Class: SQA::MultiTimeframe

Inherits:
Object
  • Object
show all
Defined in:
lib/sqa/multi_timeframe.rb

Overview

MultiTimeframe - Analyze patterns across multiple timeframes

Provides methods for:

  • Timeframe conversion (daily → weekly → monthly)

  • Multi-timeframe signal confirmation

  • Trend alignment across timeframes

  • Support/resistance across timeframes

Common timeframe strategy:

  • Use higher timeframe for trend direction

  • Use lower timeframe for entry timing

Examples:

Multi-timeframe trend alignment

mta = SQA::MultiTimeframe.new(stock: stock)
alignment = mta.trend_alignment
# => { daily: :up, weekly: :up, monthly: :up, aligned: true }

Instance Attribute Summary collapse

Instance Method Summary collapse

Constructor Details

#initialize(stock:) ⇒ MultiTimeframe

Initialize multi-timeframe analyzer

Parameters:

  • stock (SQA::Stock) —

    Stock object with daily data



31
32
33
34
35
36
37
 
# File 'lib/sqa/multi_timeframe.rb', line 31

def initialize(stock:)
  @stock = stock
  @timeframes = {}

  # Convert daily data to other timeframes
  convert_timeframes
end

Instance Attribute Details

#stock ⇒ Object (readonly)

Returns the value of attribute stock.



24
25
26
 
# File 'lib/sqa/multi_timeframe.rb', line 24

def stock
  @stock
end

#timeframes ⇒ Object (readonly)

Returns the value of attribute timeframes.



24
25
26
 
# File 'lib/sqa/multi_timeframe.rb', line 24

def timeframes
  @timeframes
end

Instance Method Details

#confirmation(strategy_class:) ⇒ Hash

Check if timeframes confirm each other

Parameters:

  • strategy_class (Class) —

    Strategy to use

Returns:

  • (Hash) —

    Confirmation status



228
229
230
231
232
233
234
235
236
237
238
239
240
241
242
243
244
245
246
247
248
249
250
251
 
# File 'lib/sqa/multi_timeframe.rb', line 228

def confirmation(strategy_class:)
  signals = {}

  @timeframes.each do |timeframe, data|
    vector = create_vector(data)
    signals[timeframe] = strategy_class.trade(vector)
  end

  # Check agreement
  buy_count = signals.values.count(:buy)
  sell_count = signals.values.count(:sell)

  {
    signals: signals,
    confirmed: buy_count >= 2 || sell_count >= 2,
    consensus: if buy_count >= 2
                 :buy
               elsif sell_count >= 2
                 :sell
               else
                 :hold
               end
  }
end

#convert_timeframes ⇒ Object

Convert daily data to weekly and monthly



42
43
44
45
46
47
48
 
# File 'lib/sqa/multi_timeframe.rb', line 42

def convert_timeframes
  daily_data = @stock.df.data

  @timeframes[:daily] = daily_data
  @timeframes[:weekly] = resample(daily_data, period: 5)
  @timeframes[:monthly] = resample(daily_data, period: 21)
end

#detect_divergence ⇒ Hash

Detect divergence across timeframes

Divergence occurs when price and indicator move in opposite directions.

Returns:

  • (Hash) —

    Divergence information



197
198
199
200
201
202
203
204
205
206
207
208
209
210
211
212
213
214
215
216
217
218
219
220
 
# File 'lib/sqa/multi_timeframe.rb', line 197

def detect_divergence
  divergences = {}

  @timeframes.each do |timeframe, data|
    prices = data["adj_close_price"].to_a
    rsi = SQAI.rsi(prices, period: 14)

    next if prices.size < 20 || rsi.size < 20

    # Compare last 10 periods
    price_trend = prices[-1] > prices[-10]
    rsi_trend = rsi[-1] > rsi[-10]

    divergences[timeframe] = if price_trend && !rsi_trend
                               :bearish_divergence
                             elsif !price_trend && rsi_trend
                               :bullish_divergence
                             else
                               :no_divergence
                             end
  end

  divergences
end

#indicators(indicator:, **options) ⇒ Hash

Calculate indicators for each timeframe

Parameters:

  • indicator (Symbol) —

    Indicator to calculate

  • options (Hash) —

    Indicator options

Returns:

  • (Hash) —

    Indicator values for each timeframe



167
168
169
170
171
172
173
174
175
176
177
178
179
180
181
182
183
184
185
186
187
188
 
# File 'lib/sqa/multi_timeframe.rb', line 167

def indicators(indicator:, **options)
  results = {}

  @timeframes.each do |timeframe, data|
    prices = data["adj_close_price"].to_a

    results[timeframe] = case indicator
                         when :sma
                           SQAI.sma(prices, **options)
                         when :ema
                           SQAI.ema(prices, **options)
                         when :rsi
                           SQAI.rsi(prices, **options)
                         when :macd
                           SQAI.macd(prices, **options)
                         else
                           nil
                         end
  end

  results
end

#signal(strategy_class:, higher_timeframe: :weekly, lower_timeframe: :daily) ⇒ Symbol

Generate multi-timeframe signal

Uses higher timeframe for trend, lower for timing.

Parameters:

  • strategy_class (Class) —

    Strategy to apply

  • higher_timeframe (Symbol) (defaults to: :weekly) —

    Timeframe for trend (:weekly, :monthly)

  • lower_timeframe (Symbol) (defaults to: :daily) —

    Timeframe for entry (:daily, :weekly)

Returns:

  • (Symbol) —

    :buy, :sell, or :hold



102
103
104
105
106
107
108
109
110
111
112
113
114
115
116
117
118
119
120
121
122
123
124
125
126
127
128
 
# File 'lib/sqa/multi_timeframe.rb', line 102

def signal(strategy_class:, higher_timeframe: :weekly, lower_timeframe: :daily)
  # Get trend from higher timeframe
  higher_data = @timeframes[higher_timeframe]
  higher_prices = higher_data["adj_close_price"].to_a

  higher_trend = if higher_prices.last > higher_prices[-10..-1].sum / 10.0
                   :up
                 else
                   :down
                 end

  # Get signal from lower timeframe
  lower_data = @timeframes[lower_timeframe]
  lower_vector = create_vector(lower_data)

  lower_signal = strategy_class.trade(lower_vector)

  # Combine: only take trades aligned with higher timeframe
  case higher_trend
  when :up
    lower_signal == :buy ? :buy : :hold
  when :down
    lower_signal == :sell ? :sell : :hold
  else
    :hold
  end
end

#support_resistance(tolerance: 0.02) ⇒ Hash

Find support/resistance levels across timeframes

Levels that appear on multiple timeframes are stronger.

Parameters:

  • tolerance (Float) (defaults to: 0.02) —

    Price tolerance for matching levels (default: 0.02 for 2%)

Returns:

  • (Hash) —

    Support and resistance levels



138
139
140
141
142
143
144
145
146
147
148
149
150
151
152
153
154
155
156
157
158
 
# File 'lib/sqa/multi_timeframe.rb', line 138

def support_resistance(tolerance: 0.02)
  all_levels = { support: [], resistance: [] }

  @timeframes.each do |timeframe, data|
    prices = data["adj_close_price"].to_a
    levels = find_levels(prices)

    all_levels[:support] += levels[:support].map { |l| { price: l, timeframe: timeframe } }
    all_levels[:resistance] += levels[:resistance].map { |l| { price: l, timeframe: timeframe } }
  end

  # Find levels that appear on multiple timeframes
  strong_support = cluster_levels(all_levels[:support], tolerance)
  strong_resistance = cluster_levels(all_levels[:resistance], tolerance)

  {
    support: strong_support,
    resistance: strong_resistance,
    current_price: @stock.df.data["adj_close_price"].to_a.last
  }
end

#trend_alignment(lookback: 20) ⇒ Hash

Check trend alignment across timeframes

Parameters:

  • lookback (Integer) (defaults to: 20) —

    Periods to look back for trend

Returns:

  • (Hash) —

    Trend direction for each timeframe



56
57
58
59
60
61
62
63
64
65
66
67
68
69
70
71
72
73
74
75
76
77
78
79
80
81
82
83
84
85
86
87
88
89
90
 
# File 'lib/sqa/multi_timeframe.rb', line 56

def trend_alignment(lookback: 20)
  trends = {}

  @timeframes.each do |timeframe, data|
    prices = data["adj_close_price"].to_a
    recent = prices.last([lookback, prices.size].min)

    # Simple trend: compare current to average
    current = recent.last
    avg = recent.sum / recent.size.to_f

    trends[timeframe] = if current > avg * 1.02
                          :up
                        elsif current < avg * 0.98
                          :down
                        else
                          :sideways
                        end
  end

  # Check if all timeframes aligned
  all_up = trends.values.all? { |t| t == :up }
  all_down = trends.values.all? { |t| t == :down }

  trends[:aligned] = all_up || all_down
  trends[:direction] = if all_up
                         :bullish
                       elsif all_down
                         :bearish
                       else
                         :mixed
                       end

  trends
end