the situation.

Lessons learned

  • Government meddling in market mechanism to further political agenda is generally a recipe for disaster
  • Venturing beyond circle of competence in search of high yield is generally a recipe for disaster
  • Overt or implied guarantee of government bail out is a source of moral hazard that leads to excessive leverage by operators which is definitely a recipe for disaster

Book summary: Barbarians at the gate by Bryan Burrough and John Helyar

This book documents the series of events leading up to the successful leverage buyout (LBO) of RJR Nabisco.

Mechanism of an LBO exercise

  • Figure out the cheapest possible price to acquire the asset and its future cashflows while keeping transaction costs low
  • The acquisition team access the business to decipher potential cashflow, areas for cost savings and parts that could be sold off
  • The acquisition team raises private money to do the acquisition
  • During this period of time bandwidth of law firms and banks are fully engaged
  • Competing offers should be expected once a public announcement of an LBO buyout is made
  • Law firms and investment banks will charge fees even if the hiring party does not win the bid

Methods for financing an LBO exercise

  • issue of junk bonds
  • raising from private investors
  • issue of shares to directors to drive down level of cash required for the purchase
  • payment through cash
  • utilization of legal loop holes to reduce taxation on the LBO transaction

Motivations for an LBO exercise

  • The management team:
    • a option to exercise when the market is persistently undervaluing the shares of the business
    • free up value to reward themselves and their share holders
    • the CEO being the typical Type A personality got bored and restless from running his day to day business
  • The investment banks:
    • when the market is down but they still need to figure out ways to make money through business transactions
    • some needed an opportunity to enhance their prestige so as to attract future opportunities. Securing a prominent position in the transaction has that effect

Lessons from the LBO exercise

  • The inability to sit in a room and doing nothing is the source of most trouble.
    • The CEO ended off worst off than he did before the LBO event
  • Having inside support matters
    • Having support of the management team provides knowledge of where cost savings could be had in the operations
  • Just when you think shit will not happen, it usually does.
    • The management team was expecting an uneventful transaction. Unfortunately, the operation quickly escalated out of control when competing bids surfaced.
  • When money is cheap, Wall street gets creative
    • the Federal reserve provides cheap money which cannot be put to real economic use, LBO is just another method Wall Street utilizes to make a profit from this cheap money
  • When egos start getting involved, its no longer about making a profit
    • the successful acquirer ended up defaulting on a lot of the junk bonds issue
    • what started as an initial USD76/share bid quickly escalated to USD106/share
  • When an opportunity as large as this becomes available, the services of lawyer firms and bank credit becomes scarce and it is hard to gain access to such facilities as a new comer to the table
  • Companies actively manage Wall Street expectation
    • RJR Nabisco actively engaged in wasteful activities to project a steadily advancing year over year profitability and thus share price. It could have operated efficiently and have the share price reflect the actual value on day one
  • The core business will falter overtime when the operators get distracted by other activities and are no longer engaged and connoisseur of their own products
    • early employees of Reynolds cigarettes are themselves enthusiast smokers. They released a new product only when it passes their own taste test
    • later management were focused on milking the cash cow and started changing the culture as such
  • Negotiation dynamics
    • the senior financiers will generally play the diplomat (good cop)
    • the junior and middle level financiers will be in charge of hashing out the details (bad cop)


Key lessons from When Genius Failed by Roger Lowenstein

When Genius Failed
When Genius Failed, Roger Lowenstein


This book documents the rise and fall of Long Term Capital Management. A hedge fund that specializes in government arbitrage

LTCM’s trading methodology

  • Yield for bonds of the same length of maturity with the different maturity dates issued by the US treasure will tend towards each other over time.
  • Bond’s past a specific time frame becomes less liquid hence gets discounted by fund managers
  • leverage up to 30X capital to short the over bought bond and long the over sold bond, essentially making the difference with little capital employed

Causes for LTCM’s failure

  • becoming overly reliant on their models
    • a period of continuous credit spread widening was followed by the Russian government bond default. LTMC continuously doubled down on their position assuming the trend would eventually reverse
  • not taking into account that unlikely long tail negative events. When they occur the impact tend to be very large
  • Excessive use of leverage
    • up to 30X as compared to 20X employed by most hedge funds
    • made possible by FOMO of all banks who were eager to profit by extending credit lines
    • partners borrowed money from banks using securities they own within the firm as collateral
  • The margins of any profitable trading methodology will tend to get eroded overtime as big banks start tapping into the same opportunities
  • Stepping beyond their circle of competence and expecting the same methodology to still work with international bonds
    • assuming political dynamics overseas (Russia) will be the same as within the US
  • banks unloading sections of their portfolio likely to be impacted by LTCM’s position after news of LTCM’s funds and positions they hold further exacerbated their problem
  • Winding an extremely large position is extremely difficult
    • not enough liquidity
    • will negatively impact price

Lessons for LTCM’s failure

  • guard against hubris / overconfidence
  • be self aware of your circle of confidence and staying within it
  • always check for faulty assumptions in your reasoning
  • avoid excessive use of leverage
  • monitor for long tail events that are emergent by nature
  • do not double down on any positions that did not performed up to expectation
  • guard information about your trades tightly
  • be wary of entering into positions with little liquidity
  • If your fund gets into trouble and you owe the bank a small amount of money its your problem, but when it is an extremely large amount of money it becomes their problem

Insights from evening with Wine and Jam session with Adriene and Dennis, Birthday party with Konstantine

From Tommaso on Machine Learning – Economics

  • Study was done on Italy
  • Voting patterns can be leading indicators for credit spread
  • When a political party is stable, Eigen distance between votes of party members will cluster together, even for bills that are not critical for parties
  • When a political party becomes unstable, the Eigen distance between vote on non-critical bills by party members will increase
  • Alignment will increase before a wild swing to misalignment
    • periods of high alignment leads to very tight credit spread
    • tight credit spread indicates a very high price for bond
  • Misalignment will decrease before consolidation towards alignment
    • periods of low alignment leads to very wide credit spread
    • wide credit spread indicates a very low price for bond
  • proposed strategy:
    • when alignments increase, short bonds in anticipation for forthcoming misalignment
    • when misalignments increase, long bonds in anticipation for forthcoming alignment

From Tommaso on Machine Learning – Micro-biology

  • Started studying how presence specific bacteria affects health at an aggregate level
  • Studying ancestral tree of bacterias help estimate the distribution of bacteria in the gut of different individuals

On sales

  • Mormons are one of the best sales people due to their coming to age ritual.
  • They typically will get rejected many many times during their passing through rite

On human cyborgs

  • Neil Harbisson is an artist who is color blind, he implanted a device into his brain which allows him to see colors

On hardware and biotech with Andrew

  • To design printed circuit board install IDE which allows easy assembly, simulation and coding – DesignSpark
  • Firmware for micro-processors are written in C. Firmware controls where signals are past to when incoming signals are received
  • Micro-processors are installed on circuit board
  • Can be printed in China and shipped over in 5 days – PCBWay
  • BioCurious and another biotech hacker space up in Berkeley have managed to train yeast to product cocaine and THC

Related readings