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

Overview

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

Insights from lunch with Andrew and Paul

On trading

  • learn to read technical charts
  • price and volume reflects all necessary sentiment and information
  • Read the charts in different time frames with gives a sense of various impacts have on pricing trends
  • news happen after the fact which drives emotions like fear. When the brain is overcame by fear irrational behavior results.
  • charts remove the emotional component

On news and propaganda

  • All news are forms of propaganda best avoided or taken with a pinch of salt.
  • It is hard to trace much major change in life to any specific news occurrence
  • news is less about facts but more a reflection of the reader’s attitudes and belief toward the subject receiving coverage
  • how is it that US news sites are able to report on a country like North Korea where no information is available externally? Are the gaps mainly filled in by US propaganda

On education

  • its hard to be an educator in the US.
  • There is too much regulation
  • Students are not as motivated compared to students in other countries

On the environment

  • Three hundred chemical components are found in donated blood that are not supposed to be there
  • climate change is a major concern
  • capitalism driven consumerism is not sustainable

Related readings

  • Slow death by the rubber duck

Macro economic extension to loss aversion reversion to mean trading methodology – Government versus Government scenario

Trading Heuristics

Chain of events and decision making

The decision making processes from June 2019 after the federal reserve signal likelihood of cutting interest rate leading up to the 2019 August downward mean reversion of the SnP.

19th June 2019, Federal Reserve signals for first time likely decrease of interest rates

Federal Chairman expresses concerns about potential cross winds caused by US trade policies and its impact on their dual mandate.

10th July 2019, news paper reports SnP reaches all time high

SnP on the cusp of crossing 3000 threshold for the first time to an all time high. Market is euphoric. Trade issue between US/China yet resolved but discussions are underway.

Short positions SQQQ and SRTY were utilized as hedges against downward macro environment reversion risk when the SnP extended beyond 3000 to reach an all time high

1st August 2019, US announcement of 10% tariffs on US300 billion imports from China starting September 2019

on 1st August, 24 hours after actual interest rates cut, Trump signaled 10% tariffs on USD300 billion Chinese import. SnP dropped.

Exited SQQQ and SRTY for 10% capital gain after reaching 30SMA and 50SMA range. Net combined loss to portfolio was 0.5%.  Left remaining long positions open.

4th August 2019, Chinese response

On 4th Aug 2019, China’s exchange rate dropped for the first time below 7RMB/1USD.

5th Aug 2019 trading day

On 5th Aug 2019, China announced they will halt all imports of agricultural goods from US.

Portfolio continued declining an additional 2% on the trading day of 5th August 2019.

Closed all long positions with the exception of REITs

Decline overview

  • SnP
  • REITs
  • Value shares
  • Growth shares

6th Aug 2019 trading day

On the evening of 6th Aug 2019, China announced decision to control fluctuation of RMB exchange rates to USD

Bought into TQQQ and URTY at below 30SMA and 50SMA

7th Aug 2019 trading day

TQQQ and URTY automatically exited at the mid point between the two following highs and lows:

  • highest point  before Trump’s tariff announcement came into effect
  • lowest point after China’s halt on US agricultural imports and RMB/USD breaking 7 came into effect

Related readings

Donald Trump’s August 1st 2019 tweet on additional tariffs

Highlights

  • The effect of a negative shock is 3X worst that the effect of a disappointment
  • The effect of a negative shock is longer lasting than the effect of a disappointment
  • The market does retain memory of prior states
  • Seems like each negative political macro event has approximately negative 3% impact on the SnP

Series of events

Wednesday, 31st July 2019, 2pm, US Federal Reserve’s disappointment

  • Federal Reserve announced an interest rate cut of 0.25% from 2.5% to 2.25%
    • no hints of further cuts
    • before announcement SPY price 300.04
    • after announcement SPY price 296.98
    • net effect on SPY -1.02%

Thursday, 1st Aug 2019, 10.26am, US President’s negative shock

  • President Donald Trump announced additional 10% tariffs on remaining 300 billion imports from China on Twitter.
    • before announcement SPY price 300.45
    • after announcement SPY price 291.02
    • net effect on SPY -3.14%
    • SPY price still above the 7th June 2019 price of 288.97 when the effect of Fed’s hint to adjust interest rate cuts has been priced in.

Sunday, 4th Aug 2019, 6.20pm PST, China exchange rate sinks below 7CNY/1USD for the first time

Monday, 5th Aug 2019, 9.58am PST, China suspends purchases of US farm products

  • US Market takes a sharp dip on Monday
    • SPY price 281.90 at lowest point
    • net effect on SPY -3.13%

Monday, 5th Aug 2019, 5.27pm PST, China announces fix to prevent further RMB depreciations against the USD

  • US market rebounds
    • SPY price 293.55 at highest point
    • net effect on SPY 4.13%

13th Aug 2019 Trump announces delay of tariff

  • US market rebounds
    • SPY price 292.32 at highest point
    • net effect on SPY 1.91%

14th Aug 2019 UK and US 2 years / 10years yield curve inverts. Germany reports GDP shrinkage for 2019Q2

  • US Market takes a sharp dip
    • SPY price 284.20 at lowest point
    • net effect on SPY -2.77%

Related artifacts

Trump’s tweet on additional 10% tariffs at 1st Aug 2019, 10.26am PST
Chinese RMB crosses 7RMB/1USD for the first time on 4th Aug 2019, 640pm PST

Related readings