lecture 8: High-Frequency Trading, Temporal patterns & Cycles Flashcards
Market Making
an activity where a firm’s trader stands ready to buy and sell a particular stock on a regular and continuous basis at a publicly quoted price on a listed exchange
What is High Frequency trading (HFT)
It is a type of trading using computer algorithms to rapidly trade securities
characterized by high speeds, high turnover rates, and high order-to-trade ratios using specialized order types, co-location, very short-term investment horizons, and high cancellation rates of orders
uses market making and proprietary trading strategies carried out by computers to move in and out of positions in milliseconds with high volumes and high speeds aiming to capture sometimes a fraction of a cent in profit on every trade using insignificant amounts of capital.
–> Given the short holding periods, HFT can potentiallyachieve Sharpe ratios tens of times higher than traditional buy-and-holdstrategies
HFT firms perform “Market making” activities using what?
a set of high-frequency trading strategies that involve placing a limit order to sell (or offer) or a buy limit order (or bid) in order to earn the bid-ask spread
–> By doing so, they provide a counterpart to incoming market orders
are HFT firms under obligation to maintain this activity during periods of extreme volatility?
no
Impacts of HFT on liquidity
HFT has led to a reduction in bid-ask spreads and an increase in trading volume
However, trading volume and narrower bid-ask spreads may not be a reliable indicator of liquidity during times of significant market volatility
Impacts of HFT on volatility
More aggressive HFT strategies may increase stock volatility
HFT Liquidity detection strategies “front run” ahead of large institutional orders amplifying price swings
Front running
illegal practice of having knowledge of your client’s orders and executing your own orders first
impacts of HFT on price discovery
Although HFT strategies are very rapid helping prices be more efficient to reflect new information in the short term, their effect on long term price discovery is less clear
HFT strategies are agnostic to a company’s fate and intrinsic value
Zhang (2010) shows that HFT hinders long term price discovery
impacts of HFT on market confidence
Sophisticated “Algo” strategies and access to dark pools used by HFT firms give them an advantage over regular investors
Market events such as the flash crash of May 6, 2010 erodes confidence and create disincentives for individuals to invest in the market
Led to some market participants believing that the “markets are rigged,” with HFT having an edge at the expense of investors
impacts of HFT on market confidence
Sophisticated “Algo” strategies and access to dark pools used by HFT firms give them an advantage over regular investors
Market events such as the flash crash of May 6, 2010 erodes confidence and create disincentives for individuals to invest in the market
Led to some market participants believing that the “markets are rigged,” with HFT having an edge at the expense of investors
impacts of HFT on market confidence
Sophisticated “Algo” strategies and access to dark pools used by HFT firms give them an advantage over regular investors
Market events such as the flash crash of May 6, 2010 erodes confidence and create disincentives for individuals to invest in the market
Led to some market participants believing that the “markets are rigged,” with HFT having an edge at the expense of investors
positives of HFT
HFT has made markets more liquid and decreased transaction costs
negatives of HFT
Traders who post standing limit orders that cannot reflect changes in value due to news changes fast enough and lose to HFT (certain order types are bait to HFT)
negatives of HFT
Traders who post standing limit orders that cannot reflect changes in value due to news changes fast enough and lose to HFT (certain order types are bait to HFT)
negatives of HFT
Traders who post standing limit orders that cannot reflect changes in value due to news changes fast enough and lose to HFT (certain order types are bait to HFT)
negatives of HFT
Traders who post standing limit orders that cannot reflect changes in value due to news changes fast enough and lose to HFT (certain order types are bait to HFT)
negatives of HFT
Traders who post standing limit orders that cannot reflect changes in value due to news changes fast enough and lose to HFT (certain order types are bait to HFT)
negatives of HFT
Traders who post standing limit orders that cannot reflect changes in value due to news changes fast enough and lose to HFT (certain order types are bait to HFT)
straight up illegal impacts of HFT
HFT traders front run traders who are working large orders, making their trades more expensive.
–> Quote matchers profit from standing limit orders by trading ahead such orders by improving prices slightly
Dark Pools
Private exchanges not accessible to the public, usually owned by a broker-dealer named as such due to their lack of transparency
Dark Pools
Private exchanges not accessible to the public, usually owned by a broker-dealer named as such due to their lack of transparency
HFT are engaged in a technology arms race by employing faster computers, locating servers closer to exchanges (co-location), using algorithmic code, employing many types of orders and paying for high speed data feeds and dark pool access and being faster by milliseconds
Markets need to be slowed because fast HFT will make slower HFT go out of business, and this decreased competition will make the few firms in business increase spreads and thus transaction costs will rise making it more costly for all participants
Algorithmic trading by HFT poses systematic market risks; flash crashes, algos out of control, market terrorism in the wrong hands (Market volatility has increased since the proliferation of HFT)
CYCLE ANALYSIS
attempts to find recurring major and minor peaks and troughs in price movement for better trade timing
By adding short, medium and long term cycles together the actual price activity can be forecasted.
CYCLE ANALYSIS
attempts to find recurring major and minor peaks and troughs in price movement for better trade timing
By adding short, medium and long term cycles together the actual price activity can be forecasted.
left or right translation
when a market is trending, the cycle peak tends to shift left or right depending on the direction of the larger trend
–> usually, In a trading range, cycles are fairly regular in that the market peaks half way through the cycle
left or right translation
when a market is trending, the cycle peak tends to shift left or right depending on the direction of the larger trend
–> usually, In a trading range, cycles are fairly regular in that the market peaks half way through the cycle
left or right translation
when a market is trending, the cycle peak tends to shift left or right depending on the direction of the larger trend
–> usually, In a trading range, cycles are fairly regular in that the market peaks half way through the cycle
This is consistent with the notion that in rising markets, prices should spend more time going up and in falling markets prices should spend more time going down
2 ARGUMENTS AGAINST THE CYCLE CONCEPT
If prices behaved in pure cycles, like radio waves or tuning forks, the numbers would easily fit into mathematical formulas that would give us precise predictions similar to what we know about ocean tides and sunrises. This has not happened.
We have been unable to identify causes of specific cycles that many agree do exist in prices.
The three qualities of a cycle
AMPLITUDE
PERIOD
PHASE
AMPLITUDE
measures the height of a wave from peak to trough signifying the strength of a cycle
measured from TROUGH TO TROUGH as the tops tend to take more time to develop. Bottoms are more easily defined
The PERIOD (length) of a cycle
the time spent between troughs
AMPLITUDE
measures the height of a wave from peak to trough signifying the strength of a cycle
how are cycles measured
measured from TROUGH TO TROUGH as the tops tend to take more time to develop. Bottoms are more easily defined
how are cycles measured
measured from TROUGH TO TROUGH as the tops tend to take more time to develop. Bottoms are more easily defined
There are four important principles to cycles:
SUMMATION
HARMONICITY
SYNCHRONICITY
PROPORTIONALITY
SUMMATION
holds that all price movement is a simple addition of all active cycles
By combining each cycle & projecting forward, future price targets can be forecast
HARMONICITY
means that there are waves within waves and that they are usually related
Adjacent cycles are often related by small whole numbers (usually 2 – sometimes 3), there is a constant ratio applied to cycles
SYNCHRONICITY
refers to the tendency for waves of differing lengths to bottom at the same time
PROPORTIONALITY
describes the relationship between cycle period and amplitude
Longer-term cycles (cycles having a longer period) should also have greater amplitude
There should be a proportional relationship between cycles of differing period
–> For example, if a cycle’s period is 40 days, it should have proportional amplitude that is 2x the amplitude of a cycle that has a 20 day period.
VARIATION
states that the principles stated above are just strong tendencies and that they are not hard and fast rules. Some ‘VARIATION’ does occur
NOMINALITY
states that there tends to be a nominal set of harmonically related cycles that affect all markets
TRANSLATION
The reason that we study lows in cycle analysis is because longer and shorter cycles tend to synchronize at their lows.
–> Peaks, on the other hand, almost never synchronize.
Peaks should occur at the halfway period of the cycle.
–> For example, a 20 day cycle should have a peak 10 days from its last low. This rarely happens. (Coincidentally, this is the reason that we use the more stable trough to record our cycle lengths.)
—-> Peaks can occur earlier or later than the halfway point. Their location away from the center point is called TRANSLATION.
A RIGHT TRANSLATION
when the peak is beyond the halfway point
If the trend is up (BULLISH) the cycle is said to translate to the RIGHT
If the peak had occurred at the halfway point, we would be suspicious about the continuation of the uptrend
A LEFT TRANSLATION
when the cycle peak occurs before the halfway point
If the trend is down (BEARISH) the cycle is said to translate to the LEFT
An INVERSION
occurs when a peak occurs where a cycle low is expected.
Are economic phenomena that are not necessarily observable in commodity and stock prices. The theory that western capitalist economies have 50 – 60 year boom periods followed by a bust. (economic expansion followed by a depression)
The question asked in 2008/9-were we due for a depression?
KONDRATIEFF WAVES (K-WAVES)
Each wave is broken down into 4 seasonal periods (approx. 15 years each) with discernible characteristics:
Winter: a period of concern, fear, panic, depression
Spring: a period of fear of depressio4 n, fragile confidence
Summer: a period of growing confidence
Autumn: a period of increasing confidence, that turns into extreme confidence and euphoria
34 YEAR HISTORICAL CYCLES
Historical data suggests that 34 year cycles, composed of 17 year period of dormancy followed by a 17 year period of intensity, also appear to exist
FOUR YEAR or PRESIDENTIAL CYCLE (KITCHIN CYCLE)
The National Bureau of Economic Research showed that from 1796 to 1923, the US economy suffered a recession on average every 40 months or approximately every 4 years.
Some have argued that this follows the four year presidential cycle, but this phenomenon occurs in countries that do not have presidential elections every four years.
Today the four year cycle, from price bottom to price bottom, is the most widely accepted and most easily recognized cycle in the stock market. Occasionally it strays from four years, but only by a portion of the year.
Tops sometimes fail to occur as regularly as the bottoms do. They may occur before or after when their 4 year period would occur.
ELECTION YEAR PATTERN
Stock market returns can be related as a function of the US presidential electoral timeline.
Equity markets are:
weak during the POST ELECTION & MID YEAR (Years 1 & 2)
strong during MID YEAR 3 and PRE ELECTION YEAR (4)
SEASONAL PATTERNS
Are most apparent in agricultural prices and commodities such corn, hogs and oil.
–> This relationship is beginning to wane due to global trade
Allows the investor to profit from certain price trends that occur year after year. Though the price levels and the extent of their moves may vary – we can expect certain commodities to increase and decrease at certain times of the year.
–> For example:
Orange juice contracts have been profitable 74% of the time over the past 35 years for short trades to be initiated on June 4 and closed on July 1.
‘Sell in May and go away’
an old stock market adage that refers to the tendency for the stock market to decline from May to September and rise from October to April
JANUARY BAROMETER
an old stock market adage that states, ‘as the S&P goes in January, so goes the year’. Therefore, an up January will foreshadow a year of positive equity returns
JANUARY EFFECT
another theory that states that small cap equities tend to outperform the broader market in the first few days of the new trading year due to investors buying back stocks that were sold for tax loss reasons at the end of the previous fiscal year.
–> This has not worked as well in recent years because arbitrageurs have essentially ‘arbed’ it out of the market
