Lecture 8 - High-frequency trading, temporal patterns & cycles

Market Making

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

High Frequency Trading (HFT)

Type of trading using computer algorithms to rapidly trade securitites

• High speeds, high turnover rates, and high order-to-trade ratios

• Making profits on very fast trades, with gains even being cents

HFT firms perform “Market Making” activities using 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

During periods of extreme volatility, firms…

are under no obligation to maintain this activity

Impacts of HFT

1. Liquidity

2. Volatility

3. Price Discovery

4. Market Confidence

Impact of HFT on Liquidity

• 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

Impact of HFT on Volatility

• More aggressive HFT strategies may increase stock volatility

• HFT Liquidity detection strategies “front run” ahead of large institutional orders amplifies price swings

  • Front Running is the illegal practice of having knowledge of your client’s orders and executing your own orders first

Front Running

Illegal practice of having knowledge of your client’s orders and executing your own orders first

Impact of HFT on Price Discovery

• Although HFT strategies are very rapid to help 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 intrinstic value

Impact of HFT on Market Confidence

Sophisticated “Algo” strategies and access to Dark Pools used by HFT firms give them an advantage over regular investors

Benefits of HFT

HFT has made markets more liquid and decreased transaction costs

Harmful effects of HFT

Traders who post standing limit orders that cannot reflect changes in value due to news changes fast enough and lose to HFT

Very Harmful effects of HFT

HFT Traders are 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

Systematic risks posted by algorithmic trading

• Flash crashes

• Algos out of control

• Market terrorism in the wrong hands

Markets need to be slowed because:

fast HFT will make slower HFT go out of business, which decreases competition, making the few firms in the business increase spreads and thus transaction costs will rise

Dark Pools

Private exchanges not accessible to the public, usually owned by a broker-dealer named as such due to their lack of transparency

Objective of Cycle Analysis

Attempts to find recurring major and minor peaks and troughs in price movement for better trade timing

Cycle

Defined as price movement of a market from a local bottom to a local top and back again

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

• We have been unable to identify causes of specific cycles that many agree do exist in prices

3 qualities of cycle

1. Amplitude

2. Period

3. Phase

Amplitude

Measures the height of a wave from peak to trough, signifying the strength of a cycle

Cycles are measured from ____ to _____ as the tops tend to take more time to develop

Trough to trough

Period

Length of a wave is the time spent between troughs

Phase

Measure of time location of a wave trought, the difference between troughs of different waves

4 principles to cycles

1. Summation

2. Harmonicity

3. Synchronicity

4. Proportionality

Summation

All price movement is a simple addition of all active cycles. By combining each cycle & projecting forward, future price targets can be forecast.

Harmonicity

There are waves within waves and that they are usually related. Adjacent cycles are often related by small whole numbers, 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

Relationship between the cycle period and amplitude. Longer-term cycles should also have greater amplitude. There should be a proportional relationship between cycles of differing periods.

For example, if a cycle’s period is 40 days, it should have proportional amplitude that is 2x the amplitude that has a 20-day period.

Variation

States that the 4 principles are just strong tendencies and that they are not hard and fast rules

Nominality

States that there tends to be a nominal set of harmonically related cycles that affect all markets

Translation

The reason we study lows in cycle analysis is because longer and shorter cycles tend to synchronize at their lows. Peaks almost never synchronize

• Peaks should occur at the halfway of the cycle

• Their location away frmo the center point is translation

Kondratieff Waves

Economic phenomena that are not necessarily obseravable in commodity and stock prices.

• Winter: a period of concern, fear, panic, depression

• Spring: a period of fear of depression, fragile confidence

• Summer: a period of growing confidence

• Autumn: a period of increasing confidence, that turns into extreme confidence and euphoria

4 year/Presidential/Kitchin Cycle

• The US suffers a recession every 4 years

• Most widely and easily recognized stock cycle

  • Weak during post-election & mid-year (years 1 & 2)

  • Strong during mid-year 3 and pre election

Seasonal Patterns

• Sell in May and Go away

• August and September being bad bonds for the stock market

• October, November and January being the best months

January Barometer

Old stock market adage that states “as the S&P goes in January, so goes the year”, implying that January will foreshadow a year of positive equity returns

January Effect

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

• No longer works well in recent years as arbitrageurs have solved this

Inversion

When a peak occurs where a cycle low is expected