 01  Technical versus fundamental analysis
 02  Characteristics
 03  Quiz: Potential indicators
 04  When is technical analysis valuable
 05  When is technical analysis valuable part 2
 06  A few indicators: Momentum
 07  A few indicators: Simple moving average (SMA).
 08  A few indicators Bollinger Bands
 09  Buy or sell
 10  Normalization
 11  Wrap up
01  Technical versus fundamental analysis
Two broad categories of approaches to use for choosing stocks to buy or sell: Fundamental analysis and Technical analysis
Fundamental analysis: looking at aspects of a company to estimate its value and look for the price < value situations.
 earnings, dividends, cash flow, book value
Technical analysis: Looking for patterns or trends in a stock’s price.
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02  Characteristics
Characteristics of technical analysis
 it looks only at price and volume.
 compute statistics (or indicators) on this time series
 Indicators are heuristics that may hint at a buy or sell opportunity.
Criticism of the technical approach
 it’s not an appropriate method for investing, because it’s not considering the value of the companies.
 trading approach as opposed to an investing approach.
Reasons to believe technical analysis
 there is indeed information in price and information in a price change.
 Stock price and price change reflects sentiments of buyers and sellers
 in other domains of artificial intelligence, heuristics can work, and they work frequently.
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03  Quiz: Potential indicators
Look at each one of these four factors and fill in the box, T for technical or F for fundamental.
 the moving average of price is only using price [technical.]
 Percent change in volume is only using volume [technical].
 price/earnings, earning is a fundamental factor, which makes the whole [fundamental].
 intrinsic value is based on dividends [a fundamenta]
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04  When is technical analysis valuable
 individual indicators, by themselves, are weakly predictive. And the more people following a particular approach, the less value is realized
 combining multiple indicators adds value. Combinations of three to five different indicators, in a machine learning context, provide a much stronger predictive system
 contrasts. If certain stocks are behaving differently than the market, then they are worth a further look.
 technical analysis generally works better over shorter time periods.
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05  When is technical analysis valuable part 2
The trading horizon
For fundamental factors: Over long periods of time, fundamental factors provide a lot of value.
 For trading machines on the stock exchange, the order book or momentum, etc really matter, and the fundamental factors really have low value.
 fundamental factors over long periods of time may have significant value.
 over a period of days, Fundamental factors do have value.
for technical factors.
 over long terms technical analysis is not so valuable.
 technical factors potentially have high value over very short periods of time.
decision complexity
 Computerbased trading
 we have to be able to make the decisions really, really fast if we’re trading at the millisecond level.

at this very highfrequency trading, the complexity of decisions is simple. And computers excel in this region of the chart.
 the highfrequency trading computerdriven hedge funds are short in the trading horizon.
 human investors
 we can take a long time to make a decision if we’re going to buy and hold for years.
 If taking a long time to make a decision, it is the best region for human investors.
 The insightdriven, humanbased hedge funds are operating over a long trading horizon.
 there is a middle where we often see humans and computers working together.
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06  A few indicators: Momentum
Three are some of the most common and most popular indicators: 1) momentum, 2( simple moving average, and 3) Bollinger Bands.
momentum
Momentum is over some number of days how much has the price changed: positive momentum and negative momentum

The steepness of that line is the strength of the momentum, either positive or negative.

convert numbers
momentum, N days of momentum. 
the pseudo code for how we compute momentum on a particular day.
momentum[t] = price[t]/price[t  n] 1
, n is the number of days between two time point.
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07  A few indicators: Simple moving average (SMA).
 SMA for today is simply the average of the values over this look back window.
 the SMA looks essentially like a smoothed value of the price chart as it moves around.
 SMA lags the movement.
two different ways that technicians use simple moving average
 look for where the current price crosses through the simple moving average.
 combine that with momentum: the price has strong momentum, and it’s crossing through that simple moving average, that can be a signal.
 strong momentum crossing those lines, then again, that can be a trading signal.
 simple moving average is as a proxy for underlying value.
 The average price might represent the true value of the company.
 we should expect that the price is eventually going to regress to that average. ( it’s an arbitrage opportunity)
quantify SMA
 compare the current price with the current simple moving average, and construct a ratio.
SMA[t] = price[n]/price[tn:t].mean() 1
 This value ranges from 50% to +50%.
Time: 00:03:40
08  A few indicators Bollinger Bands
how much of an excursion from the simple moving average should I use as a signal for a buy or sell?
 a fixed number is probably not the best way to go.
 John Bollinger observed that for low volatility, use a smaller excursion for that trigger. For high volatility, use a larger number.
 the Bollinger Bands: take this simple moving average, but let’s add a band above and below 2 std (standard deviations).
How might we use Bollinger Bands now for trading signals
 look for times where the price’s outside one of these Bollinger Bands and when it crosses to the inside it should be a trading signal.
 Moving from above the band and cross to the inside, selling signal
 Moving from below the band and cross to the inside, buying signal
How to calculate the Bollinger Band on a particular day t
BB[t] = (Price[t] SMA[t]) / (2*std[t])
 BB[t] = 1 or BB[t] = 1 are the crossing point.
 BB[t 1] > 1and BB[t] = 1 and BB[t+1] > 1, then Sell
 BB[t 1] < 1and BB[t] = 1 and BB[t+1] < 1, then buy
 typically expect to BB[t] is between 1 and 1.
 occasionally, we’ll see excursions above and below those values.
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09  Buy or sell
In the four different times where the actual price crosses and upper or lower Bollinger band. Is it a buy signal, a sell signal or no signal at all?
The solution: is in the picture: remember, only when price moves into the Bollinger Band is a trading signal. Moving outside is not.
Time: 00:00:57
10  Normalization
 Simple moving average and momentum are bouned in [.5, +.5] and Bollinger bands in [1, 1].
 When used in a machine learner Bollinger Band factor would tend to overwhelm these other factors and [falsely] become the most important one.
 It might get even worse if we included fundamental factor like PE ratio ranges in [1, 300]
The solution: normalization.
Given values, the normalization works this way:
normalized_values = [values  mean(values)] / std(values)
 normalized_values will range in [1, 1] and have a mean of 0.
⚠️!!Normalize your data if use indicators in machine learning models!!
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11  Wrap up

technical indicators are really heuristics that represent how a statistical approach to previous prices and volume might suggest future price movement.

Tucker’s approach of using Bollinger Band.

🙅♂️Do not start trading. Learn more
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Total Time: 00:22:34
20190220 初稿