Global Economics
Every year I grow up a little bit – surprise surprise, as we all should – and what follows is that every year I realise how little I know and understand about the way we’ve engineered the world to work.
In this particular scenario, I mean more from an economic perspective than anything, as arguably, the economic machine and its peculiarities, cycles, and interdisciplinary nuances is what keeps the world working. I am slightly peevish to admit that my interest in understanding all this began at the age of 23 in the final year of my Masters of Engineering degree. Let us not even mention that moving across the world at 16 from Missouri to Singapore and living with an aunt who was a globally renowned transaction bankers didn’t do the trick to ‘get the ball rolling’. However, it’s better late than never, and here I am, enrolled in a Global Economics course at Imperial delivered by the lovely Igor Baranov… only now understanding the relationships between interest rates and inflation 😳.
The real funny part of this story is in the true motivation for my understanding: money. In the scramble to find a post-grad job (with a salary that satisfies my love for travel, food that I can’t cook at home, and London rents), I began applying for some of the typical roles in finance, consulting, etc. In doing this, an inherent part of interview preparation is to comprehend and comfortably speak about what is going on in the world, and how it will impact different industries. What I realised then was how little I thought about economics in the day to day, and when I tried analysing the news I was reading and the conversations I had from that perspective, how hopeless I was.
Here is a google document of my running notes and various sources I have collated throughout the economics module so far, and here is a fun presentation we prepared for a debate on currency pegging within emerging markets.
In terms of markets specifically, I have also included some notes in the basics of understanding how they work, in preparation for a final-round Jane Street interview which I did not pass.
Order Book
Market orders execute at the most competitive price (whether you are buying or selling)
If you sell a certain number of shares, this will be reflected in most competitive bid
If you buy a certain number of shares, this will be reflected in most competitive ask
Market orders are guaranteed a trade, but not a price
Limit orders execute at a specified price (whether you are buying or selling)
Orders either cross and sell immediately, or sit in the book until matched
Will execute with the best available price when transacting
More buy orders than sell orders indicates demand (buying pressure) is high and suggests that prices of stock will increase
More sell orders than buy orders indicates demand low with excess supply and suggests that prices of stock will decrease
Characteristics of markets
The smaller the spread, the more liquid and efficient the market is
More liquidity means more market depth and more efficient means orders are transacting close to the price at which buyers want to buy and sellers want to sell
Depth (can be seen as number of orders in a book) is important to keep market stable, and to be able to accept large orders without increasing the volatility of an asset
Best ASK is the lowest price at which a participant is willing to sell
Best BID is the highest price at which a participant is willing to buy
Arbitrage is different from market making because it does not add volume, but to profit from price differences between markets
Higher interest rates can impact the stock market negatively as people are more incentivised to save, or at least invest in things like government bonds and treasuries
Market makers
Open a position that doesn’t match an existing bid or ask on the market
Create a new order, and add volume to the market
Try to buy at lowest prices and sell at highest prices
Receive a premium from exchanges and other participants to keep a constant supply of liquidity in the market
Profit comes from spread
Wider spreads are a protective measure for market makers, they can have the side effect of reducing liquidity and increasing trading costs (risk management, reflects uncertainty and difficulty in price discovery)
If market price is within range of the positions, the market maker earns the margin reprinted by the spread
Do not directly match trades for external investors, but are constantly providing bid and ask prices to keep liquidity in the market and make sure that an investor’s trade can always be executed
Minimise the impact of large orders which can significantly shift prices before trade is execute (HFT helps with this)
Dark Pools, information not on exchange
Batches of hidden orders usually made by large players that don’t want their intentions known to other participants
Without these, exchanges would see significant price devaluation
When info “leaked” about a big transaction by a large institution before execution it usually leads to a drop in price of the security
Large institutions can make deals without exposure, the new data comes to light after transaction and has less impact on the market
Scrutinised for illegal front-running, when institutional traders place their order in front of a customer’s in order to profit on the uptick in share prices
Morgan Stanley’s pool, Goldman Sachs’ Sigma X, Bloomberg Pool
Hedging
A way to protect against volatility and risk in a market
Hold a lot of shares in Stock A (has been doing well, but impending uncertainty due to whatever reason)
Can use options contracts or future contracts to hedge against this risk
If Stock A is trading at $100, can use a put option at $95. If Stock A’s price falls below $95 then options will increase in value, while if it stays above $95, the investor only lost the ‘cost of the hedge’ or the premium paid for those options
Options
Options are financial derivatives that give the buyer the right, but not the obligation, to buy (call option) or sell (put option) an underlying asset at a specified price (strike price) on or before a certain date (expiration date)
Can protect portfolio against loss in value if a stock does significantly devalue
Futures
Futures contracts are a type of financial derivative that obligate the buyer to purchase, and the seller to sell, a specific asset at a predetermined future date and price
Used a lot in commodities and finance to manage risks related to price volatility
Can be used to lock in good prices, but the risk is always prices dropping and being locked into a higher price
Futures markets provide a lot of insight to people’s expectations of future prices, which can help with trading strategy
Price discovery
Process through which the market determines the price of an asset
Interaction of buyers and sellers and their trading activities leads to an equilibrium price that reflects perceived supply and demand (and value)
Market makers provide continuous quotes based on their own information
This provides liquidity so there is always a price available for a security
Sophisticated means of analysing market data and news, which is reflected in their pricing decisions
Arbitrage can help align prices across markets which makes price discovery more efficient and accurate
Business Strategy
Using their own capital to trade (proprietary)
Making sure analysis of market inefficiencies is top
Being always able to provide liquidity to facilitate smoother transactions for participants
Exploiting price discrepancies and arbitrage
Heavy investment in tech and talent
Risk management is huge!
Stress testing: using historical data and models to simulate different scenarios, such as crashes
Position limits: don’t want too large of a position, make sure portfolio is balanced (eg 5% position limit for any single stock means that no more than 5% of total investment portfolio can be in that specific stock)
Staying on top of regulation and compliance to avoid legal risk
Take advantage of global markets and opportunities across geographies
Different regions, regulations, time zones, and markets
Global data centres, secure communications, trading platforms
Limit Up Limit Down (LULD)
Using previous day closing price better: more stable, closing price more representative, not everyone participating in the morning and can lead to
Dynamic reopening auction collars: adjustable, as opposed to fixed % price ranges, and updated in real time to better reflect market conditions (wider in more volatile times, otherwise smaller)
A way to balance the transition back to continuous trading after a halt while still preventing excessive price movements
Harmonising amongst exchanges so that price discovery is more efficient
Don’t break trades that occur within the collars, which is comforting for liquidity providers but also slightly concerning if some trades were clearly erroneous and weren’t reversible
Futures-style regime: instead of halting trading during volatility, there are price limits that prevent trading at prices beyond certain thresholds, but without complete pauses.
Give market participants a time to assimilate more information
ETF
Equal weighted ETFs (each underlying asset that the ETF represents has equal weighting) would be likely to experience more volatility in a flash crash because of their design, they don’t have the buffer that a market-cap weight ETF (weighting is based on the total value of all company shares of a stock) has with larger companies absorbing market shocks better and retaining more liquidity. Giving assets with smaller market caps a larger weighting in an ETF than they would otherwise have can make the whole ETF more prone to volatility and liquidity issues, especially in times of distress
ETFs representing more stable assets such as gov bonds would be more stable in a flash crash. Also possible that those tracking consumer staples, utilities and other similar stocks would experience less volatility (these goods and services remain in demand regardless of economic conditions). Otherwise just those with large and stable investor bases giving them high liquidity and protecting from panic response.
