Contrasting Models of Finance

Contrasting Models of Finance: Efficient Market Hypothesis vs. Socionomic Theory of Finance

Efficient Market Hypothesis (EMH)	Socionomic Theory of Finance (STF)
1. Objective, conscious, rational decisions to maximize utility determine financial values	1. Subjective, unconscious, pre-rational impulses to herd determine financial values
2. Financial markets tend toward equilibrum and revert to the mean	2. Financial markets are dynamic and do not revert to anything
3. Investors in financial markets typically use information to reason	3. Investors in financial markets typically use information to rationalize emotional imperatives.
4. Investors' decisions are based on knowledge and certainty	4. Investors decisions are fraught with ignorance and uncertainty
5. Exogenous variables determine most investment decisions	5. Endogenous social processes determine most investment decisions
6. Financial prices derive from individual decisions about value	6. Financial prices derive from trends in social mood
7. Financial prices are random	7. Financial prices adhere to an organizing principle at the aggregate level

Source: https://www.socionomics.net/2012/06/contrasting-models-of-finance/

Apple Today (The Market Sum)

Apple Today
Source: Investopedia Market Sum

Strategy testing

1. Profit factor
2. Sharpe Ratio
3. Ulcer Performance Index
4. Compound Annual Growth Rate
5. Maximum Drawdown
6. Percent Profitable Trades
7. Average Win to Average Loss Ratio
8. Equity

2. Sharpe ratio

Sharpe ratio is the measure of risk-adjusted return of a financial portfolio. A portfolio with a higher Sharpe ratio is considered superior relative to its peers. 

The Sharpe ratio is a ratio of return versus risk. The formula is:

Sharpe Ratio = (Total return - Risk-free return) / SD

Total Return = the expected return on the investor's portfolio
The risk-free* rate of return
SD = the portfolio's standard deviation, a measure of risk

* Note that "sharpe ratio" is considering the volatility type of risk, ignoring that treasury notes are not really risk-free but involving other types of risks (inflation, interest rate risk, opportunity costs, etc)

Use Python to calculate the Sharpe ratio for a portfolio

Realised historical return is used to calculate ex-post Sharpe ratio while ex-ante Sharpe ratio employs expected return. 

Read more on Sharpe Ratio on India Times

Sharpe Ratio on Investing Answers

3. Ulcer Index & Ulcer Performance Index

Ulcer index is designed as a measure of volatility, but only volatility in the downward direction, i.e. the amount of drawdown or retracement occurring over a period.

Other volatility measures like standard deviation treat up and down movement equally, but a trader doesn't mind upward movement.

Flirting with Models: Looking into the Ulcer Index

Loss at a single point in time (max drawdown) is far less important than how a strategy manages losses over time (UPI).

http://www.tangotools.com/ui/ui.htm

The Ulcer Performance Index (known also as Martin Index) is calculated as follows:

SumSq = 0
MaxValue = 0
for T = 1 to NumOfPeriods do
if Value[T] > MaxValue then MaxValue = Value[T]
else SumSq = SumSq + sqr(100 * ((Value[T] / MaxValue) - 1))
UI = sqrt(SumSq / NumOfPeriods)

UPI = (Total return - Risk-free return) / UI

Brent Oil downtrend continued

Disclaimer: I am/we are short Brent Oil.

Skin in the Game

Incerto is a  four book bundle written by Nassim Nicholas Taleb

• Antifragile
• The Black Swan
• Fooled by Randomness
• The Bed of Procustes

Nassim Nicholas Taleb's landmark Incerto series is an investigation of luck, uncertainty, probability, opacity, human error, risk, disorder, and decision-making in a world we don’t understand.

TensorFlow Tutorials

• TensorFlow Tutorial - Importing Data
• TensorFlow Tutorial - Opening a Jupyter Notebook
• TensorFlow Tutorial - Running the Neural Network Results

Waiting for a recovery in BTC

Since BTC was at 20000$, because of the tail risk created by the previous parabolic growth, a huge swing to drop it 50% (to 10k) was expected, as last 3 dips in BTC were around 50% each time. But it happened with a large delay, 1 month later. That made Bitcoin lose its strength and enter in a wide range where trend became uncertain. Bulls rejected the support level at 10000$ and BTCUSD was going up for a while. Finally 9500$ support level broke-down and BTC found a strong support only at 6000$.

Good news it that this correction discharged tensions created by the exponential growth tendencies, but first I expect to hit a resistance somewhere below 12000$.